Overview

Brought to you by YData

Dataset statistics

Number of variables30
Number of observations99340
Missing cells151613
Missing cells (%)5.1%
Total size in memory14.1 MiB
Average record size in memory149.0 B

Variable types

Categorical13
Text4
Numeric13

Alerts

A1Cresult is highly imbalanced (54.4%)Imbalance
admission_type_id is highly imbalanced (50.7%)Imbalance
metformin is highly imbalanced (59.1%)Imbalance
race is highly imbalanced (55.8%)Imbalance
Race is highly imbalanced (55.8%)Imbalance
A1C is highly imbalanced (54.4%)Imbalance
Taking Metformin is highly imbalanced (59.1%)Imbalance
CaseManager_Feedback_30day_30_80_Threshold_Clarity has 22410 (22.6%) missing valuesMissing
CaseManager_Feedback_30day_30_80_Threshold_Effectiveness has 37254 (37.5%) missing valuesMissing
CaseManager_Feedback_30day_30_80_Threshold_Impact has 37559 (37.8%) missing valuesMissing
PatientSatisfaction_ReadmissionFollowup has 54390 (54.8%) missing valuesMissing
num_procedures has 45679 (46.0%) zerosZeros
Readmitted within 30 Days_Value has 86780 (87.4%) zerosZeros
Readmitted (Any)_Value has 52524 (52.9%) zerosZeros
Long Hospital Stay (>7 days)_Value has 84629 (85.2%) zerosZeros
Taking Metformin_Value has 78858 (79.4%) zerosZeros

Reproduction

Analysis started2025-09-25 18:21:34.024109
Analysis finished2025-09-25 18:21:34.756567
Duration0.73 seconds
Software versionydata-profiling vv4.17.0
Download configurationconfig.json

Variables

A1Cresult
Categorical

Imbalance 

Distinct4
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size97.3 KiB
None
82506 
>8
 
8137
Norm
 
4922
>7
 
3775

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowNone
2nd rowNorm
3rd rowNone
4th rowNorm
5th row>7

Common Values

ValueCountFrequency (%)
None82506
83.1%
>88137
 
8.2%
Norm4922
 
5.0%
>73775
 
3.8%

Common Values (Plot)

2025-09-25T18:21:34.796063image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Distinct5
Distinct (%)< 0.1%
Missing22410
Missing (%)22.6%
Memory size776.2 KiB
2025-09-25T18:21:35.013743image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Length

Max length9
Median length7
Mean length6.5
Min length4

Characters and Unicode

Total characters500286
Distinct characters18
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowVery Poor
2nd rowGood
3rd rowNeutral
4th rowPoor
5th rowNeutral
ValueCountFrequency (%)
good24952
29.6%
excellent22417
26.6%
poor14959
17.8%
neutral14602
17.3%
very7335
 
8.7%
2025-09-25T18:21:35.181927image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
o79822
 
16.0%
e66771
 
13.3%
l59436
 
11.9%
t37019
 
7.4%
r36896
 
7.4%
Other values (13)220342
44.0%

Most occurring categories

ValueCountFrequency (%)
(unknown)500286
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
o79822
 
16.0%
e66771
 
13.3%
l59436
 
11.9%
t37019
 
7.4%
r36896
 
7.4%
Other values (13)220342
44.0%

Most occurring scripts

ValueCountFrequency (%)
(unknown)500286
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
o79822
 
16.0%
e66771
 
13.3%
l59436
 
11.9%
t37019
 
7.4%
r36896
 
7.4%
Other values (13)220342
44.0%

Most occurring blocks

ValueCountFrequency (%)
(unknown)500286
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
o79822
 
16.0%
e66771
 
13.3%
l59436
 
11.9%
t37019
 
7.4%
r36896
 
7.4%
Other values (13)220342
44.0%
Distinct5
Distinct (%)< 0.1%
Missing37254
Missing (%)37.5%
Memory size776.2 KiB
2025-09-25T18:21:35.260264image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Length

Max length9
Median length7
Mean length6.5
Min length4

Characters and Unicode

Total characters404373
Distinct characters18
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowGood
2nd rowGood
3rd rowExcellent
4th rowNeutral
5th rowExcellent
ValueCountFrequency (%)
good19807
29.1%
excellent17831
26.2%
neutral12278
18.0%
poor12170
17.9%
very6008
 
8.8%
2025-09-25T18:21:35.412772image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
o63954
 
15.8%
e53948
 
13.3%
l47940
 
11.9%
r30456
 
7.5%
t30109
 
7.4%
Other values (13)177966
44.0%

Most occurring categories

ValueCountFrequency (%)
(unknown)404373
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
o63954
 
15.8%
e53948
 
13.3%
l47940
 
11.9%
r30456
 
7.5%
t30109
 
7.4%
Other values (13)177966
44.0%

Most occurring scripts

ValueCountFrequency (%)
(unknown)404373
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
o63954
 
15.8%
e53948
 
13.3%
l47940
 
11.9%
r30456
 
7.5%
t30109
 
7.4%
Other values (13)177966
44.0%

Most occurring blocks

ValueCountFrequency (%)
(unknown)404373
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
o63954
 
15.8%
e53948
 
13.3%
l47940
 
11.9%
r30456
 
7.5%
t30109
 
7.4%
Other values (13)177966
44.0%
Distinct5
Distinct (%)< 0.1%
Missing37559
Missing (%)37.8%
Memory size776.2 KiB
2025-09-25T18:21:35.492690image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Length

Max length9
Median length7
Mean length6.5
Min length4

Characters and Unicode

Total characters402222
Distinct characters18
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowExcellent
2nd rowVery Poor
3rd rowNeutral
4th rowGood
5th rowGood
ValueCountFrequency (%)
good19815
29.2%
excellent17780
26.2%
poor12145
17.9%
neutral12041
17.8%
very6015
 
8.9%
2025-09-25T18:21:35.646473image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
o63920
 
15.9%
e53616
 
13.3%
l47601
 
11.8%
r30201
 
7.5%
t29821
 
7.4%
Other values (13)177063
44.0%

Most occurring categories

ValueCountFrequency (%)
(unknown)402222
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
o63920
 
15.9%
e53616
 
13.3%
l47601
 
11.8%
r30201
 
7.5%
t29821
 
7.4%
Other values (13)177063
44.0%

Most occurring scripts

ValueCountFrequency (%)
(unknown)402222
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
o63920
 
15.9%
e53616
 
13.3%
l47601
 
11.8%
r30201
 
7.5%
t29821
 
7.4%
Other values (13)177063
44.0%

Most occurring blocks

ValueCountFrequency (%)
(unknown)402222
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
o63920
 
15.9%
e53616
 
13.3%
l47601
 
11.8%
r30201
 
7.5%
t29821
 
7.4%
Other values (13)177063
44.0%

ExpectedHospitalStay
Real number (ℝ)

Distinct99339
Distinct (%)> 99.9%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean4.4
Minimum0.57
Maximum13
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size776.2 KiB
2025-09-25T18:21:35.726127image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Quantile statistics

Minimum0.57
5-th percentile1.9
Q12.9
median4
Q35.5
95-th percentile8.3
Maximum13
Range13
Interquartile range (IQR)2.5

Descriptive statistics

Standard deviation1.9
Coefficient of variation (CV)0.44
Kurtosis0.55
Mean4.4
Median Absolute Deviation (MAD)1.2
Skewness0.92
Sum4.4 × 105
Variance3.8
MonotonicityNot monotonic
2025-09-25T18:21:35.830488image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1.6864070992
 
< 0.1%
2.1080858381
 
< 0.1%
5.2719131031
 
< 0.1%
2.2934864541
 
< 0.1%
2.7294671141
 
< 0.1%
Other values (99334)99334
> 99.9%
ValueCountFrequency (%)
0.56656170941
< 0.1%
0.6388334111
< 0.1%
0.65240521991
< 0.1%
0.70743187271
< 0.1%
0.70828869941
< 0.1%
ValueCountFrequency (%)
13.169136311
< 0.1%
13.163944971
< 0.1%
12.644076771
< 0.1%
12.59147951
< 0.1%
12.454262851
< 0.1%
Distinct5
Distinct (%)< 0.1%
Missing54390
Missing (%)54.8%
Memory size776.2 KiB
2025-09-25T18:21:35.934265image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Length

Max length9
Median length7
Mean length6.5
Min length4

Characters and Unicode

Total characters292239
Distinct characters18
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowNeutral
2nd rowGood
3rd rowExcellent
4th rowGood
5th rowVery Poor
ValueCountFrequency (%)
poor11707
23.2%
good11663
23.1%
neutral11328
22.5%
excellent10252
20.3%
very5439
10.8%
2025-09-25T18:21:36.098759image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
o46740
 
16.0%
e37271
 
12.8%
l31832
 
10.9%
r28474
 
9.7%
t21580
 
7.4%
Other values (13)126342
43.2%

Most occurring categories

ValueCountFrequency (%)
(unknown)292239
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
o46740
 
16.0%
e37271
 
12.8%
l31832
 
10.9%
r28474
 
9.7%
t21580
 
7.4%
Other values (13)126342
43.2%

Most occurring scripts

ValueCountFrequency (%)
(unknown)292239
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
o46740
 
16.0%
e37271
 
12.8%
l31832
 
10.9%
r28474
 
9.7%
t21580
 
7.4%
Other values (13)126342
43.2%

Most occurring blocks

ValueCountFrequency (%)
(unknown)292239
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
o46740
 
16.0%
e37271
 
12.8%
l31832
 
10.9%
r28474
 
9.7%
t21580
 
7.4%
Other values (13)126342
43.2%

Risk30DayReadmission
Real number (ℝ)

Distinct99280
Distinct (%)99.9%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.11
Minimum0.016
Maximum0.82
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size776.2 KiB
2025-09-25T18:21:36.178493image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Quantile statistics

Minimum0.016
5-th percentile0.041
Q10.066
median0.095
Q30.14
95-th percentile0.25
Maximum0.82
Range0.81
Interquartile range (IQR)0.075

Descriptive statistics

Standard deviation0.071
Coefficient of variation (CV)0.62
Kurtosis7.4
Mean0.11
Median Absolute Deviation (MAD)0.034
Skewness2.1
Sum1.1 × 104
Variance0.0051
MonotonicityNot monotonic
2025-09-25T18:21:36.285722image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.023527511516
 
< 0.1%
0.022526796754
 
< 0.1%
0.021030478783
 
< 0.1%
0.079530609273
 
< 0.1%
0.021966215923
 
< 0.1%
Other values (99275)99321
> 99.9%
ValueCountFrequency (%)
0.015524674631
< 0.1%
0.015712900721
< 0.1%
0.016354168761
< 0.1%
0.01723173911
< 0.1%
0.017359795611
< 0.1%
ValueCountFrequency (%)
0.82356830451
< 0.1%
0.8081312911
< 0.1%
0.78475003351
< 0.1%
0.76632679051
< 0.1%
0.75872273241
< 0.1%
Distinct78
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean11
Minimum1
Maximum82
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size776.2 KiB
2025-09-25T18:21:36.389621image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile4
Q16
median9
Q314
95-th percentile24
Maximum82
Range81
Interquartile range (IQR)8

Descriptive statistics

Standard deviation7.1
Coefficient of variation (CV)0.65
Kurtosis7.3
Mean11
Median Absolute Deviation (MAD)3
Skewness2.1
Sum1.1 × 106
Variance51
MonotonicityNot monotonic
2025-09-25T18:21:36.495343image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
69593
 
9.7%
79154
 
9.2%
88444
 
8.5%
58440
 
8.5%
97301
 
7.3%
Other values (73)56408
56.8%
ValueCountFrequency (%)
147
 
< 0.1%
21047
 
1.1%
33257
 
3.3%
46252
6.3%
58440
8.5%
ValueCountFrequency (%)
821
 
< 0.1%
801
 
< 0.1%
781
 
< 0.1%
761
 
< 0.1%
753
< 0.1%

RiskAnyReadmission
Real number (ℝ)

Distinct99336
Distinct (%)> 99.9%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.47
Minimum0.043
Maximum0.97
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size776.2 KiB
2025-09-25T18:21:36.601028image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Quantile statistics

Minimum0.043
5-th percentile0.18
Q10.32
median0.47
Q30.62
95-th percentile0.78
Maximum0.97
Range0.93
Interquartile range (IQR)0.29

Descriptive statistics

Standard deviation0.19
Coefficient of variation (CV)0.4
Kurtosis-0.81
Mean0.47
Median Absolute Deviation (MAD)0.15
Skewness0.12
Sum4.7 × 104
Variance0.035
MonotonicityNot monotonic
2025-09-25T18:21:36.704303image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.68854469232
 
< 0.1%
0.14791992912
 
< 0.1%
0.54726442772
 
< 0.1%
0.63613439632
 
< 0.1%
0.24101094351
 
< 0.1%
Other values (99331)99331
> 99.9%
ValueCountFrequency (%)
0.042914160721
< 0.1%
0.047188465631
< 0.1%
0.050530594961
< 0.1%
0.053423416331
< 0.1%
0.054997311731
< 0.1%
ValueCountFrequency (%)
0.97426921111
< 0.1%
0.97307035261
< 0.1%
0.97267080881
< 0.1%
0.97257972741
< 0.1%
0.96981183831
< 0.1%

RiskLongStay
Real number (ℝ)

Distinct99339
Distinct (%)> 99.9%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.15
Minimum0.0025
Maximum0.95
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size776.2 KiB
2025-09-25T18:21:36.805489image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Quantile statistics

Minimum0.0025
5-th percentile0.0094
Q10.025
median0.066
Q30.19
95-th percentile0.6
Maximum0.95
Range0.95
Interquartile range (IQR)0.16

Descriptive statistics

Standard deviation0.19
Coefficient of variation (CV)1.3
Kurtosis3.1
Mean0.15
Median Absolute Deviation (MAD)0.05
Skewness1.9
Sum1.5 × 104
Variance0.035
MonotonicityNot monotonic
2025-09-25T18:21:36.905653image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.034026068282
 
< 0.1%
0.0099102894181
 
< 0.1%
0.19228415831
 
< 0.1%
0.013370717931
 
< 0.1%
0.011583994461
 
< 0.1%
Other values (99334)99334
> 99.9%
ValueCountFrequency (%)
0.0025491973361
< 0.1%
0.0025640219011
< 0.1%
0.0025696161571
< 0.1%
0.0027625701921
< 0.1%
0.002853768831
< 0.1%
ValueCountFrequency (%)
0.95465561411
< 0.1%
0.95280381731
< 0.1%
0.95260777731
< 0.1%
0.95128027111
< 0.1%
0.94983467951
< 0.1%

admission_type_id
Categorical

Imbalance 

Distinct5
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size97.3 KiB
Emergency
70501 
Elective
18667 
Unknown
10144 
Trauma Center
 
18
New Born
 
10

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowElective
2nd rowEmergency
3rd rowUnknown
4th rowUnknown
5th rowUnknown

Common Values

ValueCountFrequency (%)
Emergency70501
71.0%
Elective18667
 
18.8%
Unknown10144
 
10.2%
Trauma Center18
 
< 0.1%
New Born10
 
< 0.1%

Common Values (Plot)

2025-09-25T18:21:36.977348image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

age
Categorical

Distinct5
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size97.3 KiB
70+
44352 
[50-70)
39118 
[20-50)
15020 
[10-20)
 
690
[0-10)
 
160

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row70+
2nd row70+
3rd row[20-50)
4th row70+
5th row70+

Common Values

ValueCountFrequency (%)
70+44352
44.6%
[50-70)39118
39.4%
[20-50)15020
 
15.1%
[10-20)690
 
0.7%
[0-10)160
 
0.2%

Common Values (Plot)

2025-09-25T18:21:37.040895image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

gender
Categorical

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size97.3 KiB
Female
53454 
Male
45886 

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowFemale
2nd rowMale
3rd rowMale
4th rowFemale
5th rowFemale

Common Values

ValueCountFrequency (%)
Female53454
53.8%
Male45886
46.2%

Common Values (Plot)

2025-09-25T18:21:37.091822image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

insulin
Categorical

Distinct4
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size97.3 KiB
No
46376 
Steady
30069 
Down
11908 
Up
10987 

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowDown
2nd rowUp
3rd rowNo
4th rowNo
5th rowUp

Common Values

ValueCountFrequency (%)
No46376
46.7%
Steady30069
30.3%
Down11908
 
12.0%
Up10987
 
11.1%

Common Values (Plot)

2025-09-25T18:21:37.134651image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

metformin
Categorical

Imbalance 

Distinct4
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size97.3 KiB
No
79497 
Steady
18206 
Up
 
1063
Down
 
574

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowSteady
2nd rowNo
3rd rowSteady
4th rowSteady
5th rowNo

Common Values

ValueCountFrequency (%)
No79497
80.0%
Steady18206
 
18.3%
Up1063
 
1.1%
Down574
 
0.6%

Common Values (Plot)

2025-09-25T18:21:37.189988image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

num_medications
Real number (ℝ)

Distinct75
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean16
Minimum1
Maximum81
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size776.2 KiB
2025-09-25T18:21:37.268046image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile6
Q110
median15
Q320
95-th percentile31
Maximum81
Range80
Interquartile range (IQR)10

Descriptive statistics

Standard deviation8.1
Coefficient of variation (CV)0.51
Kurtosis3.5
Mean16
Median Absolute Deviation (MAD)5
Skewness1.3
Sum1.6 × 106
Variance66
MonotonicityNot monotonic
2025-09-25T18:21:37.372497image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
135976
 
6.0%
125888
 
5.9%
115696
 
5.7%
155694
 
5.7%
145592
 
5.6%
Other values (70)70494
71.0%
ValueCountFrequency (%)
1260
 
0.3%
2457
 
0.5%
3874
0.9%
41383
1.4%
51964
2.0%
ValueCountFrequency (%)
811
 
< 0.1%
791
 
< 0.1%
752
< 0.1%
741
 
< 0.1%
723
< 0.1%

num_procedures
Real number (ℝ)

Zeros 

Distinct7
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1.3
Minimum0
Maximum6
Zeros45679
Zeros (%)46.0%
Negative0
Negative (%)0.0%
Memory size776.2 KiB
2025-09-25T18:21:37.448398image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median1
Q32
95-th percentile5
Maximum6
Range6
Interquartile range (IQR)2

Descriptive statistics

Standard deviation1.7
Coefficient of variation (CV)1.3
Kurtosis0.88
Mean1.3
Median Absolute Deviation (MAD)1
Skewness1.3
Sum1.3 × 105
Variance2.9
MonotonicityNot monotonic
2025-09-25T18:21:37.506985image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram with fixed size bins (bins=7)
ValueCountFrequency (%)
045679
46.0%
120249
20.4%
212372
 
12.5%
39203
 
9.3%
64801
 
4.8%
Other values (2)7036
 
7.1%
ValueCountFrequency (%)
045679
46.0%
120249
20.4%
212372
 
12.5%
39203
 
9.3%
44049
 
4.1%
ValueCountFrequency (%)
64801
 
4.8%
52987
 
3.0%
44049
 
4.1%
39203
9.3%
212372
12.5%

race
Categorical

Imbalance 

Distinct6
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size97.4 KiB
Caucasian
74220 
AfricanAmerican
18772 
Unknown
 
2232
Hispanic
 
2017
Other
 
1471

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowCaucasian
2nd rowCaucasian
3rd rowCaucasian
4th rowCaucasian
5th rowCaucasian

Common Values

ValueCountFrequency (%)
Caucasian74220
74.7%
AfricanAmerican18772
 
18.9%
Unknown2232
 
2.2%
Hispanic2017
 
2.0%
Other1471
 
1.5%

Common Values (Plot)

2025-09-25T18:21:37.566823image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Readmitted within 30 Days_Value
Real number (ℝ)

Zeros 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.13
Minimum0
Maximum1
Zeros86780
Zeros (%)87.4%
Negative0
Negative (%)0.0%
Memory size776.2 KiB
2025-09-25T18:21:37.630605image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile1
Maximum1
Range1
Interquartile range (IQR)0

Descriptive statistics

Standard deviation0.33
Coefficient of variation (CV)2.6
Kurtosis3.1
Mean0.13
Median Absolute Deviation (MAD)0
Skewness2.2
Sum1.3 × 104
Variance0.11
MonotonicityNot monotonic
2025-09-25T18:21:37.686999image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram with fixed size bins (bins=2)
ValueCountFrequency (%)
086780
87.4%
112560
 
12.6%
ValueCountFrequency (%)
086780
87.4%
112560
 
12.6%
ValueCountFrequency (%)
112560
 
12.6%
086780
87.4%

Readmitted (Any)_Value
Real number (ℝ)

Zeros 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.47
Minimum0
Maximum1
Zeros52524
Zeros (%)52.9%
Negative0
Negative (%)0.0%
Memory size776.2 KiB
2025-09-25T18:21:37.742135image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q31
95-th percentile1
Maximum1
Range1
Interquartile range (IQR)1

Descriptive statistics

Standard deviation0.5
Coefficient of variation (CV)1.1
Kurtosis-2
Mean0.47
Median Absolute Deviation (MAD)0
Skewness0.12
Sum4.7 × 104
Variance0.25
MonotonicityNot monotonic
2025-09-25T18:21:37.801138image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram with fixed size bins (bins=2)
ValueCountFrequency (%)
052524
52.9%
146816
47.1%
ValueCountFrequency (%)
052524
52.9%
146816
47.1%
ValueCountFrequency (%)
146816
47.1%
052524
52.9%

Long Hospital Stay (>7 days)_Value
Real number (ℝ)

Zeros 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.15
Minimum0
Maximum1
Zeros84629
Zeros (%)85.2%
Negative0
Negative (%)0.0%
Memory size776.2 KiB
2025-09-25T18:21:37.857034image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile1
Maximum1
Range1
Interquartile range (IQR)0

Descriptive statistics

Standard deviation0.36
Coefficient of variation (CV)2.4
Kurtosis1.9
Mean0.15
Median Absolute Deviation (MAD)0
Skewness2
Sum1.5 × 104
Variance0.13
MonotonicityDecreasing
2025-09-25T18:21:37.914520image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram with fixed size bins (bins=2)
ValueCountFrequency (%)
084629
85.2%
114711
 
14.8%
ValueCountFrequency (%)
084629
85.2%
114711
 
14.8%
ValueCountFrequency (%)
114711
 
14.8%
084629
85.2%
Distinct14
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean4.4
Minimum1
Maximum14
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size776.2 KiB
2025-09-25T18:21:37.973703image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q12
median4
Q36
95-th percentile11
Maximum14
Range13
Interquartile range (IQR)4

Descriptive statistics

Standard deviation3
Coefficient of variation (CV)0.68
Kurtosis0.89
Mean4.4
Median Absolute Deviation (MAD)2
Skewness1.1
Sum4.4 × 105
Variance8.8
MonotonicityDecreasing
2025-09-25T18:21:38.047329image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram with fixed size bins (bins=14)
ValueCountFrequency (%)
317432
17.5%
216891
17.0%
113822
13.9%
413684
13.8%
59749
 
9.8%
Other values (9)27762
27.9%
ValueCountFrequency (%)
113822
13.9%
216891
17.0%
317432
17.5%
413684
13.8%
59749
9.8%
ValueCountFrequency (%)
14995
1.0%
131152
1.2%
121383
1.4%
111770
1.8%
102262
2.3%
Distinct14
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean4.4
Minimum1
Maximum14
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size776.2 KiB
2025-09-25T18:21:38.115009image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q12
median4
Q36
95-th percentile11
Maximum14
Range13
Interquartile range (IQR)4

Descriptive statistics

Standard deviation3
Coefficient of variation (CV)0.68
Kurtosis0.89
Mean4.4
Median Absolute Deviation (MAD)2
Skewness1.1
Sum4.4 × 105
Variance8.8
MonotonicityDecreasing
2025-09-25T18:21:38.188169image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram with fixed size bins (bins=14)
ValueCountFrequency (%)
317432
17.5%
216891
17.0%
113822
13.9%
413684
13.8%
59749
 
9.8%
Other values (9)27762
27.9%
ValueCountFrequency (%)
113822
13.9%
216891
17.0%
317432
17.5%
413684
13.8%
59749
9.8%
ValueCountFrequency (%)
14995
1.0%
131152
1.2%
121383
1.4%
111770
1.8%
102262
2.3%

Taking Metformin_Value
Real number (ℝ)

Zeros 

Distinct3
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.21
Minimum0
Maximum2
Zeros78858
Zeros (%)79.4%
Negative0
Negative (%)0.0%
Memory size776.2 KiB
2025-09-25T18:21:38.250674image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile1
Maximum2
Range2
Interquartile range (IQR)0

Descriptive statistics

Standard deviation0.41
Coefficient of variation (CV)2
Kurtosis0.26
Mean0.21
Median Absolute Deviation (MAD)0
Skewness1.5
Sum2.1 × 104
Variance0.17
MonotonicityNot monotonic
2025-09-25T18:21:38.311059image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram with fixed size bins (bins=3)
ValueCountFrequency (%)
078858
79.4%
120423
 
20.6%
259
 
0.1%
ValueCountFrequency (%)
078858
79.4%
120423
 
20.6%
259
 
0.1%
ValueCountFrequency (%)
259
 
0.1%
120423
 
20.6%
078858
79.4%

Age
Categorical

Distinct5
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size97.3 KiB
70+
44352 
[50-70)
39118 
[20-50)
15020 
[10-20)
 
690
[0-10)
 
160

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row70+
2nd row70+
3rd row[20-50)
4th row70+
5th row70+

Common Values

ValueCountFrequency (%)
70+44352
44.6%
[50-70)39118
39.4%
[20-50)15020
 
15.1%
[10-20)690
 
0.7%
[0-10)160
 
0.2%

Common Values (Plot)

2025-09-25T18:21:38.562136image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Race
Categorical

Imbalance 

Distinct6
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size97.4 KiB
Caucasian
74220 
AfricanAmerican
18772 
Unknown
 
2232
Hispanic
 
2017
Other
 
1471

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowCaucasian
2nd rowCaucasian
3rd rowCaucasian
4th rowCaucasian
5th rowCaucasian

Common Values

ValueCountFrequency (%)
Caucasian74220
74.7%
AfricanAmerican18772
 
18.9%
Unknown2232
 
2.2%
Hispanic2017
 
2.0%
Other1471
 
1.5%

Common Values (Plot)

2025-09-25T18:21:38.625098image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Gender
Categorical

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size97.3 KiB
Female
53454 
Male
45886 

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowFemale
2nd rowMale
3rd rowMale
4th rowFemale
5th rowFemale

Common Values

ValueCountFrequency (%)
Female53454
53.8%
Male45886
46.2%

Common Values (Plot)

2025-09-25T18:21:38.678578image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

A1C
Categorical

Imbalance 

Distinct4
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size97.3 KiB
None
82506 
>8
 
8137
Norm
 
4922
>7
 
3775

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowNone
2nd rowNorm
3rd rowNone
4th rowNorm
5th row>7

Common Values

ValueCountFrequency (%)
None82506
83.1%
>88137
 
8.2%
Norm4922
 
5.0%
>73775
 
3.8%

Common Values (Plot)

2025-09-25T18:21:38.720347image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Taking Insulin
Categorical

Distinct4
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size97.3 KiB
No
46376 
Steady
30069 
Down
11908 
Up
10987 

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowDown
2nd rowUp
3rd rowNo
4th rowNo
5th rowUp

Common Values

ValueCountFrequency (%)
No46376
46.7%
Steady30069
30.3%
Down11908
 
12.0%
Up10987
 
11.1%

Common Values (Plot)

2025-09-25T18:21:38.771355image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Taking Metformin
Categorical

Imbalance 

Distinct4
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size97.3 KiB
No
79497 
Steady
18206 
Up
 
1063
Down
 
574

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowSteady
2nd rowNo
3rd rowSteady
4th rowSteady
5th rowNo

Common Values

ValueCountFrequency (%)
No79497
80.0%
Steady18206
 
18.3%
Up1063
 
1.1%
Down574
 
0.6%

Common Values (Plot)

2025-09-25T18:21:38.825536image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/