Overview

Dataset statistics

Number of variables9
Number of observations430
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory34.1 KiB
Average record size in memory81.3 B

Variable types

Categorical2
Numeric7

Dataset

DescriptionSample
Author해봄데이터㈜
URLhttps://www.bigdata-coast.kr/gdsInfo/gdsInfoDetail.do?gdsCd=CT02HBM010

Alerts

LGZ_NETBT_CTSH is highly overall correlated with CTOF_LOHigh correlation
FSGN_CTSH is highly overall correlated with FSASSN_SZN_CTSH and 1 other fieldsHigh correlation
FSASSN_SZN_CTSH is highly overall correlated with FSGN_CTSHHigh correlation
CTOF_LO is highly overall correlated with LGZ_NETBT_CTSH and 1 other fieldsHigh correlation
SST is highly overall correlated with CTOF_YMDHigh correlation
FSLSPS_CTSH is highly overall correlated with FSGN_CTSH and 1 other fieldsHigh correlation
CTOF_YMD is highly overall correlated with SSTHigh correlation
NCHVY_FSATN_CTSH has 384 (89.3%) zerosZeros
LGZ_NETBT_CTSH has 306 (71.2%) zerosZeros
FSGN_CTSH has 382 (88.8%) zerosZeros
FSASSN_SZN_CTSH has 388 (90.2%) zerosZeros

Reproduction

Analysis started2024-03-13 12:52:51.394197
Analysis finished2024-03-13 12:53:00.143105
Duration8.75 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

FSLSPS_CTSH
Categorical

HIGH CORRELATION 

Distinct4
Distinct (%)0.9%
Missing0
Missing (%)0.0%
Memory size3.5 KiB
100
155 
0
155 
200
114 
150
 
6

Length

Max length3
Median length3
Mean length2.2790698
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row200
2nd row200
3rd row200
4th row100
5th row100

Common Values

ValueCountFrequency (%)
100 155
36.0%
0 155
36.0%
200 114
26.5%
150 6
 
1.4%

Length

2024-03-13T21:53:00.245689image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-13T21:53:00.399751image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
100 155
36.0%
0 155
36.0%
200 114
26.5%
150 6
 
1.4%

NCHVY_FSATN_CTSH
Real number (ℝ)

ZEROS 

Distinct6
Distinct (%)1.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean28.951163
Minimum0
Maximum615
Zeros384
Zeros (%)89.3%
Negative0
Negative (%)0.0%
Memory size3.9 KiB
2024-03-13T21:53:00.541519image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile252.7
Maximum615
Range615
Interquartile range (IQR)0

Descriptive statistics

Standard deviation105.39078
Coefficient of variation (CV)3.6402953
Kurtosis18.382036
Mean28.951163
Median Absolute Deviation (MAD)0
Skewness4.2588954
Sum12449
Variance11107.217
MonotonicityNot monotonic
2024-03-13T21:53:00.666793image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=6)
ValueCountFrequency (%)
0 384
89.3%
79 15
 
3.5%
146 9
 
2.1%
615 8
 
1.9%
340 8
 
1.9%
385 6
 
1.4%
ValueCountFrequency (%)
0 384
89.3%
79 15
 
3.5%
146 9
 
2.1%
340 8
 
1.9%
385 6
 
1.4%
615 8
 
1.9%
ValueCountFrequency (%)
615 8
 
1.9%
385 6
 
1.4%
340 8
 
1.9%
146 9
 
2.1%
79 15
 
3.5%
0 384
89.3%

LGZ_NETBT_CTSH
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct17
Distinct (%)4.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean47.083721
Minimum0
Maximum435
Zeros306
Zeros (%)71.2%
Negative0
Negative (%)0.0%
Memory size3.9 KiB
2024-03-13T21:53:00.812241image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q316
95-th percentile373
Maximum435
Range435
Interquartile range (IQR)16

Descriptive statistics

Standard deviation114.43204
Coefficient of variation (CV)2.430395
Kurtosis5.0305312
Mean47.083721
Median Absolute Deviation (MAD)0
Skewness2.5523807
Sum20246
Variance13094.692
MonotonicityNot monotonic
2024-03-13T21:53:00.987628image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=17)
ValueCountFrequency (%)
0 306
71.2%
102 9
 
2.1%
414 9
 
2.1%
368 9
 
2.1%
39 9
 
2.1%
373 9
 
2.1%
435 9
 
2.1%
107 9
 
2.1%
25 8
 
1.9%
266 8
 
1.9%
Other values (7) 45
 
10.5%
ValueCountFrequency (%)
0 306
71.2%
3 6
 
1.4%
4 7
 
1.6%
16 6
 
1.4%
24 6
 
1.4%
25 8
 
1.9%
28 6
 
1.4%
39 9
 
2.1%
51 6
 
1.4%
77 8
 
1.9%
ValueCountFrequency (%)
435 9
2.1%
414 9
2.1%
373 9
2.1%
368 9
2.1%
266 8
1.9%
107 9
2.1%
102 9
2.1%
77 8
1.9%
51 6
1.4%
39 9
2.1%

FSGN_CTSH
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct10
Distinct (%)2.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean8.5046512
Minimum0
Maximum189
Zeros382
Zeros (%)88.8%
Negative0
Negative (%)0.0%
Memory size3.9 KiB
2024-03-13T21:53:01.153194image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile59
Maximum189
Range189
Interquartile range (IQR)0

Descriptive statistics

Standard deviation32.242507
Coefficient of variation (CV)3.7911616
Kurtosis17.932967
Mean8.5046512
Median Absolute Deviation (MAD)0
Skewness4.2968755
Sum3657
Variance1039.5792
MonotonicityNot monotonic
2024-03-13T21:53:01.324221image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=10)
ValueCountFrequency (%)
0 382
88.8%
7 6
 
1.4%
35 6
 
1.4%
59 6
 
1.4%
150 6
 
1.4%
14 6
 
1.4%
131 6
 
1.4%
29 6
 
1.4%
189 3
 
0.7%
180 3
 
0.7%
ValueCountFrequency (%)
0 382
88.8%
7 6
 
1.4%
14 6
 
1.4%
29 6
 
1.4%
35 6
 
1.4%
59 6
 
1.4%
131 6
 
1.4%
150 6
 
1.4%
180 3
 
0.7%
189 3
 
0.7%
ValueCountFrequency (%)
189 3
 
0.7%
180 3
 
0.7%
150 6
 
1.4%
131 6
 
1.4%
59 6
 
1.4%
35 6
 
1.4%
29 6
 
1.4%
14 6
 
1.4%
7 6
 
1.4%
0 382
88.8%

FSASSN_SZN_CTSH
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct10
Distinct (%)2.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean9.0837209
Minimum0
Maximum257
Zeros388
Zeros (%)90.2%
Negative0
Negative (%)0.0%
Memory size3.9 KiB
2024-03-13T21:53:01.481530image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile39
Maximum257
Range257
Interquartile range (IQR)0

Descriptive statistics

Standard deviation36.863099
Coefficient of variation (CV)4.0581497
Kurtosis24.823178
Mean9.0837209
Median Absolute Deviation (MAD)0
Skewness4.9215679
Sum3906
Variance1358.8881
MonotonicityNot monotonic
2024-03-13T21:53:01.643942image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=10)
ValueCountFrequency (%)
0 388
90.2%
62 6
 
1.4%
26 6
 
1.4%
39 6
 
1.4%
151 6
 
1.4%
27 6
 
1.4%
36 3
 
0.7%
257 3
 
0.7%
194 3
 
0.7%
205 3
 
0.7%
ValueCountFrequency (%)
0 388
90.2%
26 6
 
1.4%
27 6
 
1.4%
36 3
 
0.7%
39 6
 
1.4%
62 6
 
1.4%
151 6
 
1.4%
194 3
 
0.7%
205 3
 
0.7%
257 3
 
0.7%
ValueCountFrequency (%)
257 3
 
0.7%
205 3
 
0.7%
194 3
 
0.7%
151 6
 
1.4%
62 6
 
1.4%
39 6
 
1.4%
36 3
 
0.7%
27 6
 
1.4%
26 6
 
1.4%
0 388
90.2%

CTOF_LO
Real number (ℝ)

HIGH CORRELATION 

Distinct39
Distinct (%)9.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean127.07441
Minimum124.583
Maximum130.917
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size3.9 KiB
2024-03-13T21:53:01.823766image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum124.583
5-th percentile125.083
Q1125.75
median126.75
Q3128.25
95-th percentile129.917
Maximum130.917
Range6.334
Interquartile range (IQR)2.5

Descriptive statistics

Standard deviation1.5657707
Coefficient of variation (CV)0.012321684
Kurtosis-0.56476401
Mean127.07441
Median Absolute Deviation (MAD)1.167
Skewness0.61398145
Sum54641.996
Variance2.4516379
MonotonicityNot monotonic
2024-03-13T21:53:02.023416image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=39)
ValueCountFrequency (%)
125.917 27
 
6.3%
125.75 27
 
6.3%
125.583 27
 
6.3%
126.083 23
 
5.3%
126.25 19
 
4.4%
125.417 18
 
4.2%
125.25 18
 
4.2%
125.083 18
 
4.2%
126.917 17
 
4.0%
127.917 16
 
3.7%
Other values (29) 220
51.2%
ValueCountFrequency (%)
124.583 3
 
0.7%
124.75 3
 
0.7%
124.917 3
 
0.7%
125.083 18
4.2%
125.25 18
4.2%
125.417 18
4.2%
125.583 27
6.3%
125.75 27
6.3%
125.917 27
6.3%
126.083 23
5.3%
ValueCountFrequency (%)
130.917 6
1.4%
130.75 6
1.4%
130.583 6
1.4%
130.417 1
 
0.2%
130.25 1
 
0.2%
130.083 1
 
0.2%
129.917 2
 
0.5%
129.75 2
 
0.5%
129.583 2
 
0.5%
129.417 12
2.8%

CTOF_LA
Real number (ℝ)

Distinct24
Distinct (%)5.6%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean34.439144
Minimum32.583
Maximum36.417
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size3.9 KiB
2024-03-13T21:53:02.260509image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum32.583
5-th percentile33.083
Q133.583
median34.583
Q335.083
95-th percentile35.917
Maximum36.417
Range3.834
Interquartile range (IQR)1.5

Descriptive statistics

Standard deviation0.93788724
Coefficient of variation (CV)0.027233175
Kurtosis-0.88804052
Mean34.439144
Median Absolute Deviation (MAD)0.667
Skewness-0.059499496
Sum14808.832
Variance0.87963248
MonotonicityNot monotonic
2024-03-13T21:53:02.480897image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=24)
ValueCountFrequency (%)
34.75 54
12.6%
34.583 49
11.4%
34.917 34
 
7.9%
33.083 30
 
7.0%
33.25 30
 
7.0%
33.917 27
 
6.3%
33.75 24
 
5.6%
33.417 23
 
5.3%
35.25 21
 
4.9%
35.417 21
 
4.9%
Other values (14) 117
27.2%
ValueCountFrequency (%)
32.583 6
 
1.4%
32.75 6
 
1.4%
32.917 6
 
1.4%
33.083 30
7.0%
33.25 30
7.0%
33.417 23
5.3%
33.583 8
 
1.9%
33.75 24
5.6%
33.917 27
6.3%
34.083 6
 
1.4%
ValueCountFrequency (%)
36.417 6
 
1.4%
36.25 6
 
1.4%
36.083 6
 
1.4%
35.917 12
 
2.8%
35.75 12
 
2.8%
35.583 12
 
2.8%
35.417 21
4.9%
35.25 21
4.9%
35.083 21
4.9%
34.917 34
7.9%

CTOF_YMD
Categorical

HIGH CORRELATION 

Distinct4
Distinct (%)0.9%
Missing0
Missing (%)0.0%
Memory size3.5 KiB
20210828
119 
20210821
110 
20210807
109 
20210814
92 

Length

Max length8
Median length8
Mean length8
Min length8

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row20210807
2nd row20210807
3rd row20210807
4th row20210807
5th row20210807

Common Values

ValueCountFrequency (%)
20210828 119
27.7%
20210821 110
25.6%
20210807 109
25.3%
20210814 92
21.4%

Length

2024-03-13T21:53:02.668218image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-13T21:53:02.815319image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
20210828 119
27.7%
20210821 110
25.6%
20210807 109
25.3%
20210814 92
21.4%

SST
Real number (ℝ)

HIGH CORRELATION 

Distinct11
Distinct (%)2.6%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean25.944186
Minimum21
Maximum35
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size3.9 KiB
2024-03-13T21:53:02.959123image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum21
5-th percentile23
Q125
median26
Q327
95-th percentile28
Maximum35
Range14
Interquartile range (IQR)2

Descriptive statistics

Standard deviation2.1745832
Coefficient of variation (CV)0.083817748
Kurtosis7.7085149
Mean25.944186
Median Absolute Deviation (MAD)1
Skewness2.1229369
Sum11156
Variance4.7288123
MonotonicityNot monotonic
2024-03-13T21:53:03.109382image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=11)
ValueCountFrequency (%)
26 121
28.1%
25 106
24.7%
27 83
19.3%
24 43
 
10.0%
28 29
 
6.7%
23 21
 
4.9%
35 14
 
3.3%
22 10
 
2.3%
21 1
 
0.2%
29 1
 
0.2%
ValueCountFrequency (%)
21 1
 
0.2%
22 10
 
2.3%
23 21
 
4.9%
24 43
 
10.0%
25 106
24.7%
26 121
28.1%
27 83
19.3%
28 29
 
6.7%
29 1
 
0.2%
32 1
 
0.2%
ValueCountFrequency (%)
35 14
 
3.3%
32 1
 
0.2%
29 1
 
0.2%
28 29
 
6.7%
27 83
19.3%
26 121
28.1%
25 106
24.7%
24 43
 
10.0%
23 21
 
4.9%
22 10
 
2.3%

Interactions

2024-03-13T21:52:58.329587image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T21:52:51.868350image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T21:52:52.886340image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T21:52:53.922236image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T21:52:54.909538image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T21:52:56.013602image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T21:52:57.115443image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T21:52:58.488603image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T21:52:52.009167image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T21:52:53.059922image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T21:52:54.067888image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T21:52:55.039856image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T21:52:56.163989image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T21:52:57.274651image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T21:52:58.640693image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T21:52:52.138478image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T21:52:53.175447image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T21:52:54.202884image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T21:52:55.192609image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T21:52:56.346976image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T21:52:57.413545image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T21:52:59.215015image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T21:52:52.285003image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T21:52:53.341376image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T21:52:54.339274image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T21:52:55.381683image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T21:52:56.514313image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T21:52:57.634997image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T21:52:59.341429image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T21:52:52.414109image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T21:52:53.476734image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T21:52:54.457636image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T21:52:55.536755image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T21:52:56.645035image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T21:52:57.851707image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T21:52:59.475480image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T21:52:52.561982image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T21:52:53.627920image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T21:52:54.613763image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T21:52:55.675442image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T21:52:56.779844image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T21:52:58.018446image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T21:52:59.631968image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T21:52:52.719000image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T21:52:53.769765image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T21:52:54.756645image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T21:52:55.847344image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T21:52:56.957498image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T21:52:58.176432image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-03-13T21:53:03.256489image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
FSLSPS_CTSHNCHVY_FSATN_CTSHLGZ_NETBT_CTSHFSGN_CTSHFSASSN_SZN_CTSHCTOF_LOCTOF_LACTOF_YMDSST
FSLSPS_CTSH1.0000.3680.4640.7620.3540.7020.6720.5490.362
NCHVY_FSATN_CTSH0.3681.0000.0000.0000.7420.5710.2940.4600.290
LGZ_NETBT_CTSH0.4640.0001.0000.4910.0000.6670.5020.4330.301
FSGN_CTSH0.7620.0000.4911.0000.8840.4390.3930.3270.429
FSASSN_SZN_CTSH0.3540.7420.0000.8841.0000.4560.4220.2870.473
CTOF_LO0.7020.5710.6670.4390.4561.0000.7500.5170.465
CTOF_LA0.6720.2940.5020.3930.4220.7501.0000.5570.433
CTOF_YMD0.5490.4600.4330.3270.2870.5170.5571.0000.844
SST0.3620.2900.3010.4290.4730.4650.4330.8441.000
2024-03-13T21:53:03.426386image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
FSLSPS_CTSHCTOF_YMD
FSLSPS_CTSH1.0000.240
CTOF_YMD0.2401.000
2024-03-13T21:53:03.563995image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
NCHVY_FSATN_CTSHLGZ_NETBT_CTSHFSGN_CTSHFSASSN_SZN_CTSHCTOF_LOCTOF_LASSTFSLSPS_CTSHCTOF_YMD
NCHVY_FSATN_CTSH1.000-0.1500.0010.1800.3040.0740.0390.2440.312
LGZ_NETBT_CTSH-0.1501.0000.2280.0030.6580.194-0.0130.3150.292
FSGN_CTSH0.0010.2281.0000.6230.041-0.064-0.3420.6000.216
FSASSN_SZN_CTSH0.1800.0030.6231.0000.0650.001-0.1910.2350.188
CTOF_LO0.3040.6580.0410.0651.000-0.0760.0560.5000.333
CTOF_LA0.0740.194-0.0640.001-0.0761.000-0.1150.4700.365
SST0.039-0.013-0.342-0.1910.056-0.1151.0000.1600.519
FSLSPS_CTSH0.2440.3150.6000.2350.5000.4700.1601.0000.240
CTOF_YMD0.3120.2920.2160.1880.3330.3650.5190.2401.000

Missing values

2024-03-13T21:52:59.823882image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-03-13T21:53:00.081674image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Nullity matrix is a data-dense display which lets you quickly visually pick out patterns in data completion.

Sample

FSLSPS_CTSHNCHVY_FSATN_CTSHLGZ_NETBT_CTSHFSGN_CTSHFSASSN_SZN_CTSHCTOF_LOCTOF_LACTOF_YMDSST
02000000126.08333.0832021080727
12000000126.2533.0832021080727
22000000126.41733.0832021080727
31000000126.58333.0832021080727
41000000126.7533.0832021080727
51000000126.91733.0832021080727
62000000127.08333.0832021080727
72000000127.2533.0832021080728
82000000127.41733.0832021080727
91000000127.58333.0832021080727
FSLSPS_CTSHNCHVY_FSATN_CTSHLGZ_NETBT_CTSHFSGN_CTSHFSASSN_SZN_CTSHCTOF_LOCTOF_LACTOF_YMDSST
4201000000125.91735.9172021082824
4211000000125.58336.0832021082827
4221000000125.7536.0832021082832
4231000000125.91736.0832021082823
4241000000125.58336.252021082835
4251000000125.7536.252021082825
4261000000125.91736.252021082825
4271000000125.58336.4172021082828
4281000000125.7536.4172021082826
4291000000125.91736.4172021082823