Overview

Dataset statistics

 Readmitted within 30 Days_Value=0Readmitted within 30 Days_Value=1
Number of variables3636
Number of observations8678012560
Missing cells13140120212
Missing cells (%)4.2%4.5%
Total size in memory15.2 MiB2.2 MiB
Average record size in memory184.0 B184.3 B

Variable types

 Readmitted within 30 Days_Value=0Readmitted within 30 Days_Value=1
Categorical1616
Text77
Numeric1313

Alerts

Readmitted within 30 Days_Value=0Readmitted within 30 Days_Value=1
Readmitted within 30 Days_Value has constant value "0"Readmitted within 30 Days_Value has constant value "1"Constant
A1Cresult is highly imbalanced (53.9%)A1Cresult is highly imbalanced (58.1%)Imbalance
admission_type_id is highly imbalanced (50.5%)Alert not present in this datasetImbalance
metformin is highly imbalanced (58.6%)metformin is highly imbalanced (62.5%)Imbalance
race is highly imbalanced (55.5%)race is highly imbalanced (57.9%)Imbalance
Race is highly imbalanced (55.5%)Race is highly imbalanced (57.9%)Imbalance
A1C is highly imbalanced (53.9%)A1C is highly imbalanced (58.1%)Imbalance
Taking Metformin is highly imbalanced (58.6%)Taking Metformin is highly imbalanced (62.5%)Imbalance
CaseManager_Feedback_30day_30_80_Threshold_Clarity has 19329 (22.3%) missing valuesCaseManager_Feedback_30day_30_80_Threshold_Clarity has 3081 (24.5%) missing valuesMissing
CaseManager_Feedback_30day_30_80_Threshold_Effectiveness has 32053 (36.9%) missing valuesCaseManager_Feedback_30day_30_80_Threshold_Effectiveness has 5201 (41.4%) missing valuesMissing
CaseManager_Feedback_30day_30_80_Threshold_Impact has 32565 (37.5%) missing valuesCaseManager_Feedback_30day_30_80_Threshold_Impact has 4994 (39.8%) missing valuesMissing
PatientSatisfaction_ReadmissionFollowup has 47454 (54.7%) missing valuesPatientSatisfaction_ReadmissionFollowup has 6936 (55.2%) missing valuesMissing
ExpectedHospitalStay has unique valuesAlert not present in this datasetUnique
RiskLongStay has unique valuesRiskLongStay has unique valuesUnique
num_procedures has 39941 (46.0%) zerosnum_procedures has 5738 (45.7%) zerosZeros
Readmitted within 30 Days_Value has 86780 (100.0%) zerosAlert not present in this datasetZeros
Readmitted (Any)_Value has 52524 (60.5%) zerosAlert not present in this datasetZeros
Long Hospital Stay (>7 days)_Value has 74296 (85.6%) zerosLong Hospital Stay (>7 days)_Value has 10333 (82.3%) zerosZeros
Taking Metformin_Value has 68551 (79.0%) zerosTaking Metformin_Value has 10307 (82.1%) zerosZeros
Alert not present in this datasetReadmitted (Any)_Value has constant value "1"Constant
Alert not present in this datasetRisk30DayReadmission has unique valuesUnique
Alert not present in this datasetRiskAnyReadmission has unique valuesUnique

Reproduction

 Readmitted within 30 Days_Value=0Readmitted within 30 Days_Value=1
Analysis started2025-12-01 21:51:59.4888622025-12-01 21:52:00.120714
Analysis finished2025-12-01 21:52:00.1176742025-12-01 21:52:00.335717
Duration0.63 seconds0.22 seconds
Software versionydata-profiling vv4.18.0ydata-profiling vv4.18.0
Download configurationconfig.jsonconfig.json

Variables

A1Cresult
Categorical

 Readmitted within 30 Days_Value=0Readmitted within 30 Days_Value=1
Distinct44
Distinct (%)< 0.1%< 0.1%
Missing00
Missing (%)0.0%0.0%
Memory size762.9 KiB110.6 KiB
None
71835 
>8
7216 
Norm
 
4390
>7
 
3339
None
10671 
>8
 
921
Norm
 
532
>7
 
436

Unique

 Readmitted within 30 Days_Value=0Readmitted within 30 Days_Value=1
Unique00 ?
Unique (%)0.0%0.0%

Sample

 Readmitted within 30 Days_Value=0Readmitted within 30 Days_Value=1
1st rowNoneNorm
2nd rowNoneNone
3rd rowNorm>8
4th row>7None
5th rowNoneNone

Common Values

ValueCountFrequency (%)
None71835
82.8%
>87216
 
8.3%
Norm4390
 
5.1%
>73339
 
3.8%
ValueCountFrequency (%)
None10671
85.0%
>8921
 
7.3%
Norm532
 
4.2%
>7436
 
3.5%

Common Values (Plot)

Readmitted within 30 Days_Value=0

2025-12-01T21:52:00.717735image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Readmitted within 30 Days_Value=1

2025-12-01T21:52:00.766598image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
 Readmitted within 30 Days_Value=0Readmitted within 30 Days_Value=1
Distinct55
Distinct (%)< 0.1%0.1%
Missing193293081
Missing (%)22.3%24.5%
Memory size1.3 MiB196.2 KiB
2025-12-01T21:52:00.874351image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Length

 Readmitted within 30 Days_Value=0Readmitted within 30 Days_Value=1
Max length99
Median length77
Mean length6.56.5
Min length44

Characters and Unicode

 Readmitted within 30 Days_Value=0Readmitted within 30 Days_Value=1
Total characters43825462032
Distinct characters1818
Distinct categories11 ?
Distinct scripts11 ?
Distinct blocks11 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

 Readmitted within 30 Days_Value=0Readmitted within 30 Days_Value=1
Unique00 ?
Unique (%)0.0%0.0%

Sample

 Readmitted within 30 Days_Value=0Readmitted within 30 Days_Value=1
1st rowVery PoorGood
2nd rowNeutralNeutral
3rd rowPoorExcellent
4th rowNeutralExcellent
5th rowPoorExcellent
ValueCountFrequency (%)
good21919
29.7%
excellent19508
26.4%
poor13174
17.8%
neutral12850
17.4%
very6472
 
8.8%
ValueCountFrequency (%)
good3033
29.3%
excellent2909
28.1%
poor1785
17.3%
neutral1752
16.9%
very863
 
8.3%
2025-12-01T21:52:01.079184image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
o70186
 
16.0%
e58338
 
13.3%
l51866
 
11.8%
r32496
 
7.4%
t32358
 
7.4%
Other values (13)193010
44.0%
ValueCountFrequency (%)
o9636
 
15.5%
e8433
 
13.6%
l7570
 
12.2%
t4661
 
7.5%
r4400
 
7.1%
Other values (13)27332
44.1%

Most occurring categories

ValueCountFrequency (%)
(unknown)438254
100.0%
ValueCountFrequency (%)
(unknown)62032
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
o70186
 
16.0%
e58338
 
13.3%
l51866
 
11.8%
r32496
 
7.4%
t32358
 
7.4%
Other values (13)193010
44.0%
ValueCountFrequency (%)
o9636
 
15.5%
e8433
 
13.6%
l7570
 
12.2%
t4661
 
7.5%
r4400
 
7.1%
Other values (13)27332
44.1%

Most occurring scripts

ValueCountFrequency (%)
(unknown)438254
100.0%
ValueCountFrequency (%)
(unknown)62032
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
o70186
 
16.0%
e58338
 
13.3%
l51866
 
11.8%
r32496
 
7.4%
t32358
 
7.4%
Other values (13)193010
44.0%
ValueCountFrequency (%)
o9636
 
15.5%
e8433
 
13.6%
l7570
 
12.2%
t4661
 
7.5%
r4400
 
7.1%
Other values (13)27332
44.1%

Most occurring blocks

ValueCountFrequency (%)
(unknown)438254
100.0%
ValueCountFrequency (%)
(unknown)62032
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
o70186
 
16.0%
e58338
 
13.3%
l51866
 
11.8%
r32496
 
7.4%
t32358
 
7.4%
Other values (13)193010
44.0%
ValueCountFrequency (%)
o9636
 
15.5%
e8433
 
13.6%
l7570
 
12.2%
t4661
 
7.5%
r4400
 
7.1%
Other values (13)27332
44.1%
 Readmitted within 30 Days_Value=0Readmitted within 30 Days_Value=1
Distinct55
Distinct (%)< 0.1%0.1%
Missing320535201
Missing (%)36.9%41.4%
Memory size1.3 MiB196.2 KiB
2025-12-01T21:52:01.196746image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Length

 Readmitted within 30 Days_Value=0Readmitted within 30 Days_Value=1
Max length99
Median length77
Mean length6.56.5
Min length44

Characters and Unicode

 Readmitted within 30 Days_Value=0Readmitted within 30 Days_Value=1
Total characters35638847985
Distinct characters1818
Distinct categories11 ?
Distinct scripts11 ?
Distinct blocks11 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

 Readmitted within 30 Days_Value=0Readmitted within 30 Days_Value=1
Unique00 ?
Unique (%)0.0%0.0%

Sample

 Readmitted within 30 Days_Value=0Readmitted within 30 Days_Value=1
1st rowGoodGood
2nd rowExcellentExcellent
3rd rowNeutralPoor
4th rowExcellentPoor
5th rowGoodNeutral
ValueCountFrequency (%)
good17444
29.1%
excellent15712
26.2%
poor10796
18.0%
neutral10775
17.9%
very5319
 
8.9%
ValueCountFrequency (%)
good2363
29.4%
excellent2119
26.3%
neutral1503
18.7%
poor1374
17.1%
very689
 
8.6%
2025-12-01T21:52:01.390225image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
o56480
 
15.8%
e47518
 
13.3%
l42199
 
11.8%
r26890
 
7.5%
t26487
 
7.4%
Other values (13)156814
44.0%
ValueCountFrequency (%)
o7474
 
15.6%
e6430
 
13.4%
l5741
 
12.0%
t3622
 
7.5%
r3566
 
7.4%
Other values (13)21152
44.1%

Most occurring categories

ValueCountFrequency (%)
(unknown)356388
100.0%
ValueCountFrequency (%)
(unknown)47985
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
o56480
 
15.8%
e47518
 
13.3%
l42199
 
11.8%
r26890
 
7.5%
t26487
 
7.4%
Other values (13)156814
44.0%
ValueCountFrequency (%)
o7474
 
15.6%
e6430
 
13.4%
l5741
 
12.0%
t3622
 
7.5%
r3566
 
7.4%
Other values (13)21152
44.1%

Most occurring scripts

ValueCountFrequency (%)
(unknown)356388
100.0%
ValueCountFrequency (%)
(unknown)47985
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
o56480
 
15.8%
e47518
 
13.3%
l42199
 
11.8%
r26890
 
7.5%
t26487
 
7.4%
Other values (13)156814
44.0%
ValueCountFrequency (%)
o7474
 
15.6%
e6430
 
13.4%
l5741
 
12.0%
t3622
 
7.5%
r3566
 
7.4%
Other values (13)21152
44.1%

Most occurring blocks

ValueCountFrequency (%)
(unknown)356388
100.0%
ValueCountFrequency (%)
(unknown)47985
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
o56480
 
15.8%
e47518
 
13.3%
l42199
 
11.8%
r26890
 
7.5%
t26487
 
7.4%
Other values (13)156814
44.0%
ValueCountFrequency (%)
o7474
 
15.6%
e6430
 
13.4%
l5741
 
12.0%
t3622
 
7.5%
r3566
 
7.4%
Other values (13)21152
44.1%
 Readmitted within 30 Days_Value=0Readmitted within 30 Days_Value=1
Distinct55
Distinct (%)< 0.1%0.1%
Missing325654994
Missing (%)37.5%39.8%
Memory size1.3 MiB196.2 KiB
2025-12-01T21:52:01.508359image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Length

 Readmitted within 30 Days_Value=0Readmitted within 30 Days_Value=1
Max length99
Median length77
Mean length6.56.5
Min length44

Characters and Unicode

 Readmitted within 30 Days_Value=0Readmitted within 30 Days_Value=1
Total characters35273349489
Distinct characters1818
Distinct categories11 ?
Distinct scripts11 ?
Distinct blocks11 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

 Readmitted within 30 Days_Value=0Readmitted within 30 Days_Value=1
Unique00 ?
Unique (%)0.0%0.0%

Sample

 Readmitted within 30 Days_Value=0Readmitted within 30 Days_Value=1
1st rowExcellentVery Poor
2nd rowNeutralGood
3rd rowGoodNeutral
4th rowGoodGood
5th rowVery PoorNeutral
ValueCountFrequency (%)
good17386
29.2%
excellent15443
25.9%
poor10765
18.1%
neutral10621
17.8%
very5359
 
9.0%
ValueCountFrequency (%)
good2429
29.5%
excellent2337
28.4%
neutral1420
17.3%
poor1380
16.8%
very656
 
8.0%
2025-12-01T21:52:01.701647image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
o56302
 
16.0%
e46866
 
13.3%
l41507
 
11.8%
r26745
 
7.6%
t26064
 
7.4%
Other values (13)155249
44.0%
ValueCountFrequency (%)
o7618
 
15.4%
e6750
 
13.6%
l6094
 
12.3%
t3757
 
7.6%
r3456
 
7.0%
Other values (13)21814
44.1%

Most occurring categories

ValueCountFrequency (%)
(unknown)352733
100.0%
ValueCountFrequency (%)
(unknown)49489
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
o56302
 
16.0%
e46866
 
13.3%
l41507
 
11.8%
r26745
 
7.6%
t26064
 
7.4%
Other values (13)155249
44.0%
ValueCountFrequency (%)
o7618
 
15.4%
e6750
 
13.6%
l6094
 
12.3%
t3757
 
7.6%
r3456
 
7.0%
Other values (13)21814
44.1%

Most occurring scripts

ValueCountFrequency (%)
(unknown)352733
100.0%
ValueCountFrequency (%)
(unknown)49489
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
o56302
 
16.0%
e46866
 
13.3%
l41507
 
11.8%
r26745
 
7.6%
t26064
 
7.4%
Other values (13)155249
44.0%
ValueCountFrequency (%)
o7618
 
15.4%
e6750
 
13.6%
l6094
 
12.3%
t3757
 
7.6%
r3456
 
7.0%
Other values (13)21814
44.1%

Most occurring blocks

ValueCountFrequency (%)
(unknown)352733
100.0%
ValueCountFrequency (%)
(unknown)49489
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
o56302
 
16.0%
e46866
 
13.3%
l41507
 
11.8%
r26745
 
7.6%
t26064
 
7.4%
Other values (13)155249
44.0%
ValueCountFrequency (%)
o7618
 
15.4%
e6750
 
13.6%
l6094
 
12.3%
t3757
 
7.6%
r3456
 
7.0%
Other values (13)21814
44.1%

ExpectedHospitalStay
Real number (ℝ)

 Readmitted within 30 Days_Value=0Readmitted within 30 Days_Value=1
Distinct8678012559
Distinct (%)100.0%> 99.9%
Missing00
Missing (%)0.0%0.0%
Infinite00
Infinite (%)0.0%0.0%
Mean4.34.7
 Readmitted within 30 Days_Value=0Readmitted within 30 Days_Value=1
Minimum0.570.65
Maximum1313
Zeros00
Zeros (%)0.0%0.0%
Negative00
Negative (%)0.0%0.0%
Memory size1.3 MiB196.2 KiB
2025-12-01T21:52:01.819687image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Quantile statistics

 Readmitted within 30 Days_Value=0Readmitted within 30 Days_Value=1
Minimum0.570.65
5-th percentile1.92.1
Q12.93.3
median3.94.4
Q35.45.8
95-th percentile8.28.7
Maximum1313
Range1313
Interquartile range (IQR)2.52.6

Descriptive statistics

 Readmitted within 30 Days_Value=0Readmitted within 30 Days_Value=1
Standard deviation1.92
Coefficient of variation (CV)0.450.42
Kurtosis0.580.38
Mean4.34.7
Median Absolute Deviation (MAD)1.21.3
Skewness0.940.83
Sum3.8 × 1056 × 104
Variance3.74
MonotonicityNot monotonicNot monotonic
2025-12-01T21:52:01.972073image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
7.4206196881
 
< 0.1%
4.7635349191
 
< 0.1%
8.1155947741
 
< 0.1%
10.854278211
 
< 0.1%
9.9275720691
 
< 0.1%
Other values (86775)86775
> 99.9%
ValueCountFrequency (%)
1.6864070992
 
< 0.1%
3.7216118041
 
< 0.1%
3.9939556211
 
< 0.1%
3.3340049031
 
< 0.1%
3.4641216491
 
< 0.1%
Other values (12554)12554
> 99.9%
ValueCountFrequency (%)
0.56656170941
< 0.1%
0.6388334111
< 0.1%
0.70743187271
< 0.1%
0.70828869941
< 0.1%
0.7165622321
< 0.1%
ValueCountFrequency (%)
0.65240521991
< 0.1%
0.75405913121
< 0.1%
0.82292848321
< 0.1%
0.82667693181
< 0.1%
0.85976592581
< 0.1%
ValueCountFrequency (%)
0.65240521991
< 0.1%
0.75405913121
< 0.1%
0.82292848321
< 0.1%
0.82667693181
< 0.1%
0.85976592581
< 0.1%
ValueCountFrequency (%)
0.56656170941
< 0.1%
0.6388334111
< 0.1%
0.70743187271
< 0.1%
0.70828869941
< 0.1%
0.7165622321
< 0.1%
 Readmitted within 30 Days_Value=0Readmitted within 30 Days_Value=1
Distinct55
Distinct (%)< 0.1%0.1%
Missing474546936
Missing (%)54.7%55.2%
Memory size1.3 MiB196.2 KiB
2025-12-01T21:52:02.123249image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Length

 Readmitted within 30 Days_Value=0Readmitted within 30 Days_Value=1
Max length99
Median length77
Mean length6.56.5
Min length44

Characters and Unicode

 Readmitted within 30 Days_Value=0Readmitted within 30 Days_Value=1
Total characters25566036579
Distinct characters1818
Distinct categories11 ?
Distinct scripts11 ?
Distinct blocks11 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

 Readmitted within 30 Days_Value=0Readmitted within 30 Days_Value=1
Unique00 ?
Unique (%)0.0%0.0%

Sample

 Readmitted within 30 Days_Value=0Readmitted within 30 Days_Value=1
1st rowNeutralGood
2nd rowExcellentPoor
3rd rowGoodExcellent
4th rowVery PoorPoor
5th rowNeutralVery Poor
ValueCountFrequency (%)
poor10265
23.3%
good10235
23.2%
neutral9822
22.3%
excellent9004
20.4%
very4774
10.8%
ValueCountFrequency (%)
neutral1506
23.9%
poor1442
22.9%
good1428
22.7%
excellent1248
19.8%
very665
10.6%
2025-12-01T21:52:02.323692image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
o41000
 
16.0%
e32604
 
12.8%
l27830
 
10.9%
r24861
 
9.7%
t18826
 
7.4%
Other values (13)110539
43.2%
ValueCountFrequency (%)
o5740
 
15.7%
e4667
 
12.8%
l4002
 
10.9%
r3613
 
9.9%
t2754
 
7.5%
Other values (13)15803
43.2%

Most occurring categories

ValueCountFrequency (%)
(unknown)255660
100.0%
ValueCountFrequency (%)
(unknown)36579
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
o41000
 
16.0%
e32604
 
12.8%
l27830
 
10.9%
r24861
 
9.7%
t18826
 
7.4%
Other values (13)110539
43.2%
ValueCountFrequency (%)
o5740
 
15.7%
e4667
 
12.8%
l4002
 
10.9%
r3613
 
9.9%
t2754
 
7.5%
Other values (13)15803
43.2%

Most occurring scripts

ValueCountFrequency (%)
(unknown)255660
100.0%
ValueCountFrequency (%)
(unknown)36579
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
o41000
 
16.0%
e32604
 
12.8%
l27830
 
10.9%
r24861
 
9.7%
t18826
 
7.4%
Other values (13)110539
43.2%
ValueCountFrequency (%)
o5740
 
15.7%
e4667
 
12.8%
l4002
 
10.9%
r3613
 
9.9%
t2754
 
7.5%
Other values (13)15803
43.2%

Most occurring blocks

ValueCountFrequency (%)
(unknown)255660
100.0%
ValueCountFrequency (%)
(unknown)36579
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
o41000
 
16.0%
e32604
 
12.8%
l27830
 
10.9%
r24861
 
9.7%
t18826
 
7.4%
Other values (13)110539
43.2%
ValueCountFrequency (%)
o5740
 
15.7%
e4667
 
12.8%
l4002
 
10.9%
r3613
 
9.9%
t2754
 
7.5%
Other values (13)15803
43.2%

Risk30DayReadmission
Real number (ℝ)

 Readmitted within 30 Days_Value=0Readmitted within 30 Days_Value=1
Distinct8672312560
Distinct (%)99.9%100.0%
Missing00
Missing (%)0.0%0.0%
Infinite00
Infinite (%)0.0%0.0%
Mean0.10.18
 Readmitted within 30 Days_Value=0Readmitted within 30 Days_Value=1
Minimum0.0160.021
Maximum0.620.82
Zeros00
Zeros (%)0.0%0.0%
Negative00
Negative (%)0.0%0.0%
Memory size1.3 MiB196.2 KiB
2025-12-01T21:52:02.440446image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Quantile statistics

 Readmitted within 30 Days_Value=0Readmitted within 30 Days_Value=1
Minimum0.0160.021
5-th percentile0.040.061
Q10.0640.1
median0.0890.15
Q30.130.22
95-th percentile0.220.39
Maximum0.620.82
Range0.60.8
Interquartile range (IQR)0.0670.12

Descriptive statistics

 Readmitted within 30 Days_Value=0Readmitted within 30 Days_Value=1
Standard deviation0.0590.11
Coefficient of variation (CV)0.570.6
Kurtosis5.23
Mean0.10.18
Median Absolute Deviation (MAD)0.0310.059
Skewness1.81.5
Sum9.1 × 1032.2 × 103
Variance0.00350.011
MonotonicityNot monotonicNot monotonic
2025-12-01T21:52:02.592149image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.023527511516
 
< 0.1%
0.022526796754
 
< 0.1%
0.021966215923
 
< 0.1%
0.021030478783
 
< 0.1%
0.079530609273
 
< 0.1%
Other values (86718)86761
> 99.9%
ValueCountFrequency (%)
0.21191457131
 
< 0.1%
0.10062310751
 
< 0.1%
0.15338849741
 
< 0.1%
0.08946786231
 
< 0.1%
0.15426819821
 
< 0.1%
Other values (12555)12555
> 99.9%
ValueCountFrequency (%)
0.015524674631
< 0.1%
0.015712900721
< 0.1%
0.016354168761
< 0.1%
0.01723173911
< 0.1%
0.017359795611
< 0.1%
ValueCountFrequency (%)
0.020605706341
< 0.1%
0.023273143671
< 0.1%
0.025154211911
< 0.1%
0.025681446551
< 0.1%
0.026110838741
< 0.1%
ValueCountFrequency (%)
0.020605706341
< 0.1%
0.023273143671
< 0.1%
0.025154211911
< 0.1%
0.025681446551
< 0.1%
0.026110838741
< 0.1%
ValueCountFrequency (%)
0.015524674631
< 0.1%
0.015712900721
< 0.1%
0.016354168761
< 0.1%
0.01723173911
< 0.1%
0.017359795611
< 0.1%
 Readmitted within 30 Days_Value=0Readmitted within 30 Days_Value=1
Distinct6177
Distinct (%)0.1%0.6%
Missing00
Missing (%)0.0%0.0%
Infinite00
Infinite (%)0.0%0.0%
Mean1017
 Readmitted within 30 Days_Value=0Readmitted within 30 Days_Value=1
Minimum12
Maximum6182
Zeros00
Zeros (%)0.0%0.0%
Negative00
Negative (%)0.0%0.0%
Memory size1.3 MiB196.2 KiB
2025-12-01T21:52:02.974647image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Quantile statistics

 Readmitted within 30 Days_Value=0Readmitted within 30 Days_Value=1
Minimum12
5-th percentile46
Q169
median815
Q31322
95-th percentile2138
Maximum6182
Range6080
Interquartile range (IQR)713

Descriptive statistics

 Readmitted within 30 Days_Value=0Readmitted within 30 Days_Value=1
Standard deviation5.911
Coefficient of variation (CV)0.60.61
Kurtosis5.13
Mean1017
Median Absolute Deviation (MAD)36
Skewness1.81.5
Sum8.7 × 1052.2 × 105
Variance351.1 × 102
MonotonicityNot monotonicNot monotonic
2025-12-01T21:52:03.128567image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
69051
 
10.4%
78533
 
9.8%
58109
 
9.3%
87734
 
8.9%
96600
 
7.6%
Other values (56)46753
53.9%
ValueCountFrequency (%)
8710
 
5.7%
9701
 
5.6%
10647
 
5.2%
11622
 
5.0%
7621
 
4.9%
Other values (72)9259
73.7%
ValueCountFrequency (%)
147
 
0.1%
21037
 
1.2%
33202
 
3.7%
46078
7.0%
58109
9.3%
ValueCountFrequency (%)
210
 
0.1%
355
 
0.4%
4174
 
1.4%
5331
2.6%
6542
4.3%
ValueCountFrequency (%)
210
 
< 0.1%
355
 
0.1%
4174
 
0.2%
5331
0.4%
6542
0.6%
ValueCountFrequency (%)
147
 
0.4%
21037
 
8.3%
33202
 
25.5%
46078
48.4%
58109
64.6%

RiskAnyReadmission
Real number (ℝ)

 Readmitted within 30 Days_Value=0Readmitted within 30 Days_Value=1
Distinct8677712560
Distinct (%)> 99.9%100.0%
Missing00
Missing (%)0.0%0.0%
Infinite00
Infinite (%)0.0%0.0%
Mean0.460.56
 Readmitted within 30 Days_Value=0Readmitted within 30 Days_Value=1
Minimum0.0430.081
Maximum0.970.97
Zeros00
Zeros (%)0.0%0.0%
Negative00
Negative (%)0.0%0.0%
Memory size1.3 MiB196.2 KiB
2025-12-01T21:52:03.281118image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Quantile statistics

 Readmitted within 30 Days_Value=0Readmitted within 30 Days_Value=1
Minimum0.0430.081
5-th percentile0.170.25
Q10.310.42
median0.450.58
Q30.60.7
95-th percentile0.760.85
Maximum0.970.97
Range0.930.89
Interquartile range (IQR)0.290.28

Descriptive statistics

 Readmitted within 30 Days_Value=0Readmitted within 30 Days_Value=1
Standard deviation0.180.18
Coefficient of variation (CV)0.40.33
Kurtosis-0.81-0.73
Mean0.460.56
Median Absolute Deviation (MAD)0.140.14
Skewness0.14-0.13
Sum4 × 1047 × 103
Variance0.0340.033
MonotonicityNot monotonicNot monotonic
2025-12-01T21:52:03.433263image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.54726442772
 
< 0.1%
0.63613439632
 
< 0.1%
0.68854469232
 
< 0.1%
0.33662078311
 
< 0.1%
0.47694173251
 
< 0.1%
Other values (86772)86772
> 99.9%
ValueCountFrequency (%)
0.5704236731
 
< 0.1%
0.40420468011
 
< 0.1%
0.52714059251
 
< 0.1%
0.46898147481
 
< 0.1%
0.34001792441
 
< 0.1%
Other values (12555)12555
> 99.9%
ValueCountFrequency (%)
0.042914160721
< 0.1%
0.047188465631
< 0.1%
0.050530594961
< 0.1%
0.053423416331
< 0.1%
0.054997311731
< 0.1%
ValueCountFrequency (%)
0.081024071791
< 0.1%
0.096850975241
< 0.1%
0.097017706371
< 0.1%
0.10505702161
< 0.1%
0.10620927691
< 0.1%
ValueCountFrequency (%)
0.081024071791
< 0.1%
0.096850975241
< 0.1%
0.097017706371
< 0.1%
0.10505702161
< 0.1%
0.10620927691
< 0.1%
ValueCountFrequency (%)
0.042914160721
< 0.1%
0.047188465631
< 0.1%
0.050530594961
< 0.1%
0.053423416331
< 0.1%
0.054997311731
< 0.1%

RiskLongStay
Real number (ℝ)

 Readmitted within 30 Days_Value=0Readmitted within 30 Days_Value=1
Distinct8678012560
Distinct (%)100.0%100.0%
Missing00
Missing (%)0.0%0.0%
Infinite00
Infinite (%)0.0%0.0%
Mean0.140.18
 Readmitted within 30 Days_Value=0Readmitted within 30 Days_Value=1
Minimum0.00250.0029
Maximum0.950.94
Zeros00
Zeros (%)0.0%0.0%
Negative00
Negative (%)0.0%0.0%
Memory size1.3 MiB196.2 KiB
2025-12-01T21:52:03.585261image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Quantile statistics

 Readmitted within 30 Days_Value=0Readmitted within 30 Days_Value=1
Minimum0.00250.0029
5-th percentile0.00910.012
Q10.0240.035
median0.0630.091
Q30.180.25
95-th percentile0.590.65
Maximum0.950.94
Range0.950.94
Interquartile range (IQR)0.160.21

Descriptive statistics

 Readmitted within 30 Days_Value=0Readmitted within 30 Days_Value=1
Standard deviation0.180.2
Coefficient of variation (CV)1.31.1
Kurtosis3.31.9
Mean0.140.18
Median Absolute Deviation (MAD)0.0480.069
Skewness1.91.6
Sum1.2 × 1042.2 × 103
Variance0.0340.041
MonotonicityNot monotonicNot monotonic
2025-12-01T21:52:03.736309image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.42742724091
 
< 0.1%
0.097723621891
 
< 0.1%
0.54603840231
 
< 0.1%
0.84552936861
 
< 0.1%
0.79006932621
 
< 0.1%
Other values (86775)86775
> 99.9%
ValueCountFrequency (%)
0.5324123431
 
< 0.1%
0.64232665981
 
< 0.1%
0.91310466121
 
< 0.1%
0.77698633691
 
< 0.1%
0.8833695271
 
< 0.1%
Other values (12555)12555
> 99.9%
ValueCountFrequency (%)
0.0025491973361
< 0.1%
0.0025640219011
< 0.1%
0.0025696161571
< 0.1%
0.0027625701921
< 0.1%
0.002853768831
< 0.1%
ValueCountFrequency (%)
0.0028597530521
< 0.1%
0.0028869775521
< 0.1%
0.0029888642021
< 0.1%
0.0033788009831
< 0.1%
0.0033945177531
< 0.1%
ValueCountFrequency (%)
0.0028597530521
< 0.1%
0.0028869775521
< 0.1%
0.0029888642021
< 0.1%
0.0033788009831
< 0.1%
0.0033945177531
< 0.1%
ValueCountFrequency (%)
0.0025491973361
< 0.1%
0.0025640219011
< 0.1%
0.0025696161571
< 0.1%
0.0027625701921
< 0.1%
0.002853768831
< 0.1%

admission_type_id
Categorical

 Readmitted within 30 Days_Value=0Readmitted within 30 Days_Value=1
Distinct54
Distinct (%)< 0.1%< 0.1%
Missing00
Missing (%)0.0%0.0%
Memory size762.9 KiB110.6 KiB
Emergency
61342 
Elective
16518 
Unknown
8893 
Trauma Center
 
18
New Born
 
9
Emergency
9159 
Elective
2149 
Unknown
1251 
New Born
 
1

Unique

 Readmitted within 30 Days_Value=0Readmitted within 30 Days_Value=1
Unique01 ?
Unique (%)0.0%< 0.1%

Sample

 Readmitted within 30 Days_Value=0Readmitted within 30 Days_Value=1
1st rowElectiveEmergency
2nd rowUnknownUnknown
3rd rowUnknownEmergency
4th rowUnknownEmergency
5th rowUnknownEmergency

Common Values

ValueCountFrequency (%)
Emergency61342
70.7%
Elective16518
 
19.0%
Unknown8893
 
10.2%
Trauma Center18
 
< 0.1%
New Born9
 
< 0.1%
ValueCountFrequency (%)
Emergency9159
72.9%
Elective2149
 
17.1%
Unknown1251
 
10.0%
New Born1
 
< 0.1%

Common Values (Plot)

Readmitted within 30 Days_Value=0

2025-12-01T21:52:03.826219image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Readmitted within 30 Days_Value=1

2025-12-01T21:52:03.885988image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

age
Categorical

 Readmitted within 30 Days_Value=0Readmitted within 30 Days_Value=1
Distinct55
Distinct (%)< 0.1%< 0.1%
Missing00
Missing (%)0.0%0.0%
Memory size762.9 KiB110.6 KiB
70+
38369 
[50-70)
34453 
[20-50)
13160 
[10-20)
 
642
[0-10)
 
156
70+
5983 
[50-70)
4665 
[20-50)
1860 
[10-20)
 
48
[0-10)
 
4

Unique

 Readmitted within 30 Days_Value=0Readmitted within 30 Days_Value=1
Unique00 ?
Unique (%)0.0%0.0%

Sample

 Readmitted within 30 Days_Value=0Readmitted within 30 Days_Value=1
1st row70+70+
2nd row[20-50)70+
3rd row70+70+
4th row70+[50-70)
5th row70+70+

Common Values

ValueCountFrequency (%)
70+38369
44.2%
[50-70)34453
39.7%
[20-50)13160
 
15.2%
[10-20)642
 
0.7%
[0-10)156
 
0.2%
ValueCountFrequency (%)
70+5983
47.6%
[50-70)4665
37.1%
[20-50)1860
 
14.8%
[10-20)48
 
0.4%
[0-10)4
 
< 0.1%

Common Values (Plot)

Readmitted within 30 Days_Value=0

2025-12-01T21:52:03.943972image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Readmitted within 30 Days_Value=1

2025-12-01T21:52:04.008689image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

department
['Text', 'Text']

 Readmitted within 30 Days_Value=0Readmitted within 30 Days_Value=1
Distinct99
Distinct (%)< 0.1%0.1%
Missing00
Missing (%)0.0%0.0%
Memory size1.3 MiB196.2 KiB
2025-12-01T21:52:04.149797image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Length

 Readmitted within 30 Days_Value=0Readmitted within 30 Days_Value=1
Max length2020
Median length1818
Mean length1212
Min length88

Characters and Unicode

 Readmitted within 30 Days_Value=0Readmitted within 30 Days_Value=1
Total characters1061141153398
Distinct characters2828
Distinct categories11 ?
Distinct scripts11 ?
Distinct blocks11 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

 Readmitted within 30 Days_Value=0Readmitted within 30 Days_Value=1
Unique00 ?
Unique (%)0.0%0.0%

Sample

 Readmitted within 30 Days_Value=0Readmitted within 30 Days_Value=1
1st rowNephrologyGeriatrics
2nd rowPharmacyPharmacy
3rd rowEndocrinologyPodiatry
4th rowInternal MedicineEndocrinology
5th rowPodiatryPharmacy
ValueCountFrequency (%)
endocrinology20601
19.1%
cardiology14006
13.0%
pharmacy12480
11.6%
internal11478
10.6%
medicine11478
10.6%
geriatrics8154
 
7.6%
podiatry5406
 
5.0%
emergency5282
 
4.9%
department5282
 
4.9%
nephrology5105
 
4.7%
Other values (2)8536
7.9%
ValueCountFrequency (%)
endocrinology2965
19.0%
cardiology1997
12.8%
pharmacy1839
11.8%
internal1651
10.6%
medicine1651
10.6%
geriatrics1163
 
7.5%
podiatry785
 
5.0%
nephrology768
 
4.9%
emergency729
 
4.7%
department729
 
4.7%
Other values (2)1326
8.5%
2025-12-01T21:52:04.378542image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
o109699
 
10.3%
r104484
 
9.8%
i92081
 
8.7%
n90468
 
8.5%
e77357
 
7.3%
Other values (23)587052
55.3%
ValueCountFrequency (%)
o15873
 
10.3%
r15115
 
9.9%
i13364
 
8.7%
n13004
 
8.5%
e11126
 
7.3%
Other values (23)84916
55.4%

Most occurring categories

ValueCountFrequency (%)
(unknown)1061141
100.0%
ValueCountFrequency (%)
(unknown)153398
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
o109699
 
10.3%
r104484
 
9.8%
i92081
 
8.7%
n90468
 
8.5%
e77357
 
7.3%
Other values (23)587052
55.3%
ValueCountFrequency (%)
o15873
 
10.3%
r15115
 
9.9%
i13364
 
8.7%
n13004
 
8.5%
e11126
 
7.3%
Other values (23)84916
55.4%

Most occurring scripts

ValueCountFrequency (%)
(unknown)1061141
100.0%
ValueCountFrequency (%)
(unknown)153398
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
o109699
 
10.3%
r104484
 
9.8%
i92081
 
8.7%
n90468
 
8.5%
e77357
 
7.3%
Other values (23)587052
55.3%
ValueCountFrequency (%)
o15873
 
10.3%
r15115
 
9.9%
i13364
 
8.7%
n13004
 
8.5%
e11126
 
7.3%
Other values (23)84916
55.4%

Most occurring blocks

ValueCountFrequency (%)
(unknown)1061141
100.0%
ValueCountFrequency (%)
(unknown)153398
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
o109699
 
10.3%
r104484
 
9.8%
i92081
 
8.7%
n90468
 
8.5%
e77357
 
7.3%
Other values (23)587052
55.3%
ValueCountFrequency (%)
o15873
 
10.3%
r15115
 
9.9%
i13364
 
8.7%
n13004
 
8.5%
e11126
 
7.3%
Other values (23)84916
55.4%

gender
Categorical

 Readmitted within 30 Days_Value=0Readmitted within 30 Days_Value=1
Distinct22
Distinct (%)< 0.1%< 0.1%
Missing00
Missing (%)0.0%0.0%
Memory size762.8 KiB110.5 KiB
Female
46603 
Male
40177 
Female
6851 
Male
5709 

Unique

 Readmitted within 30 Days_Value=0Readmitted within 30 Days_Value=1
Unique00 ?
Unique (%)0.0%0.0%

Sample

 Readmitted within 30 Days_Value=0Readmitted within 30 Days_Value=1
1st rowFemaleMale
2nd rowMaleFemale
3rd rowFemaleMale
4th rowFemaleFemale
5th rowFemaleMale

Common Values

ValueCountFrequency (%)
Female46603
53.7%
Male40177
46.3%
ValueCountFrequency (%)
Female6851
54.5%
Male5709
45.5%

Common Values (Plot)

Readmitted within 30 Days_Value=0

2025-12-01T21:52:04.430221image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Readmitted within 30 Days_Value=1

2025-12-01T21:52:04.466861image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

insulin
Categorical

 Readmitted within 30 Days_Value=0Readmitted within 30 Days_Value=1
Distinct44
Distinct (%)< 0.1%< 0.1%
Missing00
Missing (%)0.0%0.0%
Memory size762.9 KiB110.6 KiB
No
41084 
Steady
26289 
Down
10049 
Up
9358 
No
5292 
Steady
3780 
Down
1859 
Up
1629 

Unique

 Readmitted within 30 Days_Value=0Readmitted within 30 Days_Value=1
Unique00 ?
Unique (%)0.0%0.0%

Sample

 Readmitted within 30 Days_Value=0Readmitted within 30 Days_Value=1
1st rowDownUp
2nd rowNoSteady
3rd rowNoDown
4th rowUpSteady
5th rowDownSteady

Common Values

ValueCountFrequency (%)
No41084
47.3%
Steady26289
30.3%
Down10049
 
11.6%
Up9358
 
10.8%
ValueCountFrequency (%)
No5292
42.1%
Steady3780
30.1%
Down1859
 
14.8%
Up1629
 
13.0%

Common Values (Plot)

Readmitted within 30 Days_Value=0

2025-12-01T21:52:04.510104image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Readmitted within 30 Days_Value=1

2025-12-01T21:52:04.565819image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

location
['Text', 'Text']

 Readmitted within 30 Days_Value=0Readmitted within 30 Days_Value=1
Distinct55
Distinct (%)< 0.1%< 0.1%
Missing00
Missing (%)0.0%0.0%
Memory size1.3 MiB196.2 KiB
2025-12-01T21:52:04.705127image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Length

 Readmitted within 30 Days_Value=0Readmitted within 30 Days_Value=1
Max length2828
Median length2525
Mean length2222
Min length1818

Characters and Unicode

 Readmitted within 30 Days_Value=0Readmitted within 30 Days_Value=1
Total characters1890396274115
Distinct characters2929
Distinct categories11 ?
Distinct scripts11 ?
Distinct blocks11 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

 Readmitted within 30 Days_Value=0Readmitted within 30 Days_Value=1
Unique00 ?
Unique (%)0.0%0.0%

Sample

 Readmitted within 30 Days_Value=0Readmitted within 30 Days_Value=1
1st rowUrban Medical CenterUrban Medical Center
2nd rowRegional Health SystemSpecialty Diabetes Institute
3rd rowSpecialty Diabetes InstituteRegional Health System
4th rowCommunity HospitalRegional Health System
5th rowRegional Health SystemSpecialty Diabetes Institute
ValueCountFrequency (%)
medical34722
14.3%
urban26012
10.7%
center26012
10.7%
regional21588
8.9%
health21588
8.9%
system21588
8.9%
community17569
7.2%
hospital17569
7.2%
specialty12901
 
5.3%
diabetes12901
 
5.3%
Other values (3)30321
12.5%
ValueCountFrequency (%)
medical5000
14.2%
urban3739
10.6%
center3739
10.6%
regional3165
9.0%
health3165
9.0%
system3165
9.0%
community2488
7.1%
hospital2488
7.1%
specialty1907
 
5.4%
diabetes1907
 
5.4%
Other values (3)4429
12.6%
2025-12-01T21:52:04.931463image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
e220534
 
11.7%
t186251
 
9.9%
a164701
 
8.7%
155991
 
8.3%
i147571
 
7.8%
Other values (24)1015348
53.7%
ValueCountFrequency (%)
e32123
 
11.7%
t27102
 
9.9%
a23893
 
8.7%
22632
 
8.3%
i21384
 
7.8%
Other values (24)146981
53.6%

Most occurring categories

ValueCountFrequency (%)
(unknown)1890396
100.0%
ValueCountFrequency (%)
(unknown)274115
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
e220534
 
11.7%
t186251
 
9.9%
a164701
 
8.7%
155991
 
8.3%
i147571
 
7.8%
Other values (24)1015348
53.7%
ValueCountFrequency (%)
e32123
 
11.7%
t27102
 
9.9%
a23893
 
8.7%
22632
 
8.3%
i21384
 
7.8%
Other values (24)146981
53.6%

Most occurring scripts

ValueCountFrequency (%)
(unknown)1890396
100.0%
ValueCountFrequency (%)
(unknown)274115
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
e220534
 
11.7%
t186251
 
9.9%
a164701
 
8.7%
155991
 
8.3%
i147571
 
7.8%
Other values (24)1015348
53.7%
ValueCountFrequency (%)
e32123
 
11.7%
t27102
 
9.9%
a23893
 
8.7%
22632
 
8.3%
i21384
 
7.8%
Other values (24)146981
53.6%

Most occurring blocks

ValueCountFrequency (%)
(unknown)1890396
100.0%
ValueCountFrequency (%)
(unknown)274115
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
e220534
 
11.7%
t186251
 
9.9%
a164701
 
8.7%
155991
 
8.3%
i147571
 
7.8%
Other values (24)1015348
53.7%
ValueCountFrequency (%)
e32123
 
11.7%
t27102
 
9.9%
a23893
 
8.7%
22632
 
8.3%
i21384
 
7.8%
Other values (24)146981
53.6%

metformin
Categorical

 Readmitted within 30 Days_Value=0Readmitted within 30 Days_Value=1
Distinct44
Distinct (%)< 0.1%< 0.1%
Missing00
Missing (%)0.0%0.0%
Memory size762.9 KiB110.6 KiB
No
69109 
Steady
16213 
Up
 
964
Down
 
494
No
10388 
Steady
1993 
Up
 
99
Down
 
80

Unique

 Readmitted within 30 Days_Value=0Readmitted within 30 Days_Value=1
Unique00 ?
Unique (%)0.0%0.0%

Sample

 Readmitted within 30 Days_Value=0Readmitted within 30 Days_Value=1
1st rowSteadyNo
2nd rowSteadyNo
3rd rowSteadySteady
4th rowNoNo
5th rowNoNo

Common Values

ValueCountFrequency (%)
No69109
79.6%
Steady16213
 
18.7%
Up964
 
1.1%
Down494
 
0.6%
ValueCountFrequency (%)
No10388
82.7%
Steady1993
 
15.9%
Up99
 
0.8%
Down80
 
0.6%

Common Values (Plot)

Readmitted within 30 Days_Value=0

2025-12-01T21:52:04.989663image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Readmitted within 30 Days_Value=1

2025-12-01T21:52:05.038728image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

num_medications
Real number (ℝ)

 Readmitted within 30 Days_Value=0Readmitted within 30 Days_Value=1
Distinct7369
Distinct (%)0.1%0.5%
Missing00
Missing (%)0.0%0.0%
Infinite00
Infinite (%)0.0%0.0%
Mean1617
 Readmitted within 30 Days_Value=0Readmitted within 30 Days_Value=1
Minimum11
Maximum7981
Zeros00
Zeros (%)0.0%0.0%
Negative00
Negative (%)0.0%0.0%
Memory size1.3 MiB196.2 KiB
2025-12-01T21:52:05.149364image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Quantile statistics

 Readmitted within 30 Days_Value=0Readmitted within 30 Days_Value=1
Minimum11
5-th percentile56
Q11011
median1516
Q32021
95-th percentile3031
Maximum7981
Range7880
Interquartile range (IQR)1010

Descriptive statistics

 Readmitted within 30 Days_Value=0Readmitted within 30 Days_Value=1
Standard deviation8.18.1
Coefficient of variation (CV)0.510.48
Kurtosis3.53.7
Mean1617
Median Absolute Deviation (MAD)55
Skewness1.31.3
Sum1.4 × 1062.1 × 105
Variance6565
MonotonicityNot monotonicNot monotonic
2025-12-01T21:52:05.300065image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
135221
 
6.0%
125171
 
6.0%
115031
 
5.8%
154946
 
5.7%
144919
 
5.7%
Other values (68)61492
70.9%
ValueCountFrequency (%)
13755
 
6.0%
15748
 
6.0%
12717
 
5.7%
16686
 
5.5%
14673
 
5.4%
Other values (64)8981
71.5%
ValueCountFrequency (%)
1247
 
0.3%
2412
 
0.5%
3805
0.9%
41254
1.4%
51796
2.1%
ValueCountFrequency (%)
113
 
0.1%
245
 
0.4%
369
0.5%
4129
1.0%
5168
1.3%
ValueCountFrequency (%)
113
 
< 0.1%
245
 
0.1%
369
0.1%
4129
0.1%
5168
0.2%
ValueCountFrequency (%)
1247
 
2.0%
2412
 
3.3%
3805
6.4%
41254
10.0%
51796
14.3%

num_procedures
Real number (ℝ)

 Readmitted within 30 Days_Value=0Readmitted within 30 Days_Value=1
Distinct77
Distinct (%)< 0.1%0.1%
Missing00
Missing (%)0.0%0.0%
Infinite00
Infinite (%)0.0%0.0%
Mean1.31.3
 Readmitted within 30 Days_Value=0Readmitted within 30 Days_Value=1
Minimum00
Maximum66
Zeros399415738
Zeros (%)46.0%45.7%
Negative00
Negative (%)0.0%0.0%
Memory size1.3 MiB196.2 KiB
2025-12-01T21:52:05.397055image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Quantile statistics

 Readmitted within 30 Days_Value=0Readmitted within 30 Days_Value=1
Minimum00
5-th percentile00
Q100
median11
Q322
95-th percentile55
Maximum66
Range66
Interquartile range (IQR)22

Descriptive statistics

 Readmitted within 30 Days_Value=0Readmitted within 30 Days_Value=1
Standard deviation1.71.6
Coefficient of variation (CV)1.31.3
Kurtosis0.841.1
Mean1.31.3
Median Absolute Deviation (MAD)11
Skewness1.31.4
Sum1.2 × 1051.6 × 104
Variance2.92.7
MonotonicityNot monotonicNot monotonic
2025-12-01T21:52:05.463517image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram with fixed size bins (bins=7)
ValueCountFrequency (%)
039941
46.0%
117482
20.1%
210805
 
12.5%
38082
 
9.3%
64268
 
4.9%
Other values (2)6202
 
7.1%
ValueCountFrequency (%)
05738
45.7%
12767
22.0%
21567
 
12.5%
31121
 
8.9%
6533
 
4.2%
Other values (2)834
 
6.6%
ValueCountFrequency (%)
039941
46.0%
117482
20.1%
210805
 
12.5%
38082
 
9.3%
43538
 
4.1%
ValueCountFrequency (%)
05738
45.7%
12767
22.0%
21567
 
12.5%
31121
 
8.9%
4511
 
4.1%
ValueCountFrequency (%)
05738
6.6%
12767
3.2%
21567
 
1.8%
31121
 
1.3%
4511
 
0.6%
ValueCountFrequency (%)
039941
318.0%
117482
139.2%
210805
 
86.0%
38082
 
64.3%
43538
 
28.2%

race
Categorical

 Readmitted within 30 Days_Value=0Readmitted within 30 Days_Value=1
Distinct66
Distinct (%)< 0.1%< 0.1%
Missing00
Missing (%)0.0%0.0%
Memory size762.9 KiB110.6 KiB
Caucasian
64716 
AfricanAmerican
16394 
Unknown
 
2015
Hispanic
 
1787
Other
 
1311
Caucasian
9504 
AfricanAmerican
2378 
Hispanic
 
230
Unknown
 
217
Other
 
160

Unique

 Readmitted within 30 Days_Value=0Readmitted within 30 Days_Value=1
Unique00 ?
Unique (%)0.0%0.0%

Sample

 Readmitted within 30 Days_Value=0Readmitted within 30 Days_Value=1
1st rowCaucasianCaucasian
2nd rowCaucasianCaucasian
3rd rowCaucasianCaucasian
4th rowCaucasianAfricanAmerican
5th rowCaucasianCaucasian

Common Values

ValueCountFrequency (%)
Caucasian64716
74.6%
AfricanAmerican16394
 
18.9%
Unknown2015
 
2.3%
Hispanic1787
 
2.1%
Other1311
 
1.5%
ValueCountFrequency (%)
Caucasian9504
75.7%
AfricanAmerican2378
 
18.9%
Hispanic230
 
1.8%
Unknown217
 
1.7%
Other160
 
1.3%

Common Values (Plot)

Readmitted within 30 Days_Value=0

2025-12-01T21:52:05.527106image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Readmitted within 30 Days_Value=1

2025-12-01T21:52:05.592626image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

specialty
['Text', 'Text']

 Readmitted within 30 Days_Value=0Readmitted within 30 Days_Value=1
Distinct1818
Distinct (%)< 0.1%0.1%
Missing00
Missing (%)0.0%0.0%
Memory size1.3 MiB196.2 KiB
2025-12-01T21:52:05.784826image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Length

 Readmitted within 30 Days_Value=0Readmitted within 30 Days_Value=1
Max length2626
Median length2222
Mean length2020
Min length1313

Characters and Unicode

 Readmitted within 30 Days_Value=0Readmitted within 30 Days_Value=1
Total characters1706954246821
Distinct characters3939
Distinct categories11 ?
Distinct scripts11 ?
Distinct blocks11 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

 Readmitted within 30 Days_Value=0Readmitted within 30 Days_Value=1
Unique00 ?
Unique (%)0.0%0.0%

Sample

 Readmitted within 30 Days_Value=0Readmitted within 30 Days_Value=1
1st rowKidney Function MonitoringElderly Diabetes Care
2nd rowMedication SafetyHypoglycemia Monitoring
3rd rowInsulin ManagementWound Healing
4th rowPost-Discharge Follow-UpInsulin Management
5th rowDiabetic Foot CareHypoglycemia Monitoring
ValueCountFrequency (%)
disease12678
 
6.5%
diabetes11704
 
6.0%
complications9539
 
4.9%
monitoring8752
 
4.5%
kidney8247
 
4.2%
care7568
 
3.9%
peripheral6977
 
3.6%
artery6977
 
3.6%
control6908
 
3.5%
glycemic6908
 
3.5%
Other values (23)110094
56.1%
ValueCountFrequency (%)
disease1790
 
6.3%
diabetes1587
 
5.6%
complications1379
 
4.9%
monitoring1300
 
4.6%
kidney1198
 
4.2%
care1021
 
3.6%
cardiac1007
 
3.6%
management1007
 
3.6%
insulin1007
 
3.6%
peripheral981
 
3.5%
Other values (23)16043
56.6%
2025-12-01T21:52:06.081936image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
i167315
 
9.8%
e161270
 
9.4%
a131239
 
7.7%
n121283
 
7.1%
o116265
 
6.8%
Other values (34)1009582
59.1%
ValueCountFrequency (%)
i24272
 
9.8%
e22973
 
9.3%
a18884
 
7.7%
n17937
 
7.3%
o16986
 
6.9%
Other values (34)145769
59.1%

Most occurring categories

ValueCountFrequency (%)
(unknown)1706954
100.0%
ValueCountFrequency (%)
(unknown)246821
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
i167315
 
9.8%
e161270
 
9.4%
a131239
 
7.7%
n121283
 
7.1%
o116265
 
6.8%
Other values (34)1009582
59.1%
ValueCountFrequency (%)
i24272
 
9.8%
e22973
 
9.3%
a18884
 
7.7%
n17937
 
7.3%
o16986
 
6.9%
Other values (34)145769
59.1%

Most occurring scripts

ValueCountFrequency (%)
(unknown)1706954
100.0%
ValueCountFrequency (%)
(unknown)246821
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
i167315
 
9.8%
e161270
 
9.4%
a131239
 
7.7%
n121283
 
7.1%
o116265
 
6.8%
Other values (34)1009582
59.1%
ValueCountFrequency (%)
i24272
 
9.8%
e22973
 
9.3%
a18884
 
7.7%
n17937
 
7.3%
o16986
 
6.9%
Other values (34)145769
59.1%

Most occurring blocks

ValueCountFrequency (%)
(unknown)1706954
100.0%
ValueCountFrequency (%)
(unknown)246821
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
i167315
 
9.8%
e161270
 
9.4%
a131239
 
7.7%
n121283
 
7.1%
o116265
 
6.8%
Other values (34)1009582
59.1%
ValueCountFrequency (%)
i24272
 
9.8%
e22973
 
9.3%
a18884
 
7.7%
n17937
 
7.3%
o16986
 
6.9%
Other values (34)145769
59.1%
 Readmitted within 30 Days_Value=0Readmitted within 30 Days_Value=1
Distinct11
Distinct (%)< 0.1%< 0.1%
Missing00
Missing (%)0.0%0.0%
Infinite00
Infinite (%)0.0%0.0%
Mean01
 Readmitted within 30 Days_Value=0Readmitted within 30 Days_Value=1
Minimum01
Maximum01
Zeros867800
Zeros (%)100.0%0.0%
Negative00
Negative (%)0.0%0.0%
Memory size1.3 MiB196.2 KiB
2025-12-01T21:52:06.143251image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Quantile statistics

 Readmitted within 30 Days_Value=0Readmitted within 30 Days_Value=1
Minimum01
5-th percentile01
Q101
median01
Q301
95-th percentile01
Maximum01
Range00
Interquartile range (IQR)00

Descriptive statistics

 Readmitted within 30 Days_Value=0Readmitted within 30 Days_Value=1
Standard deviation00
Coefficient of variation (CV)nan0
Kurtosis00
Mean01
Median Absolute Deviation (MAD)00
Skewness00
Sum01.3 × 104
Variance00
MonotonicityIncreasingIncreasing
2025-12-01T21:52:06.201703image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram with fixed size bins (bins=1)
ValueCountFrequency (%)
086780
100.0%
ValueCountFrequency (%)
112560
100.0%
ValueCountFrequency (%)
086780
100.0%
ValueCountFrequency (%)
112560
100.0%
ValueCountFrequency (%)
112560
14.5%
ValueCountFrequency (%)
086780
690.9%

Readmitted (Any)_Value
Real number (ℝ)

 Readmitted within 30 Days_Value=0Readmitted within 30 Days_Value=1
Distinct21
Distinct (%)< 0.1%< 0.1%
Missing00
Missing (%)0.0%0.0%
Infinite00
Infinite (%)0.0%0.0%
Mean0.391
 Readmitted within 30 Days_Value=0Readmitted within 30 Days_Value=1
Minimum01
Maximum11
Zeros525240
Zeros (%)60.5%0.0%
Negative00
Negative (%)0.0%0.0%
Memory size1.3 MiB196.2 KiB
2025-12-01T21:52:06.259777image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Quantile statistics

 Readmitted within 30 Days_Value=0Readmitted within 30 Days_Value=1
Minimum01
5-th percentile01
Q101
median01
Q311
95-th percentile11
Maximum11
Range10
Interquartile range (IQR)10

Descriptive statistics

 Readmitted within 30 Days_Value=0Readmitted within 30 Days_Value=1
Standard deviation0.490
Coefficient of variation (CV)1.20
Kurtosis-1.80
Mean0.391
Median Absolute Deviation (MAD)00
Skewness0.430
Sum3.4 × 1041.3 × 104
Variance0.240
MonotonicityNot monotonicIncreasing
2025-12-01T21:52:06.317453image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram with fixed size bins (bins=2)
ValueCountFrequency (%)
052524
60.5%
134256
39.5%
ValueCountFrequency (%)
112560
100.0%
ValueCountFrequency (%)
052524
60.5%
134256
39.5%
ValueCountFrequency (%)
112560
100.0%
ValueCountFrequency (%)
112560
14.5%
ValueCountFrequency (%)
052524
418.2%
134256
272.7%
 Readmitted within 30 Days_Value=0Readmitted within 30 Days_Value=1
Distinct22
Distinct (%)< 0.1%< 0.1%
Missing00
Missing (%)0.0%0.0%
Infinite00
Infinite (%)0.0%0.0%
Mean0.140.18
 Readmitted within 30 Days_Value=0Readmitted within 30 Days_Value=1
Minimum00
Maximum11
Zeros7429610333
Zeros (%)85.6%82.3%
Negative00
Negative (%)0.0%0.0%
Memory size1.3 MiB196.2 KiB
2025-12-01T21:52:06.378407image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Quantile statistics

 Readmitted within 30 Days_Value=0Readmitted within 30 Days_Value=1
Minimum00
5-th percentile00
Q100
median00
Q300
95-th percentile11
Maximum11
Range11
Interquartile range (IQR)00

Descriptive statistics

 Readmitted within 30 Days_Value=0Readmitted within 30 Days_Value=1
Standard deviation0.350.38
Coefficient of variation (CV)2.42.2
Kurtosis2.10.86
Mean0.140.18
Median Absolute Deviation (MAD)00
Skewness21.7
Sum1.2 × 1042.2 × 103
Variance0.120.15
MonotonicityDecreasingDecreasing
2025-12-01T21:52:06.442468image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram with fixed size bins (bins=2)
ValueCountFrequency (%)
074296
85.6%
112484
 
14.4%
ValueCountFrequency (%)
010333
82.3%
12227
 
17.7%
ValueCountFrequency (%)
074296
85.6%
112484
 
14.4%
ValueCountFrequency (%)
010333
82.3%
12227
 
17.7%
ValueCountFrequency (%)
010333
11.9%
12227
 
2.6%
ValueCountFrequency (%)
074296
591.5%
112484
 
99.4%
 Readmitted within 30 Days_Value=0Readmitted within 30 Days_Value=1
Distinct1414
Distinct (%)< 0.1%0.1%
Missing00
Missing (%)0.0%0.0%
Infinite00
Infinite (%)0.0%0.0%
Mean4.34.7
 Readmitted within 30 Days_Value=0Readmitted within 30 Days_Value=1
Minimum11
Maximum1414
Zeros00
Zeros (%)0.0%0.0%
Negative00
Negative (%)0.0%0.0%
Memory size1.3 MiB196.2 KiB
2025-12-01T21:52:06.518167image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Quantile statistics

 Readmitted within 30 Days_Value=0Readmitted within 30 Days_Value=1
Minimum11
5-th percentile11
Q122
median44
Q366
95-th percentile1111
Maximum1414
Range1313
Interquartile range (IQR)44

Descriptive statistics

 Readmitted within 30 Days_Value=0Readmitted within 30 Days_Value=1
Standard deviation33
Coefficient of variation (CV)0.680.64
Kurtosis0.960.49
Mean4.34.7
Median Absolute Deviation (MAD)22
Skewness1.20.99
Sum3.8 × 1056 × 104
Variance8.79.1
MonotonicityDecreasingDecreasing
2025-12-01T21:52:06.602123image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram with fixed size bins (bins=14)
ValueCountFrequency (%)
315357
17.7%
214993
17.3%
112484
14.4%
411850
13.7%
58433
 
9.7%
Other values (9)23663
27.3%
ValueCountFrequency (%)
32075
16.5%
21898
15.1%
41834
14.6%
11338
 
10.7%
51316
 
10.5%
Other values (9)4099
32.6%
ValueCountFrequency (%)
112484
14.4%
214993
17.3%
315357
17.7%
411850
13.7%
58433
9.7%
ValueCountFrequency (%)
11338
10.7%
21898
15.1%
32075
16.5%
41834
14.6%
51316
10.5%
ValueCountFrequency (%)
11338
1.5%
21898
2.2%
32075
2.4%
41834
2.1%
51316
1.5%
ValueCountFrequency (%)
112484
99.4%
214993
119.4%
315357
122.3%
411850
94.3%
58433
67.1%
 Readmitted within 30 Days_Value=0Readmitted within 30 Days_Value=1
Distinct1414
Distinct (%)< 0.1%0.1%
Missing00
Missing (%)0.0%0.0%
Infinite00
Infinite (%)0.0%0.0%
Mean4.34.7
 Readmitted within 30 Days_Value=0Readmitted within 30 Days_Value=1
Minimum11
Maximum1414
Zeros00
Zeros (%)0.0%0.0%
Negative00
Negative (%)0.0%0.0%
Memory size1.3 MiB196.2 KiB
2025-12-01T21:52:06.683996image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Quantile statistics

 Readmitted within 30 Days_Value=0Readmitted within 30 Days_Value=1
Minimum11
5-th percentile11
Q122
median44
Q366
95-th percentile1111
Maximum1414
Range1313
Interquartile range (IQR)44

Descriptive statistics

 Readmitted within 30 Days_Value=0Readmitted within 30 Days_Value=1
Standard deviation33
Coefficient of variation (CV)0.680.64
Kurtosis0.960.49
Mean4.34.7
Median Absolute Deviation (MAD)22
Skewness1.20.99
Sum3.8 × 1056 × 104
Variance8.79.1
MonotonicityDecreasingDecreasing
2025-12-01T21:52:06.769064image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram with fixed size bins (bins=14)
ValueCountFrequency (%)
315357
17.7%
214993
17.3%
112484
14.4%
411850
13.7%
58433
 
9.7%
Other values (9)23663
27.3%
ValueCountFrequency (%)
32075
16.5%
21898
15.1%
41834
14.6%
11338
 
10.7%
51316
 
10.5%
Other values (9)4099
32.6%
ValueCountFrequency (%)
112484
14.4%
214993
17.3%
315357
17.7%
411850
13.7%
58433
9.7%
ValueCountFrequency (%)
11338
10.7%
21898
15.1%
32075
16.5%
41834
14.6%
51316
10.5%
ValueCountFrequency (%)
11338
1.5%
21898
2.2%
32075
2.4%
41834
2.1%
51316
1.5%
ValueCountFrequency (%)
112484
99.4%
214993
119.4%
315357
122.3%
411850
94.3%
58433
67.1%

Taking Metformin_Value
Real number (ℝ)

 Readmitted within 30 Days_Value=0Readmitted within 30 Days_Value=1
Distinct33
Distinct (%)< 0.1%< 0.1%
Missing00
Missing (%)0.0%0.0%
Infinite00
Infinite (%)0.0%0.0%
Mean0.210.18
 Readmitted within 30 Days_Value=0Readmitted within 30 Days_Value=1
Minimum00
Maximum22
Zeros6855110307
Zeros (%)79.0%82.1%
Negative00
Negative (%)0.0%0.0%
Memory size1.3 MiB196.2 KiB
2025-12-01T21:52:06.838014image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Quantile statistics

 Readmitted within 30 Days_Value=0Readmitted within 30 Days_Value=1
Minimum00
5-th percentile00
Q100
median00
Q300
95-th percentile11
Maximum22
Range22
Interquartile range (IQR)00

Descriptive statistics

 Readmitted within 30 Days_Value=0Readmitted within 30 Days_Value=1
Standard deviation0.410.39
Coefficient of variation (CV)1.92.1
Kurtosis0.170.98
Mean0.210.18
Median Absolute Deviation (MAD)00
Skewness1.41.7
Sum1.8 × 1042.3 × 103
Variance0.170.15
MonotonicityNot monotonicNot monotonic
2025-12-01T21:52:06.907255image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram with fixed size bins (bins=3)
ValueCountFrequency (%)
068551
79.0%
118177
 
20.9%
252
 
0.1%
ValueCountFrequency (%)
010307
82.1%
12246
 
17.9%
27
 
0.1%
ValueCountFrequency (%)
068551
79.0%
118177
 
20.9%
252
 
0.1%
ValueCountFrequency (%)
010307
82.1%
12246
 
17.9%
27
 
0.1%
ValueCountFrequency (%)
010307
11.9%
12246
 
2.6%
27
 
< 0.1%
ValueCountFrequency (%)
068551
545.8%
118177
 
144.7%
252
 
0.4%

Age
Categorical

 Readmitted within 30 Days_Value=0Readmitted within 30 Days_Value=1
Distinct55
Distinct (%)< 0.1%< 0.1%
Missing00
Missing (%)0.0%0.0%
Memory size762.9 KiB110.6 KiB
70+
38369 
[50-70)
34453 
[20-50)
13160 
[10-20)
 
642
[0-10)
 
156
70+
5983 
[50-70)
4665 
[20-50)
1860 
[10-20)
 
48
[0-10)
 
4

Unique

 Readmitted within 30 Days_Value=0Readmitted within 30 Days_Value=1
Unique00 ?
Unique (%)0.0%0.0%

Sample

 Readmitted within 30 Days_Value=0Readmitted within 30 Days_Value=1
1st row70+70+
2nd row[20-50)70+
3rd row70+70+
4th row70+[50-70)
5th row70+70+

Common Values

ValueCountFrequency (%)
70+38369
44.2%
[50-70)34453
39.7%
[20-50)13160
 
15.2%
[10-20)642
 
0.7%
[0-10)156
 
0.2%
ValueCountFrequency (%)
70+5983
47.6%
[50-70)4665
37.1%
[20-50)1860
 
14.8%
[10-20)48
 
0.4%
[0-10)4
 
< 0.1%

Common Values (Plot)

Readmitted within 30 Days_Value=0

2025-12-01T21:52:06.974339image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Readmitted within 30 Days_Value=1

2025-12-01T21:52:07.034544image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Race
Categorical

 Readmitted within 30 Days_Value=0Readmitted within 30 Days_Value=1
Distinct66
Distinct (%)< 0.1%< 0.1%
Missing00
Missing (%)0.0%0.0%
Memory size762.9 KiB110.6 KiB
Caucasian
64716 
AfricanAmerican
16394 
Unknown
 
2015
Hispanic
 
1787
Other
 
1311
Caucasian
9504 
AfricanAmerican
2378 
Hispanic
 
230
Unknown
 
217
Other
 
160

Unique

 Readmitted within 30 Days_Value=0Readmitted within 30 Days_Value=1
Unique00 ?
Unique (%)0.0%0.0%

Sample

 Readmitted within 30 Days_Value=0Readmitted within 30 Days_Value=1
1st rowCaucasianCaucasian
2nd rowCaucasianCaucasian
3rd rowCaucasianCaucasian
4th rowCaucasianAfricanAmerican
5th rowCaucasianCaucasian

Common Values

ValueCountFrequency (%)
Caucasian64716
74.6%
AfricanAmerican16394
 
18.9%
Unknown2015
 
2.3%
Hispanic1787
 
2.1%
Other1311
 
1.5%
ValueCountFrequency (%)
Caucasian9504
75.7%
AfricanAmerican2378
 
18.9%
Hispanic230
 
1.8%
Unknown217
 
1.7%
Other160
 
1.3%

Common Values (Plot)

Readmitted within 30 Days_Value=0

2025-12-01T21:52:07.099344image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Readmitted within 30 Days_Value=1

2025-12-01T21:52:07.165405image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Gender
Categorical

 Readmitted within 30 Days_Value=0Readmitted within 30 Days_Value=1
Distinct22
Distinct (%)< 0.1%< 0.1%
Missing00
Missing (%)0.0%0.0%
Memory size762.8 KiB110.5 KiB
Female
46603 
Male
40177 
Female
6851 
Male
5709 

Unique

 Readmitted within 30 Days_Value=0Readmitted within 30 Days_Value=1
Unique00 ?
Unique (%)0.0%0.0%

Sample

 Readmitted within 30 Days_Value=0Readmitted within 30 Days_Value=1
1st rowFemaleMale
2nd rowMaleFemale
3rd rowFemaleMale
4th rowFemaleFemale
5th rowFemaleMale

Common Values

ValueCountFrequency (%)
Female46603
53.7%
Male40177
46.3%
ValueCountFrequency (%)
Female6851
54.5%
Male5709
45.5%

Common Values (Plot)

Readmitted within 30 Days_Value=0

2025-12-01T21:52:07.220724image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Readmitted within 30 Days_Value=1

2025-12-01T21:52:07.257518image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

A1C
Categorical

 Readmitted within 30 Days_Value=0Readmitted within 30 Days_Value=1
Distinct44
Distinct (%)< 0.1%< 0.1%
Missing00
Missing (%)0.0%0.0%
Memory size762.9 KiB110.6 KiB
None
71835 
>8
7216 
Norm
 
4390
>7
 
3339
None
10671 
>8
 
921
Norm
 
532
>7
 
436

Unique

 Readmitted within 30 Days_Value=0Readmitted within 30 Days_Value=1
Unique00 ?
Unique (%)0.0%0.0%

Sample

 Readmitted within 30 Days_Value=0Readmitted within 30 Days_Value=1
1st rowNoneNorm
2nd rowNoneNone
3rd rowNorm>8
4th row>7None
5th rowNoneNone

Common Values

ValueCountFrequency (%)
None71835
82.8%
>87216
 
8.3%
Norm4390
 
5.1%
>73339
 
3.8%
ValueCountFrequency (%)
None10671
85.0%
>8921
 
7.3%
Norm532
 
4.2%
>7436
 
3.5%

Common Values (Plot)

Readmitted within 30 Days_Value=0

2025-12-01T21:52:07.299104image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Readmitted within 30 Days_Value=1

2025-12-01T21:52:07.345862image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Taking Insulin
Categorical

 Readmitted within 30 Days_Value=0Readmitted within 30 Days_Value=1
Distinct44
Distinct (%)< 0.1%< 0.1%
Missing00
Missing (%)0.0%0.0%
Memory size762.9 KiB110.6 KiB
No
41084 
Steady
26289 
Down
10049 
Up
9358 
No
5292 
Steady
3780 
Down
1859 
Up
1629 

Unique

 Readmitted within 30 Days_Value=0Readmitted within 30 Days_Value=1
Unique00 ?
Unique (%)0.0%0.0%

Sample

 Readmitted within 30 Days_Value=0Readmitted within 30 Days_Value=1
1st rowDownUp
2nd rowNoSteady
3rd rowNoDown
4th rowUpSteady
5th rowDownSteady

Common Values

ValueCountFrequency (%)
No41084
47.3%
Steady26289
30.3%
Down10049
 
11.6%
Up9358
 
10.8%
ValueCountFrequency (%)
No5292
42.1%
Steady3780
30.1%
Down1859
 
14.8%
Up1629
 
13.0%

Common Values (Plot)

Readmitted within 30 Days_Value=0

2025-12-01T21:52:07.644876image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Readmitted within 30 Days_Value=1

2025-12-01T21:52:07.701642image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Taking Metformin
Categorical

 Readmitted within 30 Days_Value=0Readmitted within 30 Days_Value=1
Distinct44
Distinct (%)< 0.1%< 0.1%
Missing00
Missing (%)0.0%0.0%
Memory size762.9 KiB110.6 KiB
No
69109 
Steady
16213 
Up
 
964
Down
 
494
No
10388 
Steady
1993 
Up
 
99
Down
 
80

Unique

 Readmitted within 30 Days_Value=0Readmitted within 30 Days_Value=1
Unique00 ?
Unique (%)0.0%0.0%

Sample

 Readmitted within 30 Days_Value=0Readmitted within 30 Days_Value=1
1st rowSteadyNo
2nd rowSteadyNo
3rd rowSteadySteady
4th rowNoNo
5th rowNoNo

Common Values

ValueCountFrequency (%)
No69109
79.6%
Steady16213
 
18.7%
Up964
 
1.1%
Down494
 
0.6%
ValueCountFrequency (%)
No10388
82.7%
Steady1993
 
15.9%
Up99
 
0.8%
Down80
 
0.6%

Common Values (Plot)

Readmitted within 30 Days_Value=0

2025-12-01T21:52:07.756876image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Readmitted within 30 Days_Value=1

2025-12-01T21:52:07.807986image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Location
Categorical

 Readmitted within 30 Days_Value=0Readmitted within 30 Days_Value=1
Distinct55
Distinct (%)< 0.1%< 0.1%
Missing00
Missing (%)0.0%0.0%
Memory size762.9 KiB110.6 KiB
Urban Medical Center
26012 
Regional Health System
21588 
Community Hospital
17569 
Specialty Diabetes Institute
12901 
Veterans Medical Facility
8710 
Urban Medical Center
3739 
Regional Health System
3165 
Community Hospital
2488 
Specialty Diabetes Institute
1907 
Veterans Medical Facility
1261 

Unique

 Readmitted within 30 Days_Value=0Readmitted within 30 Days_Value=1
Unique00 ?
Unique (%)0.0%0.0%

Sample

 Readmitted within 30 Days_Value=0Readmitted within 30 Days_Value=1
1st rowUrban Medical CenterUrban Medical Center
2nd rowRegional Health SystemSpecialty Diabetes Institute
3rd rowSpecialty Diabetes InstituteRegional Health System
4th rowCommunity HospitalRegional Health System
5th rowRegional Health SystemSpecialty Diabetes Institute

Common Values

ValueCountFrequency (%)
Urban Medical Center26012
30.0%
Regional Health System21588
24.9%
Community Hospital17569
20.2%
Specialty Diabetes Institute12901
14.9%
Veterans Medical Facility8710
 
10.0%
ValueCountFrequency (%)
Urban Medical Center3739
29.8%
Regional Health System3165
25.2%
Community Hospital2488
19.8%
Specialty Diabetes Institute1907
15.2%
Veterans Medical Facility1261
 
10.0%

Common Values (Plot)

Readmitted within 30 Days_Value=0

2025-12-01T21:52:07.865881image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Readmitted within 30 Days_Value=1

2025-12-01T21:52:07.941567image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Department
Categorical

 Readmitted within 30 Days_Value=0Readmitted within 30 Days_Value=1
Distinct99
Distinct (%)< 0.1%0.1%
Missing00
Missing (%)0.0%0.0%
Memory size763.1 KiB110.8 KiB
Endocrinology
20601 
Cardiology
14006 
Pharmacy
12480 
Internal Medicine
11478 
Geriatrics
8154 
Other values (4)
20061 
Endocrinology
2965 
Cardiology
1997 
Pharmacy
1839 
Internal Medicine
1651 
Geriatrics
1163 
Other values (4)
2945 

Unique

 Readmitted within 30 Days_Value=0Readmitted within 30 Days_Value=1
Unique00 ?
Unique (%)0.0%0.0%

Sample

 Readmitted within 30 Days_Value=0Readmitted within 30 Days_Value=1
1st rowNephrologyGeriatrics
2nd rowPharmacyPharmacy
3rd rowEndocrinologyPodiatry
4th rowInternal MedicineEndocrinology
5th rowPodiatryPharmacy

Common Values

ValueCountFrequency (%)
Endocrinology20601
23.7%
Cardiology14006
16.1%
Pharmacy12480
14.4%
Internal Medicine11478
13.2%
Geriatrics8154
 
9.4%
Other values (4)20061
23.1%
ValueCountFrequency (%)
Endocrinology2965
23.6%
Cardiology1997
15.9%
Pharmacy1839
14.6%
Internal Medicine1651
13.1%
Geriatrics1163
 
9.3%
Other values (4)2945
23.4%

Common Values (Plot)

Readmitted within 30 Days_Value=0

2025-12-01T21:52:08.031952image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Readmitted within 30 Days_Value=1

2025-12-01T21:52:08.135602image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Specialty
Categorical

 Readmitted within 30 Days_Value=0Readmitted within 30 Days_Value=1
Distinct1818
Distinct (%)< 0.1%0.1%
Missing00
Missing (%)0.0%0.0%
Memory size763.4 KiB111.1 KiB
Peripheral Artery Disease
6977 
Glycemic Control
6908 
Cardiac Complications
6898 
Diabetes Education
6836 
Insulin Management
6683 
Other values (13)
52478 
Cardiac Complications
1007 
Insulin Management
1007 
Peripheral Artery Disease
981 
Glycemic Control
978 
Wound Healing
974 
Other values (13)
7613 

Unique

 Readmitted within 30 Days_Value=0Readmitted within 30 Days_Value=1
Unique00 ?
Unique (%)0.0%0.0%

Sample

 Readmitted within 30 Days_Value=0Readmitted within 30 Days_Value=1
1st rowKidney Function MonitoringElderly Diabetes Care
2nd rowMedication SafetyHypoglycemia Monitoring
3rd rowInsulin ManagementWound Healing
4th rowPost-Discharge Follow-UpInsulin Management
5th rowDiabetic Foot CareHypoglycemia Monitoring

Common Values

ValueCountFrequency (%)
Peripheral Artery Disease6977
 
8.0%
Glycemic Control6908
 
8.0%
Cardiac Complications6898
 
7.9%
Diabetes Education6836
 
7.9%
Insulin Management6683
 
7.7%
Other values (13)52478
60.5%
ValueCountFrequency (%)
Cardiac Complications1007
 
8.0%
Insulin Management1007
 
8.0%
Peripheral Artery Disease981
 
7.8%
Glycemic Control978
 
7.8%
Wound Healing974
 
7.8%
Other values (13)7613
60.6%

Common Values (Plot)

Readmitted within 30 Days_Value=0


Number of variable categories passes threshold (config.plot.cat_freq.max_unique)

Readmitted within 30 Days_Value=1


Number of variable categories passes threshold (config.plot.cat_freq.max_unique)