Overview

Dataset statistics

Number of variables15
Number of observations10000
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory1.3 MiB
Average record size in memory140.0 B

Variable types

DateTime1
Categorical5
Numeric9

Dataset

Descriptiono (내용) 지사·출장소별 암검진 종목별 수검자 인원 수 o (대상) 당해연도 암검진 종별 중 하나라도 대상자인 건강보험가입자 및 의료급여수급권자 o (변수 레이아웃) 1 기준일자 2 사업년도 3 업무구분코드: 41 일반(암) 종목별 대상자, 42 일반(암) 종목별 수검자, A1 특정암 대상자, A3 특정암 수검자, A5 국가암 대상자, A7 국가암 수검자 4 지사코드(수검 당시 주소지 관할 지사) 5 소속구분코드(0: 지사, 1: 출장소1, 2: 출장소2, 3: 출장소3) 6 직역구분코드(E: 의료급여, G: 공교, J: 지역, K: 직장) 7 가입자구분코드(1: 지역세대주, 2: 지역세대원, 3: 비가입세대주, 4: 임의계속사업자, 5: 직장가입자, 6: 직장피부양자, 7: 의료급여세대주, 8: 의료급여세대원, 9: 임의계속피부양자) 0054 8 위암건수 9 대장암건수 10 유방암건수 11 간암상반기건수 12 자궁경부암건수 13 간암하반기건수 14 간암건수 15 폐암건수 o (자료제공범위) 조회일자 기준 최근 ‘1개월’ (2023년7월28일~2023년8월28일)
URLhttps://www.data.go.kr/data/15121853/fileData.do

Alerts

사업년도 has constant value ""Constant
위암건수 is highly overall correlated with 대장암건수 and 6 other fieldsHigh correlation
대장암건수 is highly overall correlated with 위암건수 and 6 other fieldsHigh correlation
유방암건수 is highly overall correlated with 위암건수 and 6 other fieldsHigh correlation
간암상반기건수 is highly overall correlated with 위암건수 and 6 other fieldsHigh correlation
자궁경부암건수 is highly overall correlated with 위암건수 and 6 other fieldsHigh correlation
간암하반기건수 is highly overall correlated with 위암건수 and 6 other fieldsHigh correlation
간암건수 is highly overall correlated with 위암건수 and 6 other fieldsHigh correlation
폐암건수 is highly overall correlated with 위암건수 and 6 other fieldsHigh correlation
직역구분코드 is highly overall correlated with 가입자구분코드High correlation
가입자구분코드 is highly overall correlated with 직역구분코드High correlation
위암건수 has 166 (1.7%) zerosZeros
대장암건수 has 192 (1.9%) zerosZeros
유방암건수 has 365 (3.6%) zerosZeros
간암상반기건수 has 907 (9.1%) zerosZeros
자궁경부암건수 has 305 (3.0%) zerosZeros
간암하반기건수 has 2861 (28.6%) zerosZeros
간암건수 has 898 (9.0%) zerosZeros
폐암건수 has 2194 (21.9%) zerosZeros

Reproduction

Analysis started2023-12-12 23:05:43.939855
Analysis finished2023-12-12 23:05:56.532528
Duration12.59 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

Distinct9
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
Minimum2023-07-28 00:00:00
Maximum2023-08-05 00:00:00
2023-12-13T08:05:56.578350image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T08:05:56.693412image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=9)

사업년도
Categorical

CONSTANT 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2023
10000 

Length

Max length4
Median length4
Mean length4
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2023
2nd row2023
3rd row2023
4th row2023
5th row2023

Common Values

ValueCountFrequency (%)
2023 10000
100.0%

Length

2023-12-13T08:05:56.844230image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T08:05:56.961643image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2023 10000
100.0%
Distinct6
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
41
1814 
A1
1792 
42
1716 
A3
1640 
A5
1545 

Length

Max length2
Median length2
Mean length2
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowA5
2nd row41
3rd rowA5
4th rowA1
5th rowA7

Common Values

ValueCountFrequency (%)
41 1814
18.1%
A1 1792
17.9%
42 1716
17.2%
A3 1640
16.4%
A5 1545
15.4%
A7 1493
14.9%

Length

2023-12-13T08:05:57.086505image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T08:05:57.194625image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
41 1814
18.1%
a1 1792
17.9%
42 1716
17.2%
a3 1640
16.4%
a5 1545
15.4%
a7 1493
14.9%

지사코드
Real number (ℝ)

Distinct178
Distinct (%)1.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean440.3111
Minimum101
Maximum802
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2023-12-13T08:05:57.329458image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum101
5-th percentile113
Q1242
median405
Q3662
95-th percentile759
Maximum802
Range701
Interquartile range (IQR)420

Descriptive statistics

Standard deviation218.83374
Coefficient of variation (CV)0.496998
Kurtosis-1.423544
Mean440.3111
Median Absolute Deviation (MAD)197
Skewness0.051998228
Sum4403111
Variance47888.204
MonotonicityNot monotonic
2023-12-13T08:05:57.497494image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
716 158
 
1.6%
765 138
 
1.4%
401 131
 
1.3%
606 129
 
1.3%
604 125
 
1.2%
704 125
 
1.2%
505 123
 
1.2%
405 114
 
1.1%
416 109
 
1.1%
503 103
 
1.0%
Other values (168) 8745
87.5%
ValueCountFrequency (%)
101 57
0.6%
103 33
0.3%
104 55
0.5%
105 39
0.4%
106 38
0.4%
107 55
0.5%
108 38
0.4%
109 43
0.4%
110 44
0.4%
111 51
0.5%
ValueCountFrequency (%)
802 43
 
0.4%
801 43
 
0.4%
771 91
0.9%
769 46
 
0.5%
767 42
 
0.4%
765 138
1.4%
762 84
0.8%
759 87
0.9%
757 51
 
0.5%
756 39
 
0.4%
Distinct3
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
0
7724 
1
1827 
2
 
449

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2
2nd row0
3rd row0
4th row0
5th row1

Common Values

ValueCountFrequency (%)
0 7724
77.2%
1 1827
 
18.3%
2 449
 
4.5%

Length

2023-12-13T08:05:57.637770image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T08:05:57.739670image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 7724
77.2%
1 1827
 
18.3%
2 449
 
4.5%

직역구분코드
Categorical

HIGH CORRELATION 

Distinct3
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
K
4971 
J
2522 
G
2507 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowK
2nd rowK
3rd rowK
4th rowG
5th rowJ

Common Values

ValueCountFrequency (%)
K 4971
49.7%
J 2522
25.2%
G 2507
25.1%

Length

2023-12-13T08:05:57.842118image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T08:05:57.950012image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
k 4971
49.7%
j 2522
25.2%
g 2507
25.1%

가입자구분코드
Categorical

HIGH CORRELATION 

Distinct4
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
5
2536 
2
2527 
6
2481 
1
2456 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row1
2nd row5
3rd row1
4th row6
5th row2

Common Values

ValueCountFrequency (%)
5 2536
25.4%
2 2527
25.3%
6 2481
24.8%
1 2456
24.6%

Length

2023-12-13T08:05:58.072902image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T08:05:58.198033image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
5 2536
25.4%
2 2527
25.3%
6 2481
24.8%
1 2456
24.6%

위암건수
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct4328
Distinct (%)43.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean3235.7059
Minimum0
Maximum112917
Zeros166
Zeros (%)1.7%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2023-12-13T08:05:58.343446image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile3
Q170
median693
Q33107.75
95-th percentile14743.55
Maximum112917
Range112917
Interquartile range (IQR)3037.75

Descriptive statistics

Standard deviation7239.4528
Coefficient of variation (CV)2.2373643
Kurtosis53.166771
Mean3235.7059
Median Absolute Deviation (MAD)684
Skewness5.8783507
Sum32357059
Variance52409677
MonotonicityNot monotonic
2023-12-13T08:05:58.499542image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 166
 
1.7%
1 164
 
1.6%
3 159
 
1.6%
2 134
 
1.3%
4 115
 
1.1%
5 97
 
1.0%
7 86
 
0.9%
6 75
 
0.8%
11 61
 
0.6%
8 61
 
0.6%
Other values (4318) 8882
88.8%
ValueCountFrequency (%)
0 166
1.7%
1 164
1.6%
2 134
1.3%
3 159
1.6%
4 115
1.1%
5 97
1.0%
6 75
0.8%
7 86
0.9%
8 61
 
0.6%
9 48
 
0.5%
ValueCountFrequency (%)
112917 1
< 0.1%
112733 1
< 0.1%
112370 1
< 0.1%
108817 1
< 0.1%
93942 2
< 0.1%
91928 1
< 0.1%
91068 1
< 0.1%
87136 2
< 0.1%
81837 1
< 0.1%
79984 1
< 0.1%

대장암건수
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct4333
Distinct (%)43.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean3801.6463
Minimum0
Maximum166885
Zeros192
Zeros (%)1.9%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2023-12-13T08:05:58.651354image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile2
Q147
median622.5
Q33160
95-th percentile18840.65
Maximum166885
Range166885
Interquartile range (IQR)3113

Descriptive statistics

Standard deviation9049.2994
Coefficient of variation (CV)2.3803633
Kurtosis54.965937
Mean3801.6463
Median Absolute Deviation (MAD)617.5
Skewness5.8975187
Sum38016463
Variance81889819
MonotonicityNot monotonic
2023-12-13T08:05:58.799120image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 238
 
2.4%
0 192
 
1.9%
2 180
 
1.8%
3 171
 
1.7%
4 153
 
1.5%
6 125
 
1.2%
5 113
 
1.1%
8 97
 
1.0%
7 69
 
0.7%
13 61
 
0.6%
Other values (4323) 8601
86.0%
ValueCountFrequency (%)
0 192
1.9%
1 238
2.4%
2 180
1.8%
3 171
1.7%
4 153
1.5%
5 113
1.1%
6 125
1.2%
7 69
 
0.7%
8 97
1.0%
9 49
 
0.5%
ValueCountFrequency (%)
166885 1
< 0.1%
142079 1
< 0.1%
130731 1
< 0.1%
130414 1
< 0.1%
130277 1
< 0.1%
125077 1
< 0.1%
116852 1
< 0.1%
107600 2
< 0.1%
96567 1
< 0.1%
96371 1
< 0.1%

유방암건수
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct3406
Distinct (%)34.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1655.9623
Minimum0
Maximum75237
Zeros365
Zeros (%)3.6%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2023-12-13T08:05:58.971314image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile1
Q140
median359.5
Q31624
95-th percentile7622.35
Maximum75237
Range75237
Interquartile range (IQR)1584

Descriptive statistics

Standard deviation3635.9252
Coefficient of variation (CV)2.195657
Kurtosis65.911616
Mean1655.9623
Median Absolute Deviation (MAD)355.5
Skewness6.1972047
Sum16559623
Variance13219952
MonotonicityNot monotonic
2023-12-13T08:05:59.139955image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 365
 
3.6%
1 246
 
2.5%
2 190
 
1.9%
3 163
 
1.6%
4 109
 
1.1%
7 104
 
1.0%
5 90
 
0.9%
6 73
 
0.7%
8 66
 
0.7%
11 65
 
0.7%
Other values (3396) 8529
85.3%
ValueCountFrequency (%)
0 365
3.6%
1 246
2.5%
2 190
1.9%
3 163
1.6%
4 109
 
1.1%
5 90
 
0.9%
6 73
 
0.7%
7 104
 
1.0%
8 66
 
0.7%
9 63
 
0.6%
ValueCountFrequency (%)
75237 1
< 0.1%
67263 1
< 0.1%
57918 1
< 0.1%
55836 1
< 0.1%
48687 1
< 0.1%
48685 1
< 0.1%
41192 1
< 0.1%
41174 1
< 0.1%
39200 1
< 0.1%
39156 1
< 0.1%

간암상반기건수
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct1326
Distinct (%)13.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean248.8937
Minimum0
Maximum8034
Zeros907
Zeros (%)9.1%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2023-12-13T08:05:59.322452image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q16
median58
Q3261
95-th percentile1123
Maximum8034
Range8034
Interquartile range (IQR)255

Descriptive statistics

Standard deviation515.07101
Coefficient of variation (CV)2.0694417
Kurtosis42.444568
Mean248.8937
Median Absolute Deviation (MAD)57
Skewness5.1686784
Sum2488937
Variance265298.14
MonotonicityNot monotonic
2023-12-13T08:05:59.784666image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 907
 
9.1%
1 505
 
5.1%
2 347
 
3.5%
3 223
 
2.2%
4 208
 
2.1%
6 182
 
1.8%
5 173
 
1.7%
7 125
 
1.2%
8 119
 
1.2%
9 106
 
1.1%
Other values (1316) 7105
71.0%
ValueCountFrequency (%)
0 907
9.1%
1 505
5.1%
2 347
 
3.5%
3 223
 
2.2%
4 208
 
2.1%
5 173
 
1.7%
6 182
 
1.8%
7 125
 
1.2%
8 119
 
1.2%
9 106
 
1.1%
ValueCountFrequency (%)
8034 1
< 0.1%
8022 1
< 0.1%
8017 1
< 0.1%
6721 1
< 0.1%
6257 2
< 0.1%
5984 1
< 0.1%
5827 2
< 0.1%
5656 1
< 0.1%
4927 1
< 0.1%
4918 2
< 0.1%

자궁경부암건수
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct3747
Distinct (%)37.5%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2227.6119
Minimum0
Maximum95055
Zeros305
Zeros (%)3.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2023-12-13T08:05:59.940955image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile1
Q155
median469
Q32062
95-th percentile10383.6
Maximum95055
Range95055
Interquartile range (IQR)2007

Descriptive statistics

Standard deviation5140.2516
Coefficient of variation (CV)2.3075167
Kurtosis58.632969
Mean2227.6119
Median Absolute Deviation (MAD)464
Skewness6.1911545
Sum22276119
Variance26422186
MonotonicityNot monotonic
2023-12-13T08:06:00.109365image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 305
 
3.0%
1 265
 
2.6%
2 177
 
1.8%
3 149
 
1.5%
4 128
 
1.3%
5 90
 
0.9%
6 73
 
0.7%
8 70
 
0.7%
7 69
 
0.7%
10 54
 
0.5%
Other values (3737) 8620
86.2%
ValueCountFrequency (%)
0 305
3.0%
1 265
2.6%
2 177
1.8%
3 149
1.5%
4 128
1.3%
5 90
 
0.9%
6 73
 
0.7%
7 69
 
0.7%
8 70
 
0.7%
9 50
 
0.5%
ValueCountFrequency (%)
95055 1
< 0.1%
85025 1
< 0.1%
73963 1
< 0.1%
70043 1
< 0.1%
64554 1
< 0.1%
64553 1
< 0.1%
64070 2
< 0.1%
55375 1
< 0.1%
55278 1
< 0.1%
55166 1
< 0.1%

간암하반기건수
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct1053
Distinct (%)10.5%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean153.3058
Minimum0
Maximum7922
Zeros2861
Zeros (%)28.6%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2023-12-13T08:06:00.254510image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median8
Q382
95-th percentile792.15
Maximum7922
Range7922
Interquartile range (IQR)82

Descriptive statistics

Standard deviation455.07065
Coefficient of variation (CV)2.9683851
Kurtosis66.765665
Mean153.3058
Median Absolute Deviation (MAD)8
Skewness6.7274813
Sum1533058
Variance207089.29
MonotonicityNot monotonic
2023-12-13T08:06:00.409321image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 2861
28.6%
1 751
 
7.5%
2 392
 
3.9%
3 289
 
2.9%
5 224
 
2.2%
4 210
 
2.1%
6 135
 
1.4%
9 130
 
1.3%
8 125
 
1.2%
7 123
 
1.2%
Other values (1043) 4760
47.6%
ValueCountFrequency (%)
0 2861
28.6%
1 751
 
7.5%
2 392
 
3.9%
3 289
 
2.9%
4 210
 
2.1%
5 224
 
2.2%
6 135
 
1.4%
7 123
 
1.2%
8 125
 
1.2%
9 130
 
1.3%
ValueCountFrequency (%)
7922 1
< 0.1%
7911 1
< 0.1%
7904 1
< 0.1%
6683 1
< 0.1%
6209 2
< 0.1%
5793 2
< 0.1%
5607 1
< 0.1%
5068 1
< 0.1%
4846 2
< 0.1%
4835 1
< 0.1%

간암건수
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct1342
Distinct (%)13.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean252.1826
Minimum0
Maximum8062
Zeros898
Zeros (%)9.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2023-12-13T08:06:00.552404image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q16
median60
Q3265.25
95-th percentile1142
Maximum8062
Range8062
Interquartile range (IQR)259.25

Descriptive statistics

Standard deviation519.8939
Coefficient of variation (CV)2.0615772
Kurtosis41.713867
Mean252.1826
Median Absolute Deviation (MAD)59
Skewness5.1263029
Sum2521826
Variance270289.67
MonotonicityNot monotonic
2023-12-13T08:06:00.729831image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 898
 
9.0%
1 499
 
5.0%
2 332
 
3.3%
3 240
 
2.4%
4 207
 
2.1%
6 171
 
1.7%
5 166
 
1.7%
7 132
 
1.3%
8 121
 
1.2%
9 99
 
1.0%
Other values (1332) 7135
71.4%
ValueCountFrequency (%)
0 898
9.0%
1 499
5.0%
2 332
 
3.3%
3 240
 
2.4%
4 207
 
2.1%
5 166
 
1.7%
6 171
 
1.7%
7 132
 
1.3%
8 121
 
1.2%
9 99
 
1.0%
ValueCountFrequency (%)
8062 1
< 0.1%
8050 1
< 0.1%
8046 1
< 0.1%
6758 1
< 0.1%
6282 2
< 0.1%
6024 1
< 0.1%
5851 2
< 0.1%
5687 1
< 0.1%
4957 1
< 0.1%
4935 2
< 0.1%

폐암건수
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct675
Distinct (%)6.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean72.1445
Minimum0
Maximum3715
Zeros2194
Zeros (%)21.9%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2023-12-13T08:06:00.881193image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q11
median9
Q354
95-th percentile374
Maximum3715
Range3715
Interquartile range (IQR)53

Descriptive statistics

Standard deviation183.35487
Coefficient of variation (CV)2.5414948
Kurtosis72.083544
Mean72.1445
Median Absolute Deviation (MAD)9
Skewness6.4171994
Sum721445
Variance33619.01
MonotonicityNot monotonic
2023-12-13T08:06:01.046983image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 2194
21.9%
1 849
 
8.5%
2 508
 
5.1%
3 295
 
2.9%
4 271
 
2.7%
5 211
 
2.1%
7 195
 
1.9%
6 194
 
1.9%
8 166
 
1.7%
10 166
 
1.7%
Other values (665) 4951
49.5%
ValueCountFrequency (%)
0 2194
21.9%
1 849
 
8.5%
2 508
 
5.1%
3 295
 
2.9%
4 271
 
2.7%
5 211
 
2.1%
6 194
 
1.9%
7 195
 
1.9%
8 166
 
1.7%
9 146
 
1.5%
ValueCountFrequency (%)
3715 1
< 0.1%
3697 1
< 0.1%
3696 1
< 0.1%
2623 1
< 0.1%
2218 1
< 0.1%
1959 1
< 0.1%
1945 1
< 0.1%
1933 1
< 0.1%
1881 1
< 0.1%
1880 2
< 0.1%

Interactions

2023-12-13T08:05:55.370617image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T08:05:46.269354image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T08:05:47.574016image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T08:05:48.671514image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T08:05:49.662894image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T08:05:50.703578image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T08:05:51.816765image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T08:05:52.878881image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T08:05:54.374630image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T08:05:55.472660image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T08:05:46.374224image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T08:05:47.679337image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T08:05:48.772813image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T08:05:49.801395image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T08:05:50.817437image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T08:05:51.925536image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T08:05:53.016725image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T08:05:54.480940image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T08:05:55.564089image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T08:05:46.466574image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T08:05:47.798208image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T08:05:48.891045image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T08:05:49.894964image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T08:05:50.948394image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T08:05:52.039418image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T08:05:53.123905image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T08:05:54.594096image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T08:05:55.673067image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T08:05:46.597565image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T08:05:47.922049image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T08:05:48.989849image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T08:05:50.031648image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T08:05:51.071430image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T08:05:52.164107image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T08:05:53.296540image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T08:05:54.712888image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T08:05:55.765781image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T08:05:46.712147image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T08:05:48.026980image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T08:05:49.102625image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T08:05:50.128855image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T08:05:51.178751image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T08:05:52.275503image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T08:05:53.414975image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T08:05:54.842369image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T08:05:55.860744image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T08:05:46.822803image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T08:05:48.122495image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T08:05:49.216975image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T08:05:50.254112image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T08:05:51.297593image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T08:05:52.403330image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T08:05:53.540776image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T08:05:54.966527image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T08:05:55.942248image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T08:05:46.910046image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T08:05:48.225917image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T08:05:49.327769image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T08:05:50.364720image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T08:05:51.409518image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T08:05:52.510373image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T08:05:53.674585image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T08:05:55.052532image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T08:05:56.037893image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T08:05:47.030647image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T08:05:48.346457image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T08:05:49.443737image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T08:05:50.483991image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T08:05:51.541329image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T08:05:52.658388image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T08:05:53.816171image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T08:05:55.152533image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T08:05:56.137449image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T08:05:47.458907image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T08:05:48.514152image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T08:05:49.542149image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T08:05:50.589823image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T08:05:51.675420image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T08:05:52.784663image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T08:05:53.945611image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T08:05:55.260210image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-13T08:06:01.205317image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
기준일자업무구분코드지사코드소속지사구분코드직역구분코드가입자구분코드위암건수대장암건수유방암건수간암상반기건수자궁경부암건수간암하반기건수간암건수폐암건수
기준일자1.0000.1770.0130.0270.0000.0000.0100.0000.0150.0000.0150.0220.0050.000
업무구분코드0.1771.0000.0360.0000.0000.0000.2330.2460.2140.1760.2110.2220.1770.209
지사코드0.0130.0361.0000.4500.0000.0000.2260.1990.2070.2190.2210.1590.2210.104
소속지사구분코드0.0270.0000.4501.0000.0580.0000.1670.1480.1340.1700.1390.1290.1730.127
직역구분코드0.0000.0000.0000.0581.0000.5020.2040.1820.1750.2210.1850.1790.2230.164
가입자구분코드0.0000.0000.0000.0000.5021.0000.1570.1400.1210.2290.1320.2020.2310.270
위암건수0.0100.2330.2260.1670.2040.1571.0000.9560.9070.9580.9200.9560.9550.829
대장암건수0.0000.2460.1990.1480.1820.1400.9561.0000.9770.9220.9730.9270.9220.799
유방암건수0.0150.2140.2070.1340.1750.1210.9070.9771.0000.8630.9900.8540.8620.619
간암상반기건수0.0000.1760.2190.1700.2210.2290.9580.9220.8631.0000.8730.9921.0000.876
자궁경부암건수0.0150.2110.2210.1390.1850.1320.9200.9730.9900.8731.0000.8650.8720.618
간암하반기건수0.0220.2220.1590.1290.1790.2020.9560.9270.8540.9920.8651.0000.9930.890
간암건수0.0050.1770.2210.1730.2230.2310.9550.9220.8621.0000.8720.9931.0000.876
폐암건수0.0000.2090.1040.1270.1640.2700.8290.7990.6190.8760.6180.8900.8761.000
2023-12-13T08:06:01.414354image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
직역구분코드가입자구분코드업무구분코드소속지사구분코드
직역구분코드1.0000.5010.0000.017
가입자구분코드0.5011.0000.0000.000
업무구분코드0.0000.0001.0000.000
소속지사구분코드0.0170.0000.0001.000
2023-12-13T08:06:01.556275image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
지사코드위암건수대장암건수유방암건수간암상반기건수자궁경부암건수간암하반기건수간암건수폐암건수업무구분코드소속지사구분코드직역구분코드가입자구분코드
지사코드1.000-0.194-0.171-0.203-0.188-0.218-0.095-0.188-0.1190.0190.3030.0000.000
위암건수-0.1941.0000.9880.9850.9830.9780.9070.9820.9510.1250.1000.1240.094
대장암건수-0.1710.9881.0000.9800.9560.9680.9280.9550.9500.1320.0890.1100.084
유방암건수-0.2030.9850.9801.0000.9610.9930.8900.9610.9130.1140.0800.1060.072
간암상반기건수-0.1880.9830.9560.9611.0000.9560.8651.0000.9390.0930.1020.1350.139
자궁경부암건수-0.2180.9780.9680.9930.9561.0000.8960.9550.8990.1130.0830.1120.079
간암하반기건수-0.0950.9070.9280.8900.8650.8961.0000.8640.8840.1180.0770.1080.122
간암건수-0.1880.9820.9550.9611.0000.9550.8641.0000.9380.0940.1040.1360.140
폐암건수-0.1190.9510.9500.9130.9390.8990.8840.9381.0000.1180.0810.1050.123
업무구분코드0.0190.1250.1320.1140.0930.1130.1180.0940.1181.0000.0000.0000.000
소속지사구분코드0.3030.1000.0890.0800.1020.0830.0770.1040.0810.0001.0000.0170.000
직역구분코드0.0000.1240.1100.1060.1350.1120.1080.1360.1050.0000.0171.0000.501
가입자구분코드0.0000.0940.0840.0720.1390.0790.1220.1400.1230.0000.0000.5011.000

Missing values

2023-12-13T08:05:56.269317image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-13T08:05:56.450305image/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

기준일자사업년도업무구분코드지사코드소속지사구분코드직역구분코드가입자구분코드위암건수대장암건수유방암건수간암상반기건수자궁경부암건수간암하반기건수간암건수폐암건수
194842023-07-292023A55052K150404000
337682023-07-312023413010K564944472972096042124345341754227775
412182023-07-312023A53110K11868110010
263192023-07-302023A12520G6339752412444169318715917026
662882023-08-022023A77541J2406284306623100624
497552023-08-012023A17651K100000000
126882023-07-292023417181J2173825321434123163110612311
703432023-08-032023A12010G6157525601103881456848915
7832023-07-282023413330K61124716792798158710698484589220
322462023-07-302023A74030G6118968112971132
기준일자사업년도업무구분코드지사코드소속지사구분코드직역구분코드가입자구분코드위암건수대장암건수유방암건수간암상반기건수자궁경부암건수간암하반기건수간암건수폐암건수
144222023-07-292023427040J21481132411251581344916613
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