Overview

Dataset statistics

Number of variables9
Number of observations26
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory2.2 KiB
Average record size in memory85.1 B

Variable types

Text1
Numeric8

Dataset

Description공무원 맞춤형복지 제휴신용카드(삼성카드) 이용 정보입니다. 성별(남녀), 연령(20대 이하부터 60대 이상) 및 업종별(교육, 미용, 의료 등) 이용비율을 나타내고 있습니다.
URLhttps://www.data.go.kr/data/3077138/fileData.do

Alerts

전체 is highly overall correlated with 성별(남성) and 6 other fieldsHigh correlation
성별(남성) is highly overall correlated with 전체 and 6 other fieldsHigh correlation
성별(여성) is highly overall correlated with 전체 and 6 other fieldsHigh correlation
연령(20대 이하) is highly overall correlated with 전체 and 6 other fieldsHigh correlation
연령(30대) is highly overall correlated with 전체 and 6 other fieldsHigh correlation
연령(40대) is highly overall correlated with 전체 and 6 other fieldsHigh correlation
연령(50대) is highly overall correlated with 전체 and 6 other fieldsHigh correlation
연령(60대 이상) is highly overall correlated with 전체 and 6 other fieldsHigh correlation
구분 has unique valuesUnique
전체 has 2 (7.7%) zerosZeros
성별(남성) has 2 (7.7%) zerosZeros
성별(여성) has 2 (7.7%) zerosZeros
연령(20대 이하) has 3 (11.5%) zerosZeros
연령(30대) has 2 (7.7%) zerosZeros
연령(40대) has 2 (7.7%) zerosZeros
연령(50대) has 2 (7.7%) zerosZeros
연령(60대 이상) has 2 (7.7%) zerosZeros

Reproduction

Analysis started2023-12-12 03:49:17.914448
Analysis finished2023-12-12 03:49:26.857361
Duration8.94 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

구분
Text

UNIQUE 

Distinct26
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size340.0 B
2023-12-12T12:49:27.056219image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length12
Median length10
Mean length5.5
Min length2

Characters and Unicode

Total characters143
Distinct characters85
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique26 ?
Unique (%)100.0%

Sample

1st row가구_인테리어
2nd row가전제품
3rd row가족식사
4th row건강식품
5th row결혼_장례서비스
ValueCountFrequency (%)
가구_인테리어 1
 
3.8%
가전제품 1
 
3.8%
통신비 1
 
3.8%
취미생활 1
 
3.8%
차량_차량연료(주유 1
 
3.8%
주류소비 1
 
3.8%
제조_도매업관리 1
 
3.8%
전자상거래(온라인쇼핑 1
 
3.8%
의류_잡화 1
 
3.8%
의료 1
 
3.8%
Other values (16) 16
61.5%
2023-12-12T12:49:27.628838image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
_ 12
 
8.4%
품 4
 
2.8%
비 4
 
2.8%
가 3
 
2.1%
서 3
 
2.1%
료 3
 
2.1%
) 3
 
2.1%
의 3
 
2.1%
활 3
 
2.1%
생 3
 
2.1%
Other values (75) 102
71.3%

Most occurring categories

ValueCountFrequency (%)
Other Letter 125
87.4%
Connector Punctuation 12
 
8.4%
Close Punctuation 3
 
2.1%
Open Punctuation 3
 
2.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
품 4
 
3.2%
비 4
 
3.2%
가 3
 
2.4%
서 3
 
2.4%
료 3
 
2.4%
의 3
 
2.4%
활 3
 
2.4%
생 3
 
2.4%
용 3
 
2.4%
스 3
 
2.4%
Other values (72) 93
74.4%
Connector Punctuation
ValueCountFrequency (%)
_ 12
100.0%
Close Punctuation
ValueCountFrequency (%)
) 3
100.0%
Open Punctuation
ValueCountFrequency (%)
( 3
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 125
87.4%
Common 18
 
12.6%

Most frequent character per script

Hangul
ValueCountFrequency (%)
품 4
 
3.2%
비 4
 
3.2%
가 3
 
2.4%
서 3
 
2.4%
료 3
 
2.4%
의 3
 
2.4%
활 3
 
2.4%
생 3
 
2.4%
용 3
 
2.4%
스 3
 
2.4%
Other values (72) 93
74.4%
Common
ValueCountFrequency (%)
_ 12
66.7%
) 3
 
16.7%
( 3
 
16.7%

Most occurring blocks

ValueCountFrequency (%)
Hangul 125
87.4%
ASCII 18
 
12.6%

Most frequent character per block

ASCII
ValueCountFrequency (%)
_ 12
66.7%
) 3
 
16.7%
( 3
 
16.7%
Hangul
ValueCountFrequency (%)
품 4
 
3.2%
비 4
 
3.2%
가 3
 
2.4%
서 3
 
2.4%
료 3
 
2.4%
의 3
 
2.4%
활 3
 
2.4%
생 3
 
2.4%
용 3
 
2.4%
스 3
 
2.4%
Other values (72) 93
74.4%

전체
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct21
Distinct (%)80.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.038576923
Minimum0
Maximum0.281
Zeros2
Zeros (%)7.7%
Negative0
Negative (%)0.0%
Memory size366.0 B
2023-12-12T12:49:27.819657image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0.00025
Q10.00525
median0.017
Q30.04775
95-th percentile0.12875
Maximum0.281
Range0.281
Interquartile range (IQR)0.0425

Descriptive statistics

Standard deviation0.060491436
Coefficient of variation (CV)1.5680731
Kurtosis10.254362
Mean0.038576923
Median Absolute Deviation (MAD)0.0135
Skewness2.9524872
Sum1.003
Variance0.0036592138
MonotonicityNot monotonic
2023-12-12T12:49:28.034167image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=21)
ValueCountFrequency (%)
0.0 2
 
7.7%
0.006 2
 
7.7%
0.002 2
 
7.7%
0.022 2
 
7.7%
0.005 2
 
7.7%
0.008 1
 
3.8%
0.01 1
 
3.8%
0.085 1
 
3.8%
0.14 1
 
3.8%
0.024 1
 
3.8%
Other values (11) 11
42.3%
ValueCountFrequency (%)
0.0 2
7.7%
0.001 1
3.8%
0.002 2
7.7%
0.005 2
7.7%
0.006 2
7.7%
0.008 1
3.8%
0.009 1
3.8%
0.01 1
3.8%
0.012 1
3.8%
0.022 2
7.7%
ValueCountFrequency (%)
0.281 1
3.8%
0.14 1
3.8%
0.095 1
3.8%
0.085 1
3.8%
0.07 1
3.8%
0.051 1
3.8%
0.049 1
3.8%
0.044 1
3.8%
0.028 1
3.8%
0.026 1
3.8%

성별(남성)
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct21
Distinct (%)80.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.038461538
Minimum0
Maximum0.214
Zeros2
Zeros (%)7.7%
Negative0
Negative (%)0.0%
Memory size366.0 B
2023-12-12T12:49:28.198864image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0.00025
Q10.00525
median0.0165
Q30.0575
95-th percentile0.12
Maximum0.214
Range0.214
Interquartile range (IQR)0.05225

Descriptive statistics

Standard deviation0.052050922
Coefficient of variation (CV)1.353324
Kurtosis4.0293836
Mean0.038461538
Median Absolute Deviation (MAD)0.014
Skewness1.9402725
Sum1
Variance0.0027092985
MonotonicityNot monotonic
2023-12-12T12:49:28.380092image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=21)
ValueCountFrequency (%)
0.006 3
 
11.5%
0.013 2
 
7.7%
0.0 2
 
7.7%
0.002 2
 
7.7%
0.008 1
 
3.8%
0.003 1
 
3.8%
0.024 1
 
3.8%
0.114 1
 
3.8%
0.122 1
 
3.8%
0.02 1
 
3.8%
Other values (11) 11
42.3%
ValueCountFrequency (%)
0.0 2
7.7%
0.001 1
 
3.8%
0.002 2
7.7%
0.003 1
 
3.8%
0.005 1
 
3.8%
0.006 3
11.5%
0.008 1
 
3.8%
0.013 2
7.7%
0.02 1
 
3.8%
0.021 1
 
3.8%
ValueCountFrequency (%)
0.214 1
3.8%
0.122 1
3.8%
0.114 1
3.8%
0.101 1
3.8%
0.085 1
3.8%
0.078 1
3.8%
0.062 1
3.8%
0.044 1
3.8%
0.027 1
3.8%
0.024 1
3.8%

성별(여성)
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct20
Distinct (%)76.9%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.038461538
Minimum0
Maximum0.349
Zeros2
Zeros (%)7.7%
Negative0
Negative (%)0.0%
Memory size366.0 B
2023-12-12T12:49:28.553282image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0.00025
Q10.006
median0.016
Q30.035
95-th percentile0.1405
Maximum0.349
Range0.349
Interquartile range (IQR)0.029

Descriptive statistics

Standard deviation0.072006239
Coefficient of variation (CV)1.8721622
Kurtosis14.631637
Mean0.038461538
Median Absolute Deviation (MAD)0.0125
Skewness3.628944
Sum1
Variance0.0051848985
MonotonicityNot monotonic
2023-12-12T12:49:28.714255image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=20)
ValueCountFrequency (%)
0.006 2
 
7.7%
0.001 2
 
7.7%
0.0 2
 
7.7%
0.035 2
 
7.7%
0.007 2
 
7.7%
0.02 2
 
7.7%
0.008 1
 
3.8%
0.011 1
 
3.8%
0.056 1
 
3.8%
0.158 1
 
3.8%
Other values (10) 10
38.5%
ValueCountFrequency (%)
0.0 2
7.7%
0.001 2
7.7%
0.003 1
3.8%
0.005 1
3.8%
0.006 2
7.7%
0.007 2
7.7%
0.008 1
3.8%
0.011 1
3.8%
0.012 1
3.8%
0.02 2
7.7%
ValueCountFrequency (%)
0.349 1
3.8%
0.158 1
3.8%
0.088 1
3.8%
0.056 1
3.8%
0.054 1
3.8%
0.043 1
3.8%
0.035 2
7.7%
0.028 1
3.8%
0.024 1
3.8%
0.023 1
3.8%

연령(20대 이하)
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct20
Distinct (%)76.9%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.038423077
Minimum0
Maximum0.377
Zeros3
Zeros (%)11.5%
Negative0
Negative (%)0.0%
Memory size366.0 B
2023-12-12T12:49:28.903666image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10.00525
median0.0105
Q30.03875
95-th percentile0.09625
Maximum0.377
Range0.377
Interquartile range (IQR)0.0335

Descriptive statistics

Standard deviation0.075033951
Coefficient of variation (CV)1.9528356
Kurtosis17.767286
Mean0.038423077
Median Absolute Deviation (MAD)0.0105
Skewness3.9748616
Sum0.999
Variance0.0056300938
MonotonicityNot monotonic
2023-12-12T12:49:29.048370image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=20)
ValueCountFrequency (%)
0.0 3
 
11.5%
0.006 3
 
11.5%
0.005 2
 
7.7%
0.008 2
 
7.7%
0.044 1
 
3.8%
0.001 1
 
3.8%
0.029 1
 
3.8%
0.094 1
 
3.8%
0.097 1
 
3.8%
0.028 1
 
3.8%
Other values (10) 10
38.5%
ValueCountFrequency (%)
0.0 3
11.5%
0.001 1
 
3.8%
0.002 1
 
3.8%
0.005 2
7.7%
0.006 3
11.5%
0.008 2
7.7%
0.01 1
 
3.8%
0.011 1
 
3.8%
0.016 1
 
3.8%
0.027 1
 
3.8%
ValueCountFrequency (%)
0.377 1
3.8%
0.097 1
3.8%
0.094 1
3.8%
0.088 1
3.8%
0.056 1
3.8%
0.044 1
3.8%
0.04 1
3.8%
0.035 1
3.8%
0.029 1
3.8%
0.028 1
3.8%

연령(30대)
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct21
Distinct (%)80.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.038461538
Minimum0
Maximum0.383
Zeros2
Zeros (%)7.7%
Negative0
Negative (%)0.0%
Memory size366.0 B
2023-12-12T12:49:29.225012image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0.00025
Q10.006
median0.012
Q30.03225
95-th percentile0.145
Maximum0.383
Range0.383
Interquartile range (IQR)0.02625

Descriptive statistics

Standard deviation0.078593756
Coefficient of variation (CV)2.0434377
Kurtosis15.827299
Mean0.038461538
Median Absolute Deviation (MAD)0.01
Skewness3.8135937
Sum1
Variance0.0061769785
MonotonicityNot monotonic
2023-12-12T12:49:29.405700image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=21)
ValueCountFrequency (%)
0.006 3
 
11.5%
0.0 2
 
7.7%
0.009 2
 
7.7%
0.022 2
 
7.7%
0.005 1
 
3.8%
0.007 1
 
3.8%
0.019 1
 
3.8%
0.067 1
 
3.8%
0.002 1
 
3.8%
0.171 1
 
3.8%
Other values (11) 11
42.3%
ValueCountFrequency (%)
0.0 2
7.7%
0.001 1
 
3.8%
0.002 1
 
3.8%
0.003 1
 
3.8%
0.005 1
 
3.8%
0.006 3
11.5%
0.007 1
 
3.8%
0.008 1
 
3.8%
0.009 2
7.7%
0.015 1
 
3.8%
ValueCountFrequency (%)
0.383 1
3.8%
0.171 1
3.8%
0.067 1
3.8%
0.062 1
3.8%
0.052 1
3.8%
0.035 1
3.8%
0.033 1
3.8%
0.03 1
3.8%
0.027 1
3.8%
0.022 2
7.7%

연령(40대)
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct21
Distinct (%)80.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.038461538
Minimum0
Maximum0.34
Zeros2
Zeros (%)7.7%
Negative0
Negative (%)0.0%
Memory size366.0 B
2023-12-12T12:49:29.576278image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0.00025
Q10.006
median0.013
Q30.038
95-th percentile0.13875
Maximum0.34
Range0.34
Interquartile range (IQR)0.032

Descriptive statistics

Standard deviation0.07064799
Coefficient of variation (CV)1.8368477
Kurtosis13.974065
Mean0.038461538
Median Absolute Deviation (MAD)0.011
Skewness3.5349069
Sum1
Variance0.0049911385
MonotonicityNot monotonic
2023-12-12T12:49:29.755760image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=21)
ValueCountFrequency (%)
0.006 3
 
11.5%
0.0 2
 
7.7%
0.032 2
 
7.7%
0.002 2
 
7.7%
0.01 1
 
3.8%
0.008 1
 
3.8%
0.02 1
 
3.8%
0.069 1
 
3.8%
0.16 1
 
3.8%
0.023 1
 
3.8%
Other values (11) 11
42.3%
ValueCountFrequency (%)
0.0 2
7.7%
0.001 1
 
3.8%
0.002 2
7.7%
0.005 1
 
3.8%
0.006 3
11.5%
0.007 1
 
3.8%
0.008 1
 
3.8%
0.009 1
 
3.8%
0.01 1
 
3.8%
0.016 1
 
3.8%
ValueCountFrequency (%)
0.34 1
3.8%
0.16 1
3.8%
0.075 1
3.8%
0.069 1
3.8%
0.06 1
3.8%
0.047 1
3.8%
0.04 1
3.8%
0.032 2
7.7%
0.024 1
3.8%
0.023 1
3.8%

연령(50대)
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct23
Distinct (%)88.5%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.038461538
Minimum0
Maximum0.262
Zeros2
Zeros (%)7.7%
Negative0
Negative (%)0.0%
Memory size366.0 B
2023-12-12T12:49:29.932007image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0.00025
Q10.0055
median0.0185
Q30.047
95-th percentile0.12325
Maximum0.262
Range0.262
Interquartile range (IQR)0.0415

Descriptive statistics

Standard deviation0.057023666
Coefficient of variation (CV)1.4826153
Kurtosis9.1670548
Mean0.038461538
Median Absolute Deviation (MAD)0.016
Skewness2.7727672
Sum1
Variance0.0032516985
MonotonicityNot monotonic
2023-12-12T12:49:30.081259image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=23)
ValueCountFrequency (%)
0.0 2
 
7.7%
0.007 2
 
7.7%
0.002 2
 
7.7%
0.009 1
 
3.8%
0.012 1
 
3.8%
0.003 1
 
3.8%
0.026 1
 
3.8%
0.094 1
 
3.8%
0.133 1
 
3.8%
0.027 1
 
3.8%
Other values (13) 13
50.0%
ValueCountFrequency (%)
0.0 2
7.7%
0.001 1
3.8%
0.002 2
7.7%
0.003 1
3.8%
0.005 1
3.8%
0.007 2
7.7%
0.009 1
3.8%
0.01 1
3.8%
0.012 1
3.8%
0.014 1
3.8%
ValueCountFrequency (%)
0.262 1
3.8%
0.133 1
3.8%
0.094 1
3.8%
0.088 1
3.8%
0.076 1
3.8%
0.052 1
3.8%
0.048 1
3.8%
0.044 1
3.8%
0.03 1
3.8%
0.027 1
3.8%

연령(60대 이상)
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct22
Distinct (%)84.6%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.038538462
Minimum0
Maximum0.193
Zeros2
Zeros (%)7.7%
Negative0
Negative (%)0.0%
Memory size366.0 B
2023-12-12T12:49:30.227715image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0.00025
Q10.00425
median0.013
Q30.06675
95-th percentile0.1325
Maximum0.193
Range0.193
Interquartile range (IQR)0.0625

Descriptive statistics

Standard deviation0.051493091
Coefficient of variation (CV)1.3361481
Kurtosis2.0277768
Mean0.038538462
Median Absolute Deviation (MAD)0.0115
Skewness1.605242
Sum1.002
Variance0.0026515385
MonotonicityNot monotonic
2023-12-12T12:49:30.397573image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=22)
ValueCountFrequency (%)
0.0 2
 
7.7%
0.005 2
 
7.7%
0.001 2
 
7.7%
0.022 2
 
7.7%
0.011 1
 
3.8%
0.012 1
 
3.8%
0.02 1
 
3.8%
0.006 1
 
3.8%
0.102 1
 
3.8%
0.113 1
 
3.8%
Other values (12) 12
46.2%
ValueCountFrequency (%)
0.0 2
7.7%
0.001 2
7.7%
0.002 1
3.8%
0.003 1
3.8%
0.004 1
3.8%
0.005 2
7.7%
0.006 1
3.8%
0.007 1
3.8%
0.011 1
3.8%
0.012 1
3.8%
ValueCountFrequency (%)
0.193 1
3.8%
0.139 1
3.8%
0.113 1
3.8%
0.102 1
3.8%
0.092 1
3.8%
0.079 1
3.8%
0.072 1
3.8%
0.051 1
3.8%
0.026 1
3.8%
0.022 2
7.7%

Interactions

2023-12-12T12:49:25.168434image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T12:49:18.155573image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T12:49:19.081303image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T12:49:19.782859image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T12:49:20.789589image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T12:49:21.747083image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T12:49:22.873610image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T12:49:23.954960image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T12:49:25.304392image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T12:49:18.222531image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T12:49:19.180659image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T12:49:19.862712image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T12:49:20.883573image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T12:49:21.879861image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T12:49:22.997787image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T12:49:24.082706image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T12:49:25.455387image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T12:49:18.288142image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T12:49:19.269812image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T12:49:19.954917image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T12:49:20.998731image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T12:49:22.014312image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T12:49:23.103766image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T12:49:24.220802image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T12:49:25.597253image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T12:49:18.641672image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T12:49:19.343878image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T12:49:20.050727image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T12:49:21.111563image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T12:49:22.150860image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T12:49:23.270778image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T12:49:24.386652image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T12:49:26.067029image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T12:49:18.716696image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T12:49:19.421595image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T12:49:20.147139image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T12:49:21.222736image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T12:49:22.292306image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T12:49:23.403619image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T12:49:24.563853image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T12:49:26.194679image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T12:49:18.800552image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T12:49:19.504995image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T12:49:20.332277image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T12:49:21.356652image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T12:49:22.444911image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T12:49:23.552426image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T12:49:24.718652image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T12:49:26.334440image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T12:49:18.885050image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T12:49:19.608383image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T12:49:20.482500image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T12:49:21.480928image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T12:49:22.583345image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T12:49:23.694943image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T12:49:24.869416image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T12:49:26.449109image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T12:49:18.970217image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T12:49:19.693920image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T12:49:20.607435image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T12:49:21.614047image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T12:49:22.726572image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T12:49:23.816879image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T12:49:25.002786image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-12T12:49:30.558629image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
구분전체성별(남성)성별(여성)연령(20대 이하)연령(30대)연령(40대)연령(50대)연령(60대 이상)
구분1.0001.0001.0001.0001.0001.0001.0001.0001.000
전체1.0001.0000.8990.8920.8971.0000.9310.9980.904
성별(남성)1.0000.8991.0000.8900.8950.8620.8240.8650.983
성별(여성)1.0000.8920.8901.0000.7960.9020.9920.8770.895
연령(20대 이하)1.0000.8970.8950.7961.0000.9670.7790.9270.993
연령(30대)1.0001.0000.8620.9020.9671.0000.9321.0000.973
연령(40대)1.0000.9310.8240.9920.7790.9321.0000.9260.854
연령(50대)1.0000.9980.8650.8770.9271.0000.9261.0000.885
연령(60대 이상)1.0000.9040.9830.8950.9930.9730.8540.8851.000
2023-12-12T12:49:30.742351image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
전체성별(남성)성별(여성)연령(20대 이하)연령(30대)연령(40대)연령(50대)연령(60대 이상)
전체1.0000.9890.9820.9050.9520.9830.9940.954
성별(남성)0.9891.0000.9620.9140.9360.9610.9920.968
성별(여성)0.9820.9621.0000.9270.9760.9850.9770.921
연령(20대 이하)0.9050.9140.9271.0000.9330.9000.9230.889
연령(30대)0.9520.9360.9760.9331.0000.9740.9480.879
연령(40대)0.9830.9610.9850.9000.9741.0000.9710.901
연령(50대)0.9940.9920.9770.9230.9480.9711.0000.966
연령(60대 이상)0.9540.9680.9210.8890.8790.9010.9661.000

Missing values

2023-12-12T12:49:26.608085image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-12T12:49:26.778103image/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

구분전체성별(남성)성별(여성)연령(20대 이하)연령(30대)연령(40대)연령(50대)연령(60대 이상)
0가구_인테리어0.0080.0080.0080.0050.0060.0060.0090.011
1가전제품0.0220.0230.020.0350.0220.0160.0230.026
2가족식사0.070.0850.0540.0880.0520.060.0760.079
3건강식품0.0010.0010.0010.00.0010.0010.0010.003
4결혼_장례서비스0.00.00.00.00.00.00.00.0
5교육0.0280.0210.0350.010.0330.0470.0250.005
6기타0.0510.0780.0230.0080.0150.0320.0480.092
7레저_스포츠0.0060.0060.0070.0110.0060.0060.0070.005
8미용0.0090.0060.0120.0160.0090.0090.010.007
9보험_금융0.0490.0620.0350.0270.030.0320.0520.072
구분전체성별(남성)성별(여성)연령(20대 이하)연령(30대)연령(40대)연령(50대)연령(60대 이상)
16음료_식품0.0440.0440.0430.040.0350.040.0440.051
17의료0.0950.1010.0880.0560.0620.0750.0880.139
18의류_잡화0.0240.020.0280.0280.0220.0230.0270.022
19전자상거래(온라인쇼핑)0.140.1220.1580.0970.1710.160.1330.113
20제조_도매업관리0.00.00.00.00.00.00.00.0
21주류소비0.0020.0020.0010.0050.0020.0020.0020.001
22차량_차량연료(주유)0.0850.1140.0560.0940.0670.0690.0940.102
23취미생활0.0060.0060.0060.0060.0060.0060.0070.006
24통신비0.0220.0240.020.0290.0190.020.0260.02
25학습자재_도서구매0.0050.0030.0060.0010.0070.0080.0030.001