Overview

Dataset statistics

Number of variables17
Number of observations30
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory4.5 KiB
Average record size in memory152.4 B

Variable types

DateTime1
Numeric11
Categorical3
Text2

Dataset

Description샘플 데이터
Author경기콘텐츠진흥원
URLhttps://bigdata-region.kr/#/dataset/11d7eb59-07c3-4400-9d52-0a2aa7b55d36

Alerts

기준년월 has constant value ""Constant
남자 10대 이하 금액 has constant value ""Constant
남자 20대 금액 is highly overall correlated with 남자 30대 금액 and 7 other fieldsHigh correlation
남자 30대 금액 is highly overall correlated with 남자 20대 금액 and 5 other fieldsHigh correlation
남자 40대 금액 is highly overall correlated with 남자 20대 금액 and 6 other fieldsHigh correlation
남자 50대 금액 is highly overall correlated with 남자 20대 금액 and 6 other fieldsHigh correlation
여자 20대 금액 is highly overall correlated with 남자 20대 금액 and 7 other fieldsHigh correlation
여자 30대 금액 is highly overall correlated with 남자 20대 금액 and 6 other fieldsHigh correlation
여자 40대 금액 is highly overall correlated with 남자 20대 금액 and 7 other fieldsHigh correlation
여자 50대 금액 is highly overall correlated with 여자 20대 금액 and 1 other fieldsHigh correlation
여자 60대 이하 is highly overall correlated with 남자 20대 금액 and 3 other fieldsHigh correlation
여자 10대 이하 금액 is highly overall correlated with 남자 20대 금액 and 6 other fieldsHigh correlation
여자 10대 이하 금액 is highly imbalanced (78.9%)Imbalance
남자 20대 금액 has 12 (40.0%) zerosZeros
남자 30대 금액 has 5 (16.7%) zerosZeros
남자 40대 금액 has 7 (23.3%) zerosZeros
남자 50대 금액 has 10 (33.3%) zerosZeros
남자 60대 이하 금액 has 17 (56.7%) zerosZeros
여자 20대 금액 has 8 (26.7%) zerosZeros
여자 30대 금액 has 9 (30.0%) zerosZeros
여자 40대 금액 has 13 (43.3%) zerosZeros
여자 50대 금액 has 14 (46.7%) zerosZeros
여자 60대 이하 has 23 (76.7%) zerosZeros

Reproduction

Analysis started2023-12-10 14:17:01.885061
Analysis finished2023-12-10 14:17:23.012151
Duration21.13 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

기준년월
Date

CONSTANT 

Distinct1
Distinct (%)3.3%
Missing0
Missing (%)0.0%
Memory size372.0 B
Minimum2019-01-01 00:00:00
Maximum2019-01-01 00:00:00
2023-12-10T23:17:23.077382image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T23:17:23.223813image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=1)

블록 ID
Real number (ℝ)

Distinct7
Distinct (%)23.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean3.105051 × 1019
Minimum3.105051 × 1019
Maximum3.105051 × 1019
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size402.0 B
2023-12-10T23:17:23.362398image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum3.105051 × 1019
5-th percentile3.105051 × 1019
Q13.105051 × 1019
median3.105051 × 1019
Q33.105051 × 1019
95-th percentile3.105051 × 1019
Maximum3.105051 × 1019
Range70000640
Interquartile range (IQR)49999872

Descriptive statistics

Standard deviation27258006
Coefficient of variation (CV)8.7786015 × 10-13
Kurtosis-1.4867519
Mean3.105051 × 1019
Median Absolute Deviation (MAD)10002432
Skewness-0.54249066
Sum9.315153 × 1020
Variance7.4299887 × 1014
MonotonicityNot monotonic
2023-12-10T23:17:23.551561image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=7)
ValueCountFrequency (%)
3.10505101001e+19 12
40.0%
3.105051010005e+19 5
16.7%
3.105051010009e+19 5
16.7%
3.105051010003e+19 3
 
10.0%
3.105051010004e+19 3
 
10.0%
3.105051010007e+19 1
 
3.3%
3.105051010008e+19 1
 
3.3%
ValueCountFrequency (%)
3.105051010003e+19 3
 
10.0%
3.105051010004e+19 3
 
10.0%
3.105051010005e+19 5
16.7%
3.105051010007e+19 1
 
3.3%
3.105051010008e+19 1
 
3.3%
3.105051010009e+19 5
16.7%
3.10505101001e+19 12
40.0%
ValueCountFrequency (%)
3.10505101001e+19 12
40.0%
3.105051010009e+19 5
16.7%
3.105051010008e+19 1
 
3.3%
3.105051010007e+19 1
 
3.3%
3.105051010005e+19 5
16.7%
3.105051010004e+19 3
 
10.0%
3.105051010003e+19 3
 
10.0%

대분류
Categorical

Distinct5
Distinct (%)16.7%
Missing0
Missing (%)0.0%
Memory size372.0 B
음식
14 
소매
8 
관광/여가/오락
5 
숙박
2 
생활서비스
 
1

Length

Max length8
Median length2
Mean length3.1
Min length2

Unique

Unique1 ?
Unique (%)3.3%

Sample

1st row음식
2nd row소매
3rd row음식
4th row음식
5th row관광/여가/오락

Common Values

ValueCountFrequency (%)
음식 14
46.7%
소매 8
26.7%
관광/여가/오락 5
 
16.7%
숙박 2
 
6.7%
생활서비스 1
 
3.3%

Length

2023-12-10T23:17:23.722445image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T23:17:23.860147image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
음식 14
46.7%
소매 8
26.7%
관광/여가/오락 5
 
16.7%
숙박 2
 
6.7%
생활서비스 1
 
3.3%

중분류
Text

Distinct17
Distinct (%)56.7%
Missing0
Missing (%)0.0%
Memory size372.0 B
2023-12-10T23:17:24.026393image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length12
Median length9
Mean length5.3333333
Min length2

Characters and Unicode

Total characters160
Distinct characters64
Distinct categories3 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique10 ?
Unique (%)33.3%

Sample

1st row다방/커피숍/카페
2nd row의복
3rd row중식
4th row양식
5th row무도/유흥/가무
ValueCountFrequency (%)
한식 6
20.0%
무도/유흥/가무 3
10.0%
의복 3
10.0%
pc/오락/당구/볼링등 2
 
6.7%
양식 2
 
6.7%
모텔/여관/여인숙 2
 
6.7%
별식/퓨전요리 2
 
6.7%
일식 1
 
3.3%
다방/커피숍/카페 1
 
3.3%
화장품소매 1
 
3.3%
Other values (7) 7
23.3%
2023-12-10T23:17:24.379425image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
/ 26
 
16.2%
식 12
 
7.5%
한 6
 
3.8%
무 6
 
3.8%
의 5
 
3.1%
매 4
 
2.5%
여 4
 
2.5%
소 4
 
2.5%
관 3
 
1.9%
락 3
 
1.9%
Other values (54) 87
54.4%

Most occurring categories

ValueCountFrequency (%)
Other Letter 130
81.2%
Other Punctuation 26
 
16.2%
Uppercase Letter 4
 
2.5%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
식 12
 
9.2%
한 6
 
4.6%
무 6
 
4.6%
의 5
 
3.8%
매 4
 
3.1%
여 4
 
3.1%
소 4
 
3.1%
관 3
 
2.3%
락 3
 
2.3%
오 3
 
2.3%
Other values (51) 80
61.5%
Uppercase Letter
ValueCountFrequency (%)
P 2
50.0%
C 2
50.0%
Other Punctuation
ValueCountFrequency (%)
/ 26
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 130
81.2%
Common 26
 
16.2%
Latin 4
 
2.5%

Most frequent character per script

Hangul
ValueCountFrequency (%)
식 12
 
9.2%
한 6
 
4.6%
무 6
 
4.6%
의 5
 
3.8%
매 4
 
3.1%
여 4
 
3.1%
소 4
 
3.1%
관 3
 
2.3%
락 3
 
2.3%
오 3
 
2.3%
Other values (51) 80
61.5%
Latin
ValueCountFrequency (%)
P 2
50.0%
C 2
50.0%
Common
ValueCountFrequency (%)
/ 26
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 130
81.2%
ASCII 30
 
18.8%

Most frequent character per block

ASCII
ValueCountFrequency (%)
/ 26
86.7%
P 2
 
6.7%
C 2
 
6.7%
Hangul
ValueCountFrequency (%)
식 12
 
9.2%
한 6
 
4.6%
무 6
 
4.6%
의 5
 
3.8%
매 4
 
3.1%
여 4
 
3.1%
소 4
 
3.1%
관 3
 
2.3%
락 3
 
2.3%
오 3
 
2.3%
Other values (51) 80
61.5%

소분류
Text

Distinct27
Distinct (%)90.0%
Missing0
Missing (%)0.0%
Memory size372.0 B
2023-12-10T23:17:24.598657image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length10
Median length8
Mean length6.2666667
Min length2

Characters and Unicode

Total characters188
Distinct characters84
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

Unique25 ?
Unique (%)83.3%

Sample

1st row커피전문점
2nd row의류 판매-남성전문
3rd row중국음식/중국집
4th row돈가스 전문점
5th row노래방
ValueCountFrequency (%)
전문점 10
20.4%
판매 5
 
10.2%
노래방 3
 
6.1%
당구장 2
 
4.1%
의류 2
 
4.1%
네일케어 1
 
2.0%
전문 1
 
2.0%
화장품 1
 
2.0%
삼겹살 1
 
2.0%
닭갈비 1
 
2.0%
Other values (22) 22
44.9%
2023-12-10T23:17:24.978132image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
19
 
10.1%
전 13
 
6.9%
문 13
 
6.9%
점 12
 
6.4%
매 7
 
3.7%
판 7
 
3.7%
/ 6
 
3.2%
기 4
 
2.1%
장 4
 
2.1%
리 3
 
1.6%
Other values (74) 100
53.2%

Most occurring categories

ValueCountFrequency (%)
Other Letter 161
85.6%
Space Separator 19
 
10.1%
Other Punctuation 6
 
3.2%
Dash Punctuation 2
 
1.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
전 13
 
8.1%
문 13
 
8.1%
점 12
 
7.5%
매 7
 
4.3%
판 7
 
4.3%
기 4
 
2.5%
장 4
 
2.5%
리 3
 
1.9%
요 3
 
1.9%
래 3
 
1.9%
Other values (71) 92
57.1%
Space Separator
ValueCountFrequency (%)
19
100.0%
Other Punctuation
ValueCountFrequency (%)
/ 6
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 161
85.6%
Common 27
 
14.4%

Most frequent character per script

Hangul
ValueCountFrequency (%)
전 13
 
8.1%
문 13
 
8.1%
점 12
 
7.5%
매 7
 
4.3%
판 7
 
4.3%
기 4
 
2.5%
장 4
 
2.5%
리 3
 
1.9%
요 3
 
1.9%
래 3
 
1.9%
Other values (71) 92
57.1%
Common
ValueCountFrequency (%)
19
70.4%
/ 6
 
22.2%
- 2
 
7.4%

Most occurring blocks

ValueCountFrequency (%)
Hangul 161
85.6%
ASCII 27
 
14.4%

Most frequent character per block

ASCII
ValueCountFrequency (%)
19
70.4%
/ 6
 
22.2%
- 2
 
7.4%
Hangul
ValueCountFrequency (%)
전 13
 
8.1%
문 13
 
8.1%
점 12
 
7.5%
매 7
 
4.3%
판 7
 
4.3%
기 4
 
2.5%
장 4
 
2.5%
리 3
 
1.9%
요 3
 
1.9%
래 3
 
1.9%
Other values (71) 92
57.1%

남자 10대 이하 금액
Categorical

CONSTANT 

Distinct1
Distinct (%)3.3%
Missing0
Missing (%)0.0%
Memory size372.0 B
0
30 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
0 30
100.0%

Length

2023-12-10T23:17:25.178688image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T23:17:25.289118image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 30
100.0%

남자 20대 금액
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct19
Distinct (%)63.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean61767.586
Minimum0
Maximum485119.12
Zeros12
Zeros (%)40.0%
Negative0
Negative (%)0.0%
Memory size402.0 B
2023-12-10T23:17:25.406285image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median5271.51
Q371783.475
95-th percentile238496.49
Maximum485119.12
Range485119.12
Interquartile range (IQR)71783.475

Descriptive statistics

Standard deviation108684.43
Coefficient of variation (CV)1.7595706
Kurtosis7.3308667
Mean61767.586
Median Absolute Deviation (MAD)5271.51
Skewness2.5336824
Sum1853027.6
Variance1.1812305 × 1010
MonotonicityNot monotonic
2023-12-10T23:17:25.542868image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=19)
ValueCountFrequency (%)
0.0 12
40.0%
485119.12 1
 
3.3%
54051.05 1
 
3.3%
18189.75 1
 
3.3%
5167.79 1
 
3.3%
180712.87 1
 
3.3%
200137.27 1
 
3.3%
17380.42 1
 
3.3%
28271.97 1
 
3.3%
2126.56 1
 
3.3%
Other values (9) 9
30.0%
ValueCountFrequency (%)
0.0 12
40.0%
2126.56 1
 
3.3%
4065.87 1
 
3.3%
5167.79 1
 
3.3%
5375.23 1
 
3.3%
17380.42 1
 
3.3%
18189.75 1
 
3.3%
28271.97 1
 
3.3%
46317.7 1
 
3.3%
54051.05 1
 
3.3%
ValueCountFrequency (%)
485119.12 1
3.3%
266300.02 1
3.3%
204514.39 1
3.3%
200137.27 1
3.3%
180712.87 1
3.3%
116818.51 1
3.3%
78868.88 1
3.3%
73761.86 1
3.3%
65848.32 1
3.3%
54051.05 1
3.3%

남자 30대 금액
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct26
Distinct (%)86.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean52569.572
Minimum0
Maximum228731.52
Zeros5
Zeros (%)16.7%
Negative0
Negative (%)0.0%
Memory size402.0 B
2023-12-10T23:17:25.696919image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q15092.435
median18900.445
Q380880.575
95-th percentile210243.29
Maximum228731.52
Range228731.52
Interquartile range (IQR)75788.14

Descriptive statistics

Standard deviation72528.848
Coefficient of variation (CV)1.3796736
Kurtosis1.0722046
Mean52569.572
Median Absolute Deviation (MAD)16880.88
Skewness1.5369241
Sum1577087.1
Variance5.2604337 × 109
MonotonicityNot monotonic
2023-12-10T23:17:25.880513image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=26)
ValueCountFrequency (%)
0.0 5
 
16.7%
211092.64 1
 
3.3%
94598.54 1
 
3.3%
26036.31 1
 
3.3%
113002.45 1
 
3.3%
228731.52 1
 
3.3%
15349.69 1
 
3.3%
6195.61 1
 
3.3%
7398.68 1
 
3.3%
104524.87 1
 
3.3%
Other values (16) 16
53.3%
ValueCountFrequency (%)
0.0 5
16.7%
850.62 1
 
3.3%
3188.51 1
 
3.3%
4724.71 1
 
3.3%
6195.61 1
 
3.3%
6555.18 1
 
3.3%
7398.68 1
 
3.3%
13604.7 1
 
3.3%
13676.19 1
 
3.3%
13959.98 1
 
3.3%
ValueCountFrequency (%)
228731.52 1
3.3%
211092.64 1
3.3%
209205.19 1
3.3%
206851.81 1
3.3%
113002.45 1
3.3%
107466.65 1
3.3%
104524.87 1
3.3%
94598.54 1
3.3%
39726.68 1
3.3%
34339.48 1
3.3%

남자 40대 금액
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct24
Distinct (%)80.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean28945.101
Minimum0
Maximum145351.82
Zeros7
Zeros (%)23.3%
Negative0
Negative (%)0.0%
Memory size402.0 B
2023-12-10T23:17:26.126274image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q11179.67
median10703.185
Q330801.06
95-th percentile128306.99
Maximum145351.82
Range145351.82
Interquartile range (IQR)29621.39

Descriptive statistics

Standard deviation43123.309
Coefficient of variation (CV)1.489831
Kurtosis2.1139046
Mean28945.101
Median Absolute Deviation (MAD)10703.185
Skewness1.8144769
Sum868353.02
Variance1.8596197 × 109
MonotonicityNot monotonic
2023-12-10T23:17:26.410076image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=24)
ValueCountFrequency (%)
0.0 7
23.3%
115851.73 1
 
3.3%
11198.9 1
 
3.3%
3923.28 1
 
3.3%
20671.18 1
 
3.3%
130870.71 1
 
3.3%
6320.46 1
 
3.3%
1130.35 1
 
3.3%
30910.69 1
 
3.3%
145351.82 1
 
3.3%
Other values (14) 14
46.7%
ValueCountFrequency (%)
0.0 7
23.3%
1130.35 1
 
3.3%
1327.63 1
 
3.3%
1674.26 1
 
3.3%
3923.28 1
 
3.3%
4524.02 1
 
3.3%
6320.46 1
 
3.3%
8065.06 1
 
3.3%
10207.47 1
 
3.3%
11198.9 1
 
3.3%
ValueCountFrequency (%)
145351.82 1
3.3%
130870.71 1
3.3%
125173.55 1
3.3%
115851.73 1
3.3%
65688.41 1
3.3%
47308.56 1
3.3%
31800.93 1
3.3%
30910.69 1
3.3%
30472.17 1
3.3%
21853.6 1
3.3%

남자 50대 금액
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct21
Distinct (%)70.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean18555.631
Minimum0
Maximum130541.4
Zeros10
Zeros (%)33.3%
Negative0
Negative (%)0.0%
Memory size402.0 B
2023-12-10T23:17:26.643778image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median6423.86
Q323892.595
95-th percentile64390.161
Maximum130541.4
Range130541.4
Interquartile range (IQR)23892.595

Descriptive statistics

Standard deviation28851.914
Coefficient of variation (CV)1.5548873
Kurtosis7.0372625
Mean18555.631
Median Absolute Deviation (MAD)6423.86
Skewness2.427169
Sum556668.92
Variance8.3243293 × 108
MonotonicityNot monotonic
2023-12-10T23:17:26.884104image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=21)
ValueCountFrequency (%)
0.0 10
33.3%
65177.99 1
 
3.3%
53300.61 1
 
3.3%
10335.59 1
 
3.3%
38714.17 1
 
3.3%
10686.98 1
 
3.3%
7430.45 1
 
3.3%
130541.4 1
 
3.3%
63427.26 1
 
3.3%
40527.61 1
 
3.3%
Other values (11) 11
36.7%
ValueCountFrequency (%)
0.0 10
33.3%
1636.45 1
 
3.3%
3715.23 1
 
3.3%
3827.8 1
 
3.3%
4220.09 1
 
3.3%
5417.27 1
 
3.3%
7430.45 1
 
3.3%
7467.93 1
 
3.3%
10335.59 1
 
3.3%
10686.98 1
 
3.3%
ValueCountFrequency (%)
130541.4 1
3.3%
65177.99 1
3.3%
63427.26 1
3.3%
53300.61 1
3.3%
40527.61 1
3.3%
38714.17 1
3.3%
35891.92 1
3.3%
25308.57 1
3.3%
19644.67 1
3.3%
17728.39 1
3.3%

남자 60대 이하 금액
Real number (ℝ)

ZEROS 

Distinct14
Distinct (%)46.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean6155.9867
Minimum0
Maximum25100.04
Zeros17
Zeros (%)56.7%
Negative0
Negative (%)0.0%
Memory size402.0 B
2023-12-10T23:17:27.052654image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q313624.815
95-th percentile21661.624
Maximum25100.04
Range25100.04
Interquartile range (IQR)13624.815

Descriptive statistics

Standard deviation8624.5032
Coefficient of variation (CV)1.4009945
Kurtosis-0.6008894
Mean6155.9867
Median Absolute Deviation (MAD)0
Skewness0.99078679
Sum184679.6
Variance74382056
MonotonicityNot monotonic
2023-12-10T23:17:27.269664image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=14)
ValueCountFrequency (%)
0.0 17
56.7%
18310.28 1
 
3.3%
17364.31 1
 
3.3%
24064.53 1
 
3.3%
8916.54 1
 
3.3%
25100.04 1
 
3.3%
6250.58 1
 
3.3%
17578.93 1
 
3.3%
3617.46 1
 
3.3%
17125.47 1
 
3.3%
Other values (4) 4
 
13.3%
ValueCountFrequency (%)
0.0 17
56.7%
689.04 1
 
3.3%
3617.46 1
 
3.3%
6250.58 1
 
3.3%
8916.54 1
 
3.3%
13156.89 1
 
3.3%
13780.79 1
 
3.3%
17125.47 1
 
3.3%
17364.31 1
 
3.3%
17578.93 1
 
3.3%
ValueCountFrequency (%)
25100.04 1
3.3%
24064.53 1
3.3%
18724.74 1
3.3%
18310.28 1
3.3%
17578.93 1
3.3%
17364.31 1
3.3%
17125.47 1
3.3%
13780.79 1
3.3%
13156.89 1
3.3%
8916.54 1
3.3%

여자 10대 이하 금액
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct2
Distinct (%)6.7%
Missing0
Missing (%)0.0%
Memory size372.0 B
0.0
29 
10403.14
 
1

Length

Max length8
Median length3
Mean length3.1666667
Min length3

Unique

Unique1 ?
Unique (%)3.3%

Sample

1st row10403.14
2nd row0.0
3rd row0.0
4th row0.0
5th row0.0

Common Values

ValueCountFrequency (%)
0.0 29
96.7%
10403.14 1
 
3.3%

Length

2023-12-10T23:17:27.490065image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T23:17:27.629442image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0.0 29
96.7%
10403.14 1
 
3.3%

여자 20대 금액
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct23
Distinct (%)76.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean66477.883
Minimum0
Maximum569537.76
Zeros8
Zeros (%)26.7%
Negative0
Negative (%)0.0%
Memory size402.0 B
2023-12-10T23:17:27.761456image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q1122.3125
median21020.145
Q375350.162
95-th percentile279335.95
Maximum569537.76
Range569537.76
Interquartile range (IQR)75227.85

Descriptive statistics

Standard deviation120431.4
Coefficient of variation (CV)1.811601
Kurtosis10.789773
Mean66477.883
Median Absolute Deviation (MAD)21020.145
Skewness3.0941907
Sum1994336.5
Variance1.4503722 × 1010
MonotonicityNot monotonic
2023-12-10T23:17:27.957323image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=23)
ValueCountFrequency (%)
0.0 8
26.7%
569537.76 1
 
3.3%
26254.22 1
 
3.3%
5825.48 1
 
3.3%
94398.39 1
 
3.3%
489.25 1
 
3.3%
336083.85 1
 
3.3%
75312.37 1
 
3.3%
75362.76 1
 
3.3%
20766.22 1
 
3.3%
Other values (13) 13
43.3%
ValueCountFrequency (%)
0.0 8
26.7%
489.25 1
 
3.3%
1467.74 1
 
3.3%
2813.39 1
 
3.3%
3789.72 1
 
3.3%
5825.48 1
 
3.3%
9785.38 1
 
3.3%
20766.22 1
 
3.3%
21274.07 1
 
3.3%
26254.22 1
 
3.3%
ValueCountFrequency (%)
569537.76 1
3.3%
336083.85 1
3.3%
209977.4 1
3.3%
147010.35 1
3.3%
94398.39 1
3.3%
86461.98 1
3.3%
78881.69 1
3.3%
75362.76 1
3.3%
75312.37 1
3.3%
74197.52 1
3.3%

여자 30대 금액
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct22
Distinct (%)73.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean32159.762
Minimum0
Maximum166132.64
Zeros9
Zeros (%)30.0%
Negative0
Negative (%)0.0%
Memory size402.0 B
2023-12-10T23:17:28.155034image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median10198.295
Q353545.208
95-th percentile112067.3
Maximum166132.64
Range166132.64
Interquartile range (IQR)53545.208

Descriptive statistics

Standard deviation44351.391
Coefficient of variation (CV)1.3790958
Kurtosis1.5817424
Mean32159.762
Median Absolute Deviation (MAD)10198.295
Skewness1.5002401
Sum964792.86
Variance1.9670459 × 109
MonotonicityNot monotonic
2023-12-10T23:17:28.332951image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=22)
ValueCountFrequency (%)
0.0 9
30.0%
166132.64 1
 
3.3%
402.69 1
 
3.3%
17000.88 1
 
3.3%
75794.32 1
 
3.3%
98655.66 1
 
3.3%
108616.69 1
 
3.3%
55244.18 1
 
3.3%
74989.89 1
 
3.3%
3402.49 1
 
3.3%
Other values (12) 12
40.0%
ValueCountFrequency (%)
0.0 9
30.0%
402.69 1
 
3.3%
3402.49 1
 
3.3%
3750.6 1
 
3.3%
4134.24 1
 
3.3%
8631.68 1
 
3.3%
9471.75 1
 
3.3%
10924.84 1
 
3.3%
10952.96 1
 
3.3%
15626.44 1
 
3.3%
ValueCountFrequency (%)
166132.64 1
3.3%
114890.53 1
3.3%
108616.69 1
3.3%
98655.66 1
3.3%
79253.22 1
3.3%
75794.32 1
3.3%
74989.89 1
3.3%
55244.18 1
3.3%
48448.29 1
3.3%
30644.8 1
3.3%

여자 40대 금액
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct18
Distinct (%)60.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean19150.2
Minimum0
Maximum128953.71
Zeros13
Zeros (%)43.3%
Negative0
Negative (%)0.0%
Memory size402.0 B
2023-12-10T23:17:28.513068image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median2521.62
Q319747.98
95-th percentile104084.41
Maximum128953.71
Range128953.71
Interquartile range (IQR)19747.98

Descriptive statistics

Standard deviation34602.381
Coefficient of variation (CV)1.8068939
Kurtosis4.205862
Mean19150.2
Median Absolute Deviation (MAD)2521.62
Skewness2.2475258
Sum574506.01
Variance1.1973248 × 109
MonotonicityNot monotonic
2023-12-10T23:17:28.694631image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=18)
ValueCountFrequency (%)
0.0 13
43.3%
104796.39 1
 
3.3%
62997.39 1
 
3.3%
2480.54 1
 
3.3%
20671.18 1
 
3.3%
128953.71 1
 
3.3%
7789.16 1
 
3.3%
18724.74 1
 
3.3%
103214.21 1
 
3.3%
20089.06 1
 
3.3%
Other values (8) 8
26.7%
ValueCountFrequency (%)
0.0 13
43.3%
2168.98 1
 
3.3%
2480.54 1
 
3.3%
2562.7 1
 
3.3%
4593.6 1
 
3.3%
5196.41 1
 
3.3%
7789.16 1
 
3.3%
17471.82 1
 
3.3%
18528.49 1
 
3.3%
18724.74 1
 
3.3%
ValueCountFrequency (%)
128953.71 1
3.3%
104796.39 1
3.3%
103214.21 1
3.3%
62997.39 1
3.3%
32719.32 1
3.3%
21548.31 1
3.3%
20671.18 1
3.3%
20089.06 1
3.3%
18724.74 1
3.3%
18528.49 1
3.3%

여자 50대 금액
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct17
Distinct (%)56.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean20995.055
Minimum0
Maximum122349.8
Zeros14
Zeros (%)46.7%
Negative0
Negative (%)0.0%
Memory size402.0 B
2023-12-10T23:17:28.901564image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median713.325
Q332613.845
95-th percentile106068.67
Maximum122349.8
Range122349.8
Interquartile range (IQR)32613.845

Descriptive statistics

Standard deviation35241.768
Coefficient of variation (CV)1.6785747
Kurtosis3.0446568
Mean20995.055
Median Absolute Deviation (MAD)713.325
Skewness1.9353636
Sum629851.66
Variance1.2419822 × 109
MonotonicityNot monotonic
2023-12-10T23:17:29.101553image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=17)
ValueCountFrequency (%)
0.0 14
46.7%
120435.88 1
 
3.3%
26256.77 1
 
3.3%
475.55 1
 
3.3%
10335.59 1
 
3.3%
44254.78 1
 
3.3%
88508.74 1
 
3.3%
19770.91 1
 
3.3%
122349.8 1
 
3.3%
36579.23 1
 
3.3%
Other values (7) 7
23.3%
ValueCountFrequency (%)
0.0 14
46.7%
475.55 1
 
3.3%
951.1 1
 
3.3%
2096.77 1
 
3.3%
5834.27 1
 
3.3%
9375.86 1
 
3.3%
10335.59 1
 
3.3%
19770.91 1
 
3.3%
26256.77 1
 
3.3%
34732.87 1
 
3.3%
ValueCountFrequency (%)
122349.8 1
3.3%
120435.88 1
3.3%
88508.74 1
3.3%
66095.29 1
3.3%
44254.78 1
3.3%
41798.25 1
3.3%
36579.23 1
3.3%
34732.87 1
3.3%
26256.77 1
3.3%
19770.91 1
3.3%

여자 60대 이하
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct8
Distinct (%)26.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2139.1333
Minimum0
Maximum21429.24
Zeros23
Zeros (%)76.7%
Negative0
Negative (%)0.0%
Memory size402.0 B
2023-12-10T23:17:29.286596image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile14385.467
Maximum21429.24
Range21429.24
Interquartile range (IQR)0

Descriptive statistics

Standard deviation5289.6636
Coefficient of variation (CV)2.4728069
Kurtosis7.2450742
Mean2139.1333
Median Absolute Deviation (MAD)0
Skewness2.780641
Sum64174
Variance27980541
MonotonicityNot monotonic
2023-12-10T23:17:29.446055image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=8)
ValueCountFrequency (%)
0.0 23
76.7%
11190.66 1
 
3.3%
7599.33 1
 
3.3%
3125.29 1
 
3.3%
16999.4 1
 
3.3%
2382.82 1
 
3.3%
1447.26 1
 
3.3%
21429.24 1
 
3.3%
ValueCountFrequency (%)
0.0 23
76.7%
1447.26 1
 
3.3%
2382.82 1
 
3.3%
3125.29 1
 
3.3%
7599.33 1
 
3.3%
11190.66 1
 
3.3%
16999.4 1
 
3.3%
21429.24 1
 
3.3%
ValueCountFrequency (%)
21429.24 1
 
3.3%
16999.4 1
 
3.3%
11190.66 1
 
3.3%
7599.33 1
 
3.3%
3125.29 1
 
3.3%
2382.82 1
 
3.3%
1447.26 1
 
3.3%
0.0 23
76.7%

Interactions

2023-12-10T23:17:20.775231image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T23:17:03.402678image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T23:17:05.596193image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T23:17:07.346354image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T23:17:08.856557image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T23:17:10.686800image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T23:17:12.403466image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T23:17:14.341287image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T23:17:15.971624image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T23:17:17.570528image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T23:17:19.180365image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T23:17:20.945008image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T23:17:03.581654image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T23:17:05.791643image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T23:17:07.541273image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T23:17:09.040680image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T23:17:10.871504image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T23:17:12.583550image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T23:17:14.513813image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T23:17:16.130624image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T23:17:17.726408image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T23:17:19.359402image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T23:17:21.105183image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T23:17:03.752991image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T23:17:05.942300image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T23:17:07.665516image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T23:17:09.193983image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T23:17:11.010410image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T23:17:12.721386image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T23:17:14.652544image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T23:17:16.266217image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T23:17:17.858488image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T23:17:19.507123image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T23:17:21.246955image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T23:17:03.911084image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T23:17:06.094036image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T23:17:07.769639image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T23:17:09.340487image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T23:17:11.146638image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T23:17:13.273946image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T23:17:14.813328image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T23:17:16.397470image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T23:17:17.982867image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T23:17:19.639898image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T23:17:21.381362image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T23:17:04.111374image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T23:17:06.294914image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T23:17:07.900067image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T23:17:09.494488image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T23:17:11.286537image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T23:17:13.406203image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T23:17:14.987677image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T23:17:16.558794image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T23:17:18.189558image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T23:17:19.774272image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T23:17:21.523618image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T23:17:04.315948image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T23:17:06.443032image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T23:17:08.025733image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T23:17:09.704238image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T23:17:11.443160image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T23:17:13.544998image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T23:17:15.128394image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T23:17:16.687773image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T23:17:18.325523image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T23:17:19.919947image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T23:17:21.644252image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T23:17:04.507761image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T23:17:06.583940image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T23:17:08.165698image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T23:17:09.861561image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T23:17:11.635140image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T23:17:13.659300image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T23:17:15.259177image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T23:17:16.815311image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T23:17:18.470076image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T23:17:20.054968image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T23:17:21.782537image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T23:17:04.690311image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T23:17:06.734703image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T23:17:08.303593image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T23:17:10.030360image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T23:17:11.789016image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T23:17:13.789334image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T23:17:15.402715image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T23:17:16.974848image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T23:17:18.609871image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T23:17:20.202561image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T23:17:22.170314image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T23:17:04.885762image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T23:17:06.879503image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T23:17:08.447819image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T23:17:10.213158image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T23:17:11.944008image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T23:17:13.938133image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T23:17:15.538652image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T23:17:17.112911image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T23:17:18.756400image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T23:17:20.340422image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T23:17:22.284633image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T23:17:05.198898image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T23:17:07.046926image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T23:17:08.585415image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T23:17:10.387364image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T23:17:12.093197image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T23:17:14.072055image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T23:17:15.671401image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T23:17:17.266033image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T23:17:18.885628image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T23:17:20.489652image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T23:17:22.402326image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T23:17:05.427520image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T23:17:07.205396image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T23:17:08.724859image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T23:17:10.545956image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T23:17:12.250153image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T23:17:14.212435image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T23:17:15.822825image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T23:17:17.403849image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T23:17:19.040492image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T23:17:20.633950image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-10T23:17:29.602773image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
블록 ID대분류중분류소분류남자 20대 금액남자 30대 금액남자 40대 금액남자 50대 금액남자 60대 이하 금액여자 10대 이하 금액여자 20대 금액여자 30대 금액여자 40대 금액여자 50대 금액여자 60대 이하
블록 ID1.0000.0000.4970.9250.4630.2630.9230.3640.775NaN0.0000.3750.0000.0000.673
대분류0.0001.0001.0001.0000.0000.1460.0000.0000.0000.0000.0000.0000.0000.5790.000
중분류0.4971.0001.0001.0000.7480.0000.7690.7230.7581.0000.9170.6640.8410.6670.864
소분류0.9251.0001.0001.0000.6690.7000.8781.0000.2191.0000.9820.9210.9791.0001.000
남자 20대 금액0.4630.0000.7480.6691.0000.6910.8500.7450.6661.0000.8860.8990.8440.5820.857
남자 30대 금액0.2630.1460.0000.7000.6911.0000.9030.7090.7230.5440.6730.9080.6780.0820.607
남자 40대 금액0.9230.0000.7690.8780.8500.9031.0000.7160.8841.0000.8430.9590.8090.1450.905
남자 50대 금액0.3640.0000.7231.0000.7450.7090.7161.0000.3250.5730.9200.8430.9470.5370.914
남자 60대 이하 금액0.7750.0000.7580.2190.6660.7230.8840.3251.0000.4220.6120.6430.5370.0000.552
여자 10대 이하 금액NaN0.0001.0001.0001.0000.5441.0000.5730.4221.0001.0001.0000.8120.5531.000
여자 20대 금액0.0000.0000.9170.9820.8860.6730.8430.9200.6121.0001.0000.8890.9860.6240.916
여자 30대 금액0.3750.0000.6640.9210.8990.9080.9590.8430.6431.0000.8891.0000.8530.7120.904
여자 40대 금액0.0000.0000.8410.9790.8440.6780.8090.9470.5370.8120.9860.8531.0000.6550.894
여자 50대 금액0.0000.5790.6671.0000.5820.0820.1450.5370.0000.5530.6240.7120.6551.0000.460
여자 60대 이하0.6730.0000.8641.0000.8570.6070.9050.9140.5521.0000.9160.9040.8940.4601.000
2023-12-10T23:17:29.926182image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
여자 10대 이하 금액대분류
여자 10대 이하 금액1.0000.000
대분류0.0001.000
2023-12-10T23:17:30.083399image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
블록 ID남자 20대 금액남자 30대 금액남자 40대 금액남자 50대 금액남자 60대 이하 금액여자 20대 금액여자 30대 금액여자 40대 금액여자 50대 금액여자 60대 이하대분류여자 10대 이하 금액
블록 ID1.000-0.283-0.134-0.043-0.151-0.360-0.210-0.2050.0380.037-0.2510.0000.000
남자 20대 금액-0.2831.0000.8370.5380.7480.3910.7720.7150.5550.4370.5960.0000.906
남자 30대 금액-0.1340.8371.0000.6870.6810.3740.8020.7200.6110.3880.4940.0930.354
남자 40대 금액-0.0430.5380.6871.0000.5890.4010.5630.5210.5350.1700.4450.0000.886
남자 50대 금액-0.1510.7480.6810.5891.0000.3730.7710.6500.6780.4520.5460.0000.378
남자 60대 이하 금액-0.3600.3910.3740.4010.3731.0000.4770.4100.3720.1090.3350.0000.267
여자 20대 금액-0.2100.7720.8020.5630.7710.4771.0000.9010.6350.5270.4820.0000.926
여자 30대 금액-0.2050.7150.7200.5210.6500.4100.9011.0000.5580.4470.4530.0000.886
여자 40대 금액0.0380.5550.6110.5350.6780.3720.6350.5581.0000.3730.5240.0000.567
여자 50대 금액0.0370.4370.3880.1700.4520.1090.5270.4470.3731.0000.3990.3960.535
여자 60대 이하-0.2510.5960.4940.4450.5460.3350.4820.4530.5240.3991.0000.0000.926
대분류0.0000.0000.0930.0000.0000.0000.0000.0000.0000.3960.0001.0000.000
여자 10대 이하 금액0.0000.9060.3540.8860.3780.2670.9260.8860.5670.5350.9260.0001.000

Missing values

2023-12-10T23:17:22.580554image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-10T23:17:22.892240image/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

기준년월블록 ID대분류중분류소분류남자 10대 이하 금액남자 20대 금액남자 30대 금액남자 40대 금액남자 50대 금액남자 60대 이하 금액여자 10대 이하 금액여자 20대 금액여자 30대 금액여자 40대 금액여자 50대 금액여자 60대 이하
02019-0131050510100030000001음식다방/커피숍/카페커피전문점0485119.12211092.64115851.7365177.9918310.2810403.14569537.76166132.64104796.39120435.8811190.66
12019-0131050510100030000001소매의복의류 판매-남성전문04065.876555.181327.637467.9317364.310.086461.9810952.960.041798.250.0
22019-0131050510100030000001음식중식중국음식/중국집0116818.51209205.19125173.5525308.5724064.530.0147010.35114890.5332719.320.07599.33
32019-0131050510100040000001음식양식돈가스 전문점00.03188.518065.064220.090.00.02813.399471.750.00.00.0
42019-0131050510100040000001관광/여가/오락무도/유흥/가무노래방0266300.02107466.6514682.583715.238916.540.078881.6979253.2221548.31951.10.0
52019-0131050510100040000001음식한식돼지갈비 전문점046317.732955.0919592.485417.2725100.040.028711.5610924.840.00.00.0
62019-0131050510100050000001소매의복셔츠/내의 판매00.00.00.00.00.00.00.00.00.066095.290.0
72019-0131050510100050000001소매취미/오락관련소매그림/액자 판매00.00.00.00.00.00.00.00.04593.60.00.0
82019-0131050510100050000001음식수산물참치 전문점065848.3213676.190.017728.390.00.021274.0730644.80.00.00.0
92019-0131050510100050000001음식일식초밥 전문점078868.8830583.181674.2619644.676250.580.052683.4315626.4418528.499375.863125.29
기준년월블록 ID대분류중분류소분류남자 10대 이하 금액남자 20대 금액남자 30대 금액남자 40대 금액남자 50대 금액남자 60대 이하 금액여자 10대 이하 금액여자 20대 금액여자 30대 금액여자 40대 금액여자 50대 금액여자 60대 이하
202019-0131050510100100000002음식한식닭갈비0200137.27104524.87145351.82130541.40.00.075362.7655244.18103214.21122349.821429.24
212019-0131050510100100000003관광/여가/오락무도/유흥/가무노래방00.00.030910.697430.4518724.740.00.00.018724.740.00.0
222019-0131050510100100000003생활서비스이/미용/건강네일케어00.07398.681130.3510686.980.00.075312.37108616.697789.1619770.910.0
232019-0131050510100100000003소매의복의류 판매-기타00.06195.610.00.00.00.00.00.00.088508.740.0
242019-0131050510100100000003숙박모텔/여관/여인숙모텔00.015349.696320.460.00.00.00.00.00.00.00.0
252019-0131050510100100000006음식양식경양식 전문점0180712.87228731.52130870.7138714.170.00.0336083.8598655.66128953.7144254.780.0
262019-0131050510100100000004관광/여가/오락PC/오락/당구/볼링등당구장00.00.00.00.00.00.0489.250.00.00.00.0
272019-0131050510100100000006음식한식죽요리 전문점05167.79113002.4520671.1810335.5913780.790.094398.3975794.3220671.1810335.590.0
282019-0131050510100100000007관광/여가/오락무도/유흥/가무노래방018189.7526036.313923.280.00.00.05825.4817000.880.0475.550.0
292019-0131050510100100000007소매의약/의료품소매보청기 판매00.00.00.00.0689.040.00.00.02480.540.00.0