Overview

Dataset statistics

Number of variables11
Number of observations30
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory2.9 KiB
Average record size in memory98.4 B

Variable types

DateTime1
Categorical3
Text2
Numeric5

Dataset

Description샘플 데이터
Author경기콘텐츠진흥원
URLhttps://bigdata-region.kr/#/dataset/fbe54527-6bbb-42ba-9778-1401ff6c48b5

Alerts

기준년월 has constant value ""Constant
시도명 has constant value ""Constant
1인당 소비액 표준편차 has constant value ""Constant
소비액 is highly overall correlated with 전체 인구 and 2 other fieldsHigh correlation
전체 인구 is highly overall correlated with 소비액High correlation
1인당 소비액 is highly overall correlated with 소비액 and 1 other fieldsHigh correlation
유동 인구 소비융합지수 is highly overall correlated with 소비액 and 1 other fieldsHigh correlation
소비액 has unique valuesUnique
전체 인구 has unique valuesUnique
1인당 소비액 has unique valuesUnique
유동 인구 소비융합지수 has unique valuesUnique

Reproduction

Analysis started2023-12-10 14:14:09.355437
Analysis finished2023-12-10 14:14:15.102229
Duration5.75 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
2023-12-10T23:14:15.184692image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T23:14:15.398301image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=1)

시도명
Categorical

CONSTANT 

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

Length

Max length3
Median length3
Mean length3
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
경기도 30
100.0%

Length

2023-12-10T23:14:15.609241image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T23:14:15.778440image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
경기도 30
100.0%

시군구명
Text

Distinct16
Distinct (%)53.3%
Missing0
Missing (%)0.0%
Memory size372.0 B
2023-12-10T23:14:16.070401image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length8
Median length3
Mean length4.5666667
Min length3

Characters and Unicode

Total characters137
Distinct characters35
Distinct categories2 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique9 ?
Unique (%)30.0%

Sample

1st row고양시 덕양구
2nd row가평군
3rd row고양시 덕양구
4th row고양시 일산동구
5th row고양시 일산동구
ValueCountFrequency (%)
부천시 8
19.5%
고양시 4
9.8%
수원시 4
9.8%
김포시 3
 
7.3%
성남시 3
 
7.3%
덕양구 2
 
4.9%
일산동구 2
 
4.9%
과천시 2
 
4.9%
구리시 2
 
4.9%
장안구 2
 
4.9%
Other values (9) 9
22.0%
2023-12-10T23:14:16.610737image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
시 29
21.2%
구 13
 
9.5%
11
 
8.0%
천 10
 
7.3%
부 8
 
5.8%
양 7
 
5.1%
원 5
 
3.6%
수 5
 
3.6%
고 4
 
2.9%
남 4
 
2.9%
Other values (25) 41
29.9%

Most occurring categories

ValueCountFrequency (%)
Other Letter 126
92.0%
Space Separator 11
 
8.0%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
시 29
23.0%
구 13
 
10.3%
천 10
 
7.9%
부 8
 
6.3%
양 7
 
5.6%
원 5
 
4.0%
수 5
 
4.0%
고 4
 
3.2%
남 4
 
3.2%
김 3
 
2.4%
Other values (24) 38
30.2%
Space Separator
ValueCountFrequency (%)
11
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 126
92.0%
Common 11
 
8.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
시 29
23.0%
구 13
 
10.3%
천 10
 
7.9%
부 8
 
6.3%
양 7
 
5.6%
원 5
 
4.0%
수 5
 
4.0%
고 4
 
3.2%
남 4
 
3.2%
김 3
 
2.4%
Other values (24) 38
30.2%
Common
ValueCountFrequency (%)
11
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 126
92.0%
ASCII 11
 
8.0%

Most frequent character per block

Hangul
ValueCountFrequency (%)
시 29
23.0%
구 13
 
10.3%
천 10
 
7.9%
부 8
 
6.3%
양 7
 
5.6%
원 5
 
4.0%
수 5
 
4.0%
고 4
 
3.2%
남 4
 
3.2%
김 3
 
2.4%
Other values (24) 38
30.2%
ASCII
ValueCountFrequency (%)
11
100.0%

행정동명
Text

Distinct29
Distinct (%)96.7%
Missing0
Missing (%)0.0%
Memory size372.0 B
2023-12-10T23:14:16.949418image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length4
Median length4
Mean length3.6
Min length3

Characters and Unicode

Total characters108
Distinct characters49
Distinct categories2 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique28 ?
Unique (%)93.3%

Sample

1st row행신3동
2nd row조종면
3rd row화정2동
4th row장항2동
5th row백석2동
ValueCountFrequency (%)
심곡1동 2
 
6.7%
행신3동 1
 
3.3%
소사동 1
 
3.3%
영화동 1
 
3.3%
광교2동 1
 
3.3%
성남동 1
 
3.3%
세류3동 1
 
3.3%
수진1동 1
 
3.3%
이매2동 1
 
3.3%
중1동 1
 
3.3%
Other values (19) 19
63.3%
2023-12-10T23:14:17.479456image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
동 27
25.0%
2 8
 
7.4%
1 6
 
5.6%
곡 5
 
4.6%
심 4
 
3.7%
면 3
 
2.8%
수 3
 
2.8%
양 2
 
1.9%
본 2
 
1.9%
사 2
 
1.9%
Other values (39) 46
42.6%

Most occurring categories

ValueCountFrequency (%)
Other Letter 91
84.3%
Decimal Number 17
 
15.7%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
동 27
29.7%
곡 5
 
5.5%
심 4
 
4.4%
면 3
 
3.3%
수 3
 
3.3%
양 2
 
2.2%
본 2
 
2.2%
사 2
 
2.2%
소 2
 
2.2%
성 2
 
2.2%
Other values (35) 39
42.9%
Decimal Number
ValueCountFrequency (%)
2 8
47.1%
1 6
35.3%
3 2
 
11.8%
4 1
 
5.9%

Most occurring scripts

ValueCountFrequency (%)
Hangul 91
84.3%
Common 17
 
15.7%

Most frequent character per script

Hangul
ValueCountFrequency (%)
동 27
29.7%
곡 5
 
5.5%
심 4
 
4.4%
면 3
 
3.3%
수 3
 
3.3%
양 2
 
2.2%
본 2
 
2.2%
사 2
 
2.2%
소 2
 
2.2%
성 2
 
2.2%
Other values (35) 39
42.9%
Common
ValueCountFrequency (%)
2 8
47.1%
1 6
35.3%
3 2
 
11.8%
4 1
 
5.9%

Most occurring blocks

ValueCountFrequency (%)
Hangul 91
84.3%
ASCII 17
 
15.7%

Most frequent character per block

Hangul
ValueCountFrequency (%)
동 27
29.7%
곡 5
 
5.5%
심 4
 
4.4%
면 3
 
3.3%
수 3
 
3.3%
양 2
 
2.2%
본 2
 
2.2%
사 2
 
2.2%
소 2
 
2.2%
성 2
 
2.2%
Other values (35) 39
42.9%
ASCII
ValueCountFrequency (%)
2 8
47.1%
1 6
35.3%
3 2
 
11.8%
4 1
 
5.9%

행정동 코드
Real number (ℝ)

Distinct29
Distinct (%)96.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean4.1280989 × 109
Minimum4.111158 × 109
Maximum4.1820345 × 109
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size402.0 B
2023-12-10T23:14:17.722420image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum4.111158 × 109
5-th percentile4.1112472 × 109
Q14.1190512 × 109
median4.1200685 × 109
Q34.130556 × 109
95-th percentile4.1592542 × 109
Maximum4.1820345 × 109
Range70876500
Interquartile range (IQR)11504750

Descriptive statistics

Standard deviation17682653
Coefficient of variation (CV)0.0042834858
Kurtosis1.9835939
Mean4.1280989 × 109
Median Absolute Deviation (MAD)8397100
Skewness1.545795
Sum1.2384297 × 1011
Variance3.1267622 × 1014
MonotonicityNot monotonic
2023-12-10T23:14:17.996950image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=29)
ValueCountFrequency (%)
4119052000 2
 
6.7%
4128165500 1
 
3.3%
4182034500 1
 
3.3%
4111159800 1
 
3.3%
4111158000 1
 
3.3%
4111761000 1
 
3.3%
4113351000 1
 
3.3%
4111354000 1
 
3.3%
4113157000 1
 
3.3%
4113561000 1
 
3.3%
Other values (19) 19
63.3%
ValueCountFrequency (%)
4111158000 1
3.3%
4111159800 1
3.3%
4111354000 1
3.3%
4111761000 1
3.3%
4113157000 1
3.3%
4113351000 1
3.3%
4113561000 1
3.3%
4119051000 1
3.3%
4119052000 2
6.7%
4119055000 1
3.3%
ValueCountFrequency (%)
4182034500 1
3.3%
4161051000 1
3.3%
4157058000 1
3.3%
4157036000 1
3.3%
4157034000 1
3.3%
4136051000 1
3.3%
4131058000 1
3.3%
4131057000 1
3.3%
4129053000 1
3.3%
4129051000 1
3.3%

성별코드
Categorical

Distinct2
Distinct (%)6.7%
Missing0
Missing (%)0.0%
Memory size372.0 B
F
19 
M
11 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowM
2nd rowM
3rd rowF
4th rowF
5th rowF

Common Values

ValueCountFrequency (%)
F 19
63.3%
M 11
36.7%

Length

2023-12-10T23:14:18.261521image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T23:14:18.436028image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
f 19
63.3%
m 11
36.7%

소비액
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct30
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2.1313284 × 108
Minimum26378495
Maximum1.0764373 × 109
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size402.0 B
2023-12-10T23:14:18.615562image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum26378495
5-th percentile40853607
Q168053091
median1.0985672 × 108
Q32.7058583 × 108
95-th percentile6.2972616 × 108
Maximum1.0764373 × 109
Range1.0500588 × 109
Interquartile range (IQR)2.0253274 × 108

Descriptive statistics

Standard deviation2.350624 × 108
Coefficient of variation (CV)1.1028915
Kurtosis6.0262454
Mean2.1313284 × 108
Median Absolute Deviation (MAD)64345579
Skewness2.2859775
Sum6.3939852 × 109
Variance5.5254334 × 1016
MonotonicityNot monotonic
2023-12-10T23:14:18.888396image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=30)
ValueCountFrequency (%)
259559474.31 1
 
3.3%
111450977.84 1
 
3.3%
128602651.78 1
 
3.3%
142902508.79 1
 
3.3%
240676384.65 1
 
3.3%
273929181.83 1
 
3.3%
77237073.66 1
 
3.3%
46086210.59 1
 
3.3%
49150732.94 1
 
3.3%
1076437268.71 1
 
3.3%
Other values (20) 20
66.7%
ValueCountFrequency (%)
26378495.39 1
3.3%
37513413.13 1
3.3%
44936066.71 1
3.3%
46086210.59 1
3.3%
49150732.94 1
3.3%
50278015.76 1
3.3%
51211190.47 1
3.3%
66943886.58 1
3.3%
71380703.57 1
3.3%
77237073.66 1
3.3%
ValueCountFrequency (%)
1076437268.71 1
3.3%
780305805.22 1
3.3%
445684360.61 1
3.3%
412063926.15 1
3.3%
395525140.56 1
3.3%
378690990.42 1
3.3%
312606350.35 1
3.3%
273929181.83 1
3.3%
260555758.06 1
3.3%
259559474.31 1
3.3%

전체 인구
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct30
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean23394.463
Minimum3531.25
Maximum60610.2
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size402.0 B
2023-12-10T23:14:19.136334image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum3531.25
5-th percentile4953.3005
Q19746.295
median22675.145
Q331511.91
95-th percentile51579.888
Maximum60610.2
Range57078.95
Interquartile range (IQR)21765.615

Descriptive statistics

Standard deviation15060.701
Coefficient of variation (CV)0.64377205
Kurtosis0.095094131
Mean23394.463
Median Absolute Deviation (MAD)11756.145
Skewness0.78152319
Sum701833.88
Variance2.2682472 × 108
MonotonicityNot monotonic
2023-12-10T23:14:19.360595image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=30)
ValueCountFrequency (%)
32290.26 1
 
3.3%
26705.21 1
 
3.3%
15977.85 1
 
3.3%
20784.85 1
 
3.3%
33812.25 1
 
3.3%
47585.31 1
 
3.3%
9561.74 1
 
3.3%
3928.88 1
 
3.3%
10299.96 1
 
3.3%
60610.2 1
 
3.3%
Other values (20) 20
66.7%
ValueCountFrequency (%)
3531.25 1
3.3%
3928.88 1
3.3%
6205.37 1
3.3%
7814.25 1
3.3%
8105.2 1
3.3%
9249.57 1
3.3%
9254.09 1
3.3%
9561.74 1
3.3%
10299.96 1
3.3%
13527.53 1
3.3%
ValueCountFrequency (%)
60610.2 1
3.3%
54848.18 1
3.3%
47585.31 1
3.3%
43508.27 1
3.3%
37784.76 1
3.3%
36944.33 1
3.3%
33812.25 1
3.3%
32290.26 1
3.3%
29176.86 1
3.3%
26705.21 1
3.3%

1인당 소비액
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct30
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean8410.675
Minimum1921.55
Maximum18057.9
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size402.0 B
2023-12-10T23:14:19.566120image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1921.55
5-th percentile2312.9065
Q15303.9575
median7591.72
Q310741.747
95-th percentile17180.953
Maximum18057.9
Range16136.35
Interquartile range (IQR)5437.79

Descriptive statistics

Standard deviation4367.247
Coefficient of variation (CV)0.51925047
Kurtosis-0.03206198
Mean8410.675
Median Absolute Deviation (MAD)2687.675
Skewness0.6971547
Sum252320.25
Variance19072846
MonotonicityNot monotonic
2023-12-10T23:14:19.788030image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=30)
ValueCountFrequency (%)
8038.32 1
 
3.3%
4173.38 1
 
3.3%
8048.81 1
 
3.3%
6875.32 1
 
3.3%
7118.02 1
 
3.3%
5756.59 1
 
3.3%
8077.72 1
 
3.3%
11730.11 1
 
3.3%
4771.93 1
 
3.3%
17760.0 1
 
3.3%
Other values (20) 20
66.7%
ValueCountFrequency (%)
1921.55 1
3.3%
2132.29 1
3.3%
2533.66 1
3.3%
3710.56 1
3.3%
4173.38 1
3.3%
4771.93 1
3.3%
4874.96 1
3.3%
5153.08 1
3.3%
5756.59 1
3.3%
6203.18 1
3.3%
ValueCountFrequency (%)
18057.9 1
3.3%
17760.0 1
3.3%
16473.23 1
3.3%
14226.65 1
3.3%
12921.33 1
3.3%
12209.67 1
3.3%
11730.11 1
3.3%
10905.56 1
3.3%
10250.31 1
3.3%
10111.69 1
3.3%

1인당 소비액 표준편차
Categorical

CONSTANT 

Distinct1
Distinct (%)3.3%
Missing0
Missing (%)0.0%
Memory size372.0 B
4888.93
30 

Length

Max length7
Median length7
Mean length7
Min length7

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row4888.93
2nd row4888.93
3rd row4888.93
4th row4888.93
5th row4888.93

Common Values

ValueCountFrequency (%)
4888.93 30
100.0%

Length

2023-12-10T23:14:20.026756image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T23:14:20.202192image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
4888.93 30
100.0%

유동 인구 소비융합지수
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct30
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean172.03367
Minimum39.3
Maximum369.36
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size402.0 B
2023-12-10T23:14:20.351496image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum39.3
5-th percentile47.3045
Q1108.4875
median155.28
Q3219.7175
95-th percentile351.426
Maximum369.36
Range330.06
Interquartile range (IQR)111.23

Descriptive statistics

Standard deviation89.330183
Coefficient of variation (CV)0.51925989
Kurtosis-0.03210201
Mean172.03367
Median Absolute Deviation (MAD)54.975
Skewness0.69714027
Sum5161.01
Variance7979.8816
MonotonicityNot monotonic
2023-12-10T23:14:20.575821image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=30)
ValueCountFrequency (%)
164.42 1
 
3.3%
85.36 1
 
3.3%
164.63 1
 
3.3%
140.63 1
 
3.3%
145.59 1
 
3.3%
117.75 1
 
3.3%
165.22 1
 
3.3%
239.93 1
 
3.3%
97.61 1
 
3.3%
363.27 1
 
3.3%
Other values (20) 20
66.7%
ValueCountFrequency (%)
39.3 1
3.3%
43.61 1
3.3%
51.82 1
3.3%
75.9 1
3.3%
85.36 1
3.3%
97.61 1
3.3%
99.71 1
3.3%
105.4 1
3.3%
117.75 1
3.3%
126.88 1
3.3%
ValueCountFrequency (%)
369.36 1
3.3%
363.27 1
3.3%
336.95 1
3.3%
291.0 1
3.3%
264.3 1
3.3%
249.74 1
3.3%
239.93 1
3.3%
223.07 1
3.3%
209.66 1
3.3%
206.83 1
3.3%

Interactions

2023-12-10T23:14:13.675198image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T23:14:09.849595image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T23:14:11.001886image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T23:14:11.914502image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T23:14:12.741879image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T23:14:13.892703image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T23:14:10.003049image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T23:14:11.189980image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T23:14:12.090821image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T23:14:12.939384image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T23:14:14.068656image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T23:14:10.169486image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T23:14:11.356696image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T23:14:12.263153image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T23:14:13.084743image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T23:14:14.262289image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T23:14:10.313446image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T23:14:11.497143image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T23:14:12.414919image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T23:14:13.244977image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T23:14:14.449467image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T23:14:10.476416image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T23:14:11.704338image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T23:14:12.569944image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T23:14:13.453528image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-10T23:14:20.744287image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
시군구명행정동명행정동 코드성별코드소비액전체 인구1인당 소비액유동 인구 소비융합지수
시군구명1.0001.0001.0000.0000.0000.7660.0000.000
행정동명1.0001.0001.0000.0001.0000.9641.0001.000
행정동 코드1.0001.0001.0000.2260.0000.6240.0000.088
성별코드0.0000.0000.2261.0000.0000.3080.0000.000
소비액0.0001.0000.0000.0001.0000.8880.7590.772
전체 인구0.7660.9640.6240.3080.8881.0000.6380.667
1인당 소비액0.0001.0000.0000.0000.7590.6381.0001.000
유동 인구 소비융합지수0.0001.0000.0880.0000.7720.6671.0001.000
2023-12-10T23:14:20.934287image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
행정동 코드소비액전체 인구1인당 소비액유동 인구 소비융합지수성별코드
행정동 코드1.0000.0340.245-0.164-0.1640.222
소비액0.0341.0000.7600.5920.5920.000
전체 인구0.2450.7601.0000.0430.0430.114
1인당 소비액-0.1640.5920.0431.0001.0000.000
유동 인구 소비융합지수-0.1640.5920.0431.0001.0000.000
성별코드0.2220.0000.1140.0000.0001.000

Missing values

2023-12-10T23:14:14.694547image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-10T23:14:14.997349image/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

기준년월시도명시군구명행정동명행정동 코드성별코드소비액전체 인구1인당 소비액1인당 소비액 표준편차유동 인구 소비융합지수
02019-01경기도고양시 덕양구행신3동4128165500M259559474.3132290.268038.324888.93164.42
12019-01경기도가평군조종면4182034500M50278015.768105.26203.184888.93126.88
22019-01경기도고양시 덕양구화정2동4128162200F445684360.6124680.8518057.94888.93369.36
32019-01경기도고양시 일산동구장항2동4128559000F780305805.2254848.1814226.654888.93291.0
42019-01경기도고양시 일산동구백석2동4128555200F108262456.6529176.863710.564888.9375.9
52019-01경기도과천시별양동4129053000F79551717.6915437.75153.084888.93105.4
62019-01경기도과천시중앙동4129051000F37513413.1317593.042132.294888.9343.61
72019-01경기도광명시철산4동4121062000M26378495.393531.257470.024888.93152.79
82019-01경기도광주시경안동4161051000F412063926.1537784.7610905.564888.93223.07
92019-01경기도구리시수택1동4131057000F260555758.0621340.1112209.674888.93249.74
기준년월시도명시군구명행정동명행정동 코드성별코드소비액전체 인구1인당 소비액1인당 소비액 표준편차유동 인구 소비융합지수
202019-01경기도부천시심곡본동4119071000F312606350.3524193.0412921.334888.93264.3
212019-01경기도부천시역곡1동4119057000F89343935.7613527.536604.64888.93135.09
222019-01경기도부천시중1동4119066000M1076437268.7160610.217760.04888.93363.27
232019-01경기도성남시 분당구이매2동4113561000F49150732.9410299.964771.934888.9397.61
242019-01경기도성남시 수정구수진1동4113157000F46086210.593928.8811730.114888.93239.93
252019-01경기도수원시 권선구세류3동4111354000F77237073.669561.748077.724888.93165.22
262019-01경기도성남시 중원구성남동4113351000F273929181.8347585.315756.594888.93117.75
272019-01경기도수원시 영통구광교2동4111761000M240676384.6533812.257118.024888.93145.59
282019-01경기도수원시 장안구영화동4111158000F142902508.7920784.856875.324888.93140.63
292019-01경기도수원시 장안구조원2동4111159800M128602651.7815977.858048.814888.93164.63