Overview

Dataset statistics

Number of variables40
Number of observations98052
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory11.6 MiB
Average record size in memory124.0 B

Variable types

Numeric10
Boolean20
Categorical10

Warnings

number_emergency is highly skewed (γ1 = 22.71023391) Skewed
df_index has unique values Unique
num_procedures has 44574 (45.5%) zeros Zeros
number_outpatient has 81679 (83.3%) zeros Zeros
number_emergency has 86845 (88.6%) zeros Zeros
number_inpatient has 64633 (65.9%) zeros Zeros

Reproduction

Analysis started2021-05-05 21:26:31.501435
Analysis finished2021-05-05 21:27:10.019817
Duration38.52 seconds
Software versionpandas-profiling v2.11.0
Download configurationconfig.yaml

Variables

df_index
Real number (ℝ≥0)

UNIQUE

Distinct98052
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean51115.77261
Minimum1
Maximum101765
Zeros0
Zeros (%)0.0%
Memory size766.2 KiB
2021-05-05T17:27:10.130460image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile5180.55
Q125574.75
median51369.5
Q376379.25
95-th percentile96683.45
Maximum101765
Range101764
Interquartile range (IQR)50804.5

Descriptive statistics

Standard deviation29307.32802
Coefficient of variation (CV)0.5733519523
Kurtosis-1.191416496
Mean51115.77261
Median Absolute Deviation (MAD)25399.5
Skewness-0.01479878364
Sum5012003736
Variance858919475.5
MonotocityStrictly increasing
2021-05-05T17:27:10.261838image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
20471
 
< 0.1%
805621
 
< 0.1%
293391
 
< 0.1%
191001
 
< 0.1%
170531
 
< 0.1%
231981
 
< 0.1%
211511
 
< 0.1%
1010281
 
< 0.1%
989811
 
< 0.1%
764641
 
< 0.1%
Other values (98042)98042
> 99.9%
ValueCountFrequency (%)
11
< 0.1%
21
< 0.1%
31
< 0.1%
41
< 0.1%
51
< 0.1%
ValueCountFrequency (%)
1017651
< 0.1%
1017641
< 0.1%
1017631
< 0.1%
1017621
< 0.1%
1017611
< 0.1%

time_in_hospital
Real number (ℝ≥0)

Distinct14
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean4.42201077
Minimum1
Maximum14
Zeros0
Zeros (%)0.0%
Memory size766.2 KiB
2021-05-05T17:27:10.364788image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/

Quantile statistics

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

Descriptive statistics

Standard deviation2.993069775
Coefficient of variation (CV)0.6768571881
Kurtosis0.8179424536
Mean4.42201077
Median Absolute Deviation (MAD)2
Skewness1.123566649
Sum433587
Variance8.958466679
MonotocityNot monotonic
2021-05-05T17:27:10.461917image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
Histogram with fixed size bins (bins=14)
ValueCountFrequency (%)
317049
17.4%
216441
16.8%
113489
13.8%
413434
13.7%
59699
9.9%
67320
7.5%
75694
 
5.8%
84276
 
4.4%
92928
 
3.0%
102287
 
2.3%
Other values (4)5435
 
5.5%
ValueCountFrequency (%)
113489
13.8%
216441
16.8%
317049
17.4%
413434
13.7%
59699
9.9%
ValueCountFrequency (%)
141017
1.0%
131185
1.2%
121424
1.5%
111809
1.8%
102287
2.3%

num_lab_procedures
Real number (ℝ≥0)

Distinct118
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean43.14846204
Minimum1
Maximum132
Zeros0
Zeros (%)0.0%
Memory size766.2 KiB
2021-05-05T17:27:10.574248image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile4
Q131
median44
Q357
95-th percentile73
Maximum132
Range131
Interquartile range (IQR)26

Descriptive statistics

Standard deviation19.71175698
Coefficient of variation (CV)0.4568356797
Kurtosis-0.2451397605
Mean43.14846204
Median Absolute Deviation (MAD)13
Skewness-0.2355321992
Sum4230793
Variance388.5533634
MonotocityNot monotonic
2021-05-05T17:27:10.699443image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
13096
 
3.2%
432724
 
2.8%
442414
 
2.5%
452306
 
2.4%
382131
 
2.2%
462120
 
2.2%
402113
 
2.2%
412046
 
2.1%
422031
 
2.1%
472028
 
2.1%
Other values (108)75043
76.5%
ValueCountFrequency (%)
13096
3.2%
21062
 
1.1%
3647
 
0.7%
4364
 
0.4%
5276
 
0.3%
ValueCountFrequency (%)
1321
< 0.1%
1291
< 0.1%
1261
< 0.1%
1211
< 0.1%
1201
< 0.1%

num_procedures
Real number (ℝ≥0)

ZEROS

Distinct7
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1.350711867
Minimum0
Maximum6
Zeros44574
Zeros (%)45.5%
Memory size766.2 KiB
2021-05-05T17:27:10.806127image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/

Quantile statistics

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

Descriptive statistics

Standard deviation1.708474845
Coefficient of variation (CV)1.264869945
Kurtosis0.8238736795
Mean1.350711867
Median Absolute Deviation (MAD)1
Skewness1.303967313
Sum132440
Variance2.918886297
MonotocityNot monotonic
2021-05-05T17:27:10.884838image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
Histogram with fixed size bins (bins=7)
ValueCountFrequency (%)
044574
45.5%
120029
20.4%
212383
 
12.6%
39210
 
9.4%
64811
 
4.9%
44076
 
4.2%
52969
 
3.0%
ValueCountFrequency (%)
044574
45.5%
120029
20.4%
212383
 
12.6%
39210
 
9.4%
44076
 
4.2%
ValueCountFrequency (%)
64811
 
4.9%
52969
 
3.0%
44076
 
4.2%
39210
9.4%
212383
12.6%

num_medications
Real number (ℝ≥0)

Distinct75
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean16.11958961
Minimum1
Maximum81
Zeros0
Zeros (%)0.0%
Memory size766.2 KiB
2021-05-05T17:27:10.990143image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile6
Q111
median15
Q320
95-th percentile31
Maximum81
Range80
Interquartile range (IQR)9

Descriptive statistics

Standard deviation8.108495519
Coefficient of variation (CV)0.5030212132
Kurtosis3.493545221
Mean16.11958961
Median Absolute Deviation (MAD)5
Skewness1.332717291
Sum1580558
Variance65.74769959
MonotocityNot monotonic
2021-05-05T17:27:11.113852image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
135885
 
6.0%
125816
 
5.9%
155621
 
5.7%
115592
 
5.7%
145520
 
5.6%
165271
 
5.4%
105167
 
5.3%
174783
 
4.9%
94711
 
4.8%
184399
 
4.5%
Other values (65)45287
46.2%
ValueCountFrequency (%)
1236
 
0.2%
2397
 
0.4%
3785
0.8%
41269
1.3%
51835
1.9%
ValueCountFrequency (%)
811
 
< 0.1%
791
 
< 0.1%
752
< 0.1%
741
 
< 0.1%
723
< 0.1%

number_outpatient
Real number (ℝ≥0)

ZEROS

Distinct39
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.3763819198
Minimum0
Maximum42
Zeros81679
Zeros (%)83.3%
Memory size766.2 KiB
2021-05-05T17:27:11.236585image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile2
Maximum42
Range42
Interquartile range (IQR)0

Descriptive statistics

Standard deviation1.283365421
Coefficient of variation (CV)3.409742482
Kurtosis145.589922
Mean0.3763819198
Median Absolute Deviation (MAD)0
Skewness8.78166345
Sum36905
Variance1.647026805
MonotocityNot monotonic
2021-05-05T17:27:11.341121image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
Histogram with fixed size bins (bins=39)
ValueCountFrequency (%)
081679
83.3%
18340
 
8.5%
23514
 
3.6%
32005
 
2.0%
41078
 
1.1%
5521
 
0.5%
6297
 
0.3%
7153
 
0.2%
898
 
0.1%
983
 
0.1%
Other values (29)284
 
0.3%
ValueCountFrequency (%)
081679
83.3%
18340
 
8.5%
23514
 
3.6%
32005
 
2.0%
41078
 
1.1%
ValueCountFrequency (%)
421
< 0.1%
401
< 0.1%
391
< 0.1%
381
< 0.1%
371
< 0.1%

number_emergency
Real number (ℝ≥0)

SKEWED
ZEROS

Distinct33
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.2024639987
Minimum0
Maximum76
Zeros86845
Zeros (%)88.6%
Memory size766.2 KiB
2021-05-05T17:27:11.444000image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile1
Maximum76
Range76
Interquartile range (IQR)0

Descriptive statistics

Standard deviation0.9428968764
Coefficient of variation (CV)4.657108832
Kurtosis1171.626491
Mean0.2024639987
Median Absolute Deviation (MAD)0
Skewness22.71023391
Sum19852
Variance0.8890545196
MonotocityNot monotonic
2021-05-05T17:27:11.546273image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
Histogram with fixed size bins (bins=33)
ValueCountFrequency (%)
086845
88.6%
17550
 
7.7%
22011
 
2.1%
3716
 
0.7%
4372
 
0.4%
5190
 
0.2%
693
 
0.1%
772
 
0.1%
850
 
0.1%
1034
 
< 0.1%
Other values (23)119
 
0.1%
ValueCountFrequency (%)
086845
88.6%
17550
 
7.7%
22011
 
2.1%
3716
 
0.7%
4372
 
0.4%
ValueCountFrequency (%)
761
< 0.1%
641
< 0.1%
631
< 0.1%
541
< 0.1%
461
< 0.1%

number_inpatient
Real number (ℝ≥0)

ZEROS

Distinct20
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.646871048
Minimum0
Maximum21
Zeros64633
Zeros (%)65.9%
Memory size766.2 KiB
2021-05-05T17:27:11.654979image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q31
95-th percentile3
Maximum21
Range21
Interquartile range (IQR)1

Descriptive statistics

Standard deviation1.271025294
Coefficient of variation (CV)1.964882024
Kurtosis19.94313813
Mean0.646871048
Median Absolute Deviation (MAD)0
Skewness3.554811324
Sum63427
Variance1.615505299
MonotocityNot monotonic
2021-05-05T17:27:11.744772image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
Histogram with fixed size bins (bins=20)
ValueCountFrequency (%)
064633
65.9%
119067
 
19.4%
27421
 
7.6%
33346
 
3.4%
41597
 
1.6%
5802
 
0.8%
6474
 
0.5%
7266
 
0.3%
8147
 
0.1%
9111
 
0.1%
Other values (10)188
 
0.2%
ValueCountFrequency (%)
064633
65.9%
119067
 
19.4%
27421
 
7.6%
33346
 
3.4%
41597
 
1.6%
ValueCountFrequency (%)
211
 
< 0.1%
192
 
< 0.1%
181
 
< 0.1%
165
< 0.1%
158
< 0.1%

number_diagnoses
Real number (ℝ≥0)

Distinct14
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean7.512095623
Minimum3
Maximum16
Zeros0
Zeros (%)0.0%
Memory size766.2 KiB
2021-05-05T17:27:11.837856image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/

Quantile statistics

Minimum3
5-th percentile4
Q16
median8
Q39
95-th percentile9
Maximum16
Range13
Interquartile range (IQR)3

Descriptive statistics

Standard deviation1.832471842
Coefficient of variation (CV)0.2439361709
Kurtosis-0.3450219608
Mean7.512095623
Median Absolute Deviation (MAD)1
Skewness-0.8175309479
Sum736576
Variance3.357953051
MonotocityNot monotonic
2021-05-05T17:27:11.931006image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
Histogram with fixed size bins (bins=14)
ValueCountFrequency (%)
948687
49.7%
510592
 
10.8%
810388
 
10.6%
710179
 
10.4%
69988
 
10.2%
45360
 
5.5%
32751
 
2.8%
1640
 
< 0.1%
1316
 
< 0.1%
1016
 
< 0.1%
Other values (4)35
 
< 0.1%
ValueCountFrequency (%)
32751
 
2.8%
45360
5.5%
510592
10.8%
69988
10.2%
710179
10.4%
ValueCountFrequency (%)
1640
< 0.1%
158
 
< 0.1%
147
 
< 0.1%
1316
 
< 0.1%
129
 
< 0.1%

change
Boolean

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size95.9 KiB
False
52774 
True
45278 
ValueCountFrequency (%)
False52774
53.8%
True45278
46.2%
2021-05-05T17:27:11.997532image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size95.9 KiB
True
75350 
False
22702 
ValueCountFrequency (%)
True75350
76.8%
False22702
 
23.2%
2021-05-05T17:27:12.035788image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/

isFemale
Boolean

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size95.9 KiB
True
52833 
False
45219 
ValueCountFrequency (%)
True52833
53.9%
False45219
46.1%
2021-05-05T17:27:12.072456image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size766.2 KiB
0
79171 
1
18881 

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters98052
Distinct characters2
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 row0
2nd row1
3rd row0
4th row0
5th row0
ValueCountFrequency (%)
079171
80.7%
118881
 
19.3%
2021-05-05T17:27:12.232824image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
Histogram of lengths of the category
2021-05-05T17:27:12.291452image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
ValueCountFrequency (%)
079171
80.7%
118881
 
19.3%

Most occurring characters

ValueCountFrequency (%)
079171
80.7%
118881
 
19.3%

Most occurring categories

ValueCountFrequency (%)
Decimal Number98052
100.0%

Most frequent character per category

ValueCountFrequency (%)
079171
80.7%
118881
 
19.3%

Most occurring scripts

ValueCountFrequency (%)
Common98052
100.0%

Most frequent character per script

ValueCountFrequency (%)
079171
80.7%
118881
 
19.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII98052
100.0%

Most frequent character per block

ValueCountFrequency (%)
079171
80.7%
118881
 
19.3%

race_Asian
Categorical

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size766.2 KiB
0
97427 
1
 
625

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters98052
Distinct characters2
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 row0
2nd row0
3rd row0
4th row0
5th row0
ValueCountFrequency (%)
097427
99.4%
1625
 
0.6%
2021-05-05T17:27:12.451316image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
Histogram of lengths of the category
2021-05-05T17:27:12.509689image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
ValueCountFrequency (%)
097427
99.4%
1625
 
0.6%

Most occurring characters

ValueCountFrequency (%)
097427
99.4%
1625
 
0.6%

Most occurring categories

ValueCountFrequency (%)
Decimal Number98052
100.0%

Most frequent character per category

ValueCountFrequency (%)
097427
99.4%
1625
 
0.6%

Most occurring scripts

ValueCountFrequency (%)
Common98052
100.0%

Most frequent character per script

ValueCountFrequency (%)
097427
99.4%
1625
 
0.6%

Most occurring blocks

ValueCountFrequency (%)
ASCII98052
100.0%

Most frequent character per block

ValueCountFrequency (%)
097427
99.4%
1625
 
0.6%

race_Caucasian
Categorical

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size766.2 KiB
1
75079 
0
22973 

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters98052
Distinct characters2
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 row1
2nd row0
3rd row1
4th row1
5th row1
ValueCountFrequency (%)
175079
76.6%
022973
 
23.4%
2021-05-05T17:27:12.663549image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
Histogram of lengths of the category
2021-05-05T17:27:12.723901image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
ValueCountFrequency (%)
175079
76.6%
022973
 
23.4%

Most occurring characters

ValueCountFrequency (%)
175079
76.6%
022973
 
23.4%

Most occurring categories

ValueCountFrequency (%)
Decimal Number98052
100.0%

Most frequent character per category

ValueCountFrequency (%)
175079
76.6%
022973
 
23.4%

Most occurring scripts

ValueCountFrequency (%)
Common98052
100.0%

Most frequent character per script

ValueCountFrequency (%)
175079
76.6%
022973
 
23.4%

Most occurring blocks

ValueCountFrequency (%)
ASCII98052
100.0%

Most frequent character per block

ValueCountFrequency (%)
175079
76.6%
022973
 
23.4%

race_Hispanic
Categorical

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size766.2 KiB
0
96068 
1
 
1984

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters98052
Distinct characters2
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 row0
2nd row0
3rd row0
4th row0
5th row0
ValueCountFrequency (%)
096068
98.0%
11984
 
2.0%
2021-05-05T17:27:12.887504image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
Histogram of lengths of the category
2021-05-05T17:27:12.947141image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
ValueCountFrequency (%)
096068
98.0%
11984
 
2.0%

Most occurring characters

ValueCountFrequency (%)
096068
98.0%
11984
 
2.0%

Most occurring categories

ValueCountFrequency (%)
Decimal Number98052
100.0%

Most frequent character per category

ValueCountFrequency (%)
096068
98.0%
11984
 
2.0%

Most occurring scripts

ValueCountFrequency (%)
Common98052
100.0%

Most frequent character per script

ValueCountFrequency (%)
096068
98.0%
11984
 
2.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII98052
100.0%

Most frequent character per block

ValueCountFrequency (%)
096068
98.0%
11984
 
2.0%

race_Other
Categorical

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size766.2 KiB
0
96569 
1
 
1483

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters98052
Distinct characters2
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 row0
2nd row0
3rd row0
4th row0
5th row0
ValueCountFrequency (%)
096569
98.5%
11483
 
1.5%
2021-05-05T17:27:13.101510image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
Histogram of lengths of the category
2021-05-05T17:27:13.159151image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
ValueCountFrequency (%)
096569
98.5%
11483
 
1.5%

Most occurring characters

ValueCountFrequency (%)
096569
98.5%
11483
 
1.5%

Most occurring categories

ValueCountFrequency (%)
Decimal Number98052
100.0%

Most frequent character per category

ValueCountFrequency (%)
096569
98.5%
11483
 
1.5%

Most occurring scripts

ValueCountFrequency (%)
Common98052
100.0%

Most frequent character per script

ValueCountFrequency (%)
096569
98.5%
11483
 
1.5%

Most occurring blocks

ValueCountFrequency (%)
ASCII98052
100.0%

Most frequent character per block

ValueCountFrequency (%)
096569
98.5%
11483
 
1.5%
Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size95.9 KiB
False
62196 
True
35856 
ValueCountFrequency (%)
False62196
63.4%
True35856
36.6%
2021-05-05T17:27:13.194817image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size95.9 KiB
False
75866 
True
22186 
ValueCountFrequency (%)
False75866
77.4%
True22186
 
22.6%
2021-05-05T17:27:13.232088image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size95.9 KiB
True
57838 
False
40214 
ValueCountFrequency (%)
True57838
59.0%
False40214
41.0%
2021-05-05T17:27:13.269115image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size95.9 KiB
False
63068 
True
34984 
ValueCountFrequency (%)
False63068
64.3%
True34984
35.7%
2021-05-05T17:27:13.306179image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size95.9 KiB
False
71896 
True
26156 
ValueCountFrequency (%)
False71896
73.3%
True26156
 
26.7%
2021-05-05T17:27:13.343156image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size95.9 KiB
False
88463 
True
9589 
ValueCountFrequency (%)
False88463
90.2%
True9589
 
9.8%
2021-05-05T17:27:13.378620image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size95.9 KiB
False
90803 
True
 
7249
ValueCountFrequency (%)
False90803
92.6%
True7249
 
7.4%
2021-05-05T17:27:13.416987image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size95.9 KiB
False
83449 
True
14603 
ValueCountFrequency (%)
False83449
85.1%
True14603
 
14.9%
2021-05-05T17:27:13.453372image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size95.9 KiB
False
80684 
True
17368 
ValueCountFrequency (%)
False80684
82.3%
True17368
 
17.7%
2021-05-05T17:27:13.489495image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size95.9 KiB
False
78807 
True
19245 
ValueCountFrequency (%)
False78807
80.4%
True19245
 
19.6%
2021-05-05T17:27:13.525778image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size95.9 KiB
False
96529 
True
 
1523
ValueCountFrequency (%)
False96529
98.4%
True1523
 
1.6%
2021-05-05T17:27:13.562114image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/