Overview

Dataset statistics

Number of variables12
Number of observations30
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory3.1 KiB
Average record size in memory106.4 B

Variable types

Categorical6
Numeric5
Text1

Dataset

Description샘플 데이터
Author경기콘텐츠진흥원
URLhttps://bigdata-region.kr/#/dataset/b36256b0-0604-4583-80a2-50b446eeace7

Alerts

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

Reproduction

Analysis started2023-12-10 14:24:35.174916
Analysis finished2023-12-10 14:24:38.865744
Duration3.69 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

기준년월
Categorical

CONSTANT 

Distinct1
Distinct (%)3.3%
Missing0
Missing (%)0.0%
Memory size372.0 B
2019-01
30 

Length

Max length7
Median length7
Mean length7
Min length7

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2019-01
2nd row2019-01
3rd row2019-01
4th row2019-01
5th row2019-01

Common Values

ValueCountFrequency (%)
2019-01 30
100.0%

Length

2023-12-10T23:24:38.972117image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T23:24:39.082506image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2019-01 30
100.0%

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

2023-12-10T23:24:39.190092image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T23:24:39.287882image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
경기도 30
100.0%

시군구명
Categorical

HIGH CORRELATION 

Distinct2
Distinct (%)6.7%
Missing0
Missing (%)0.0%
Memory size372.0 B
고양시
18 
가평군
12 

Length

Max length3
Median length3
Mean length3
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
고양시 18
60.0%
가평군 12
40.0%

Length

2023-12-10T23:24:39.406729image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T23:24:39.517029image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
고양시 18
60.0%
가평군 12
40.0%

행정동명
Categorical

HIGH CORRELATION 

Distinct13
Distinct (%)43.3%
Missing0
Missing (%)0.0%
Memory size372.0 B
능곡동
5 
백석1동
4 
가평읍
3 
상면
3 
마두1동
3 
Other values (8)
12 

Length

Max length4
Median length3
Mean length3.1666667
Min length2

Unique

Unique4 ?
Unique (%)13.3%

Sample

1st row가평읍
2nd row가평읍
3rd row가평읍
4th row상면
5th row상면

Common Values

ValueCountFrequency (%)
능곡동 5
16.7%
백석1동 4
13.3%
가평읍 3
10.0%
상면 3
10.0%
마두1동 3
10.0%
설악면 2
 
6.7%
조종면 2
 
6.7%
청평면 2
 
6.7%
대화동 2
 
6.7%
고봉동 1
 
3.3%
Other values (3) 3
10.0%

Length

2023-12-10T23:24:39.650203image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
능곡동 5
16.7%
백석1동 4
13.3%
가평읍 3
10.0%
상면 3
10.0%
마두1동 3
10.0%
설악면 2
 
6.7%
조종면 2
 
6.7%
청평면 2
 
6.7%
대화동 2
 
6.7%
고봉동 1
 
3.3%
Other values (3) 3
10.0%

행정동 코드
Real number (ℝ)

HIGH CORRELATION 

Distinct13
Distinct (%)43.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean4.1498673 × 109
Minimum4.128159 × 109
Maximum4.1820345 × 109
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size402.0 B
2023-12-10T23:24:39.827851image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum4.128159 × 109
5-th percentile4.128161 × 109
Q14.1285551 × 109
median4.128558 × 109
Q34.182031 × 109
95-th percentile4.1820338 × 109
Maximum4.1820345 × 109
Range53875500
Interquartile range (IQR)53475900

Descriptive statistics

Standard deviation26710927
Coefficient of variation (CV)0.0064365739
Kurtosis-1.9498732
Mean4.1498673 × 109
Median Absolute Deviation (MAD)397000
Skewness0.42992275
Sum1.2449602 × 1011
Variance7.1347364 × 1014
MonotonicityNot monotonic
2023-12-10T23:24:39.971432image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=13)
ValueCountFrequency (%)
4128161000 5
16.7%
4128555100 4
13.3%
4182025000 3
10.0%
4182033000 3
10.0%
4128556000 3
10.0%
4182031000 2
 
6.7%
4182034500 2
 
6.7%
4182032500 2
 
6.7%
4128757000 2
 
6.7%
4128560000 1
 
3.3%
Other values (3) 3
10.0%
ValueCountFrequency (%)
4128159000 1
 
3.3%
4128161000 5
16.7%
4128167000 1
 
3.3%
4128555100 4
13.3%
4128555200 1
 
3.3%
4128556000 3
10.0%
4128560000 1
 
3.3%
4128757000 2
 
6.7%
4182025000 3
10.0%
4182031000 2
 
6.7%
ValueCountFrequency (%)
4182034500 2
6.7%
4182033000 3
10.0%
4182032500 2
6.7%
4182031000 2
6.7%
4182025000 3
10.0%
4128757000 2
6.7%
4128560000 1
 
3.3%
4128556000 3
10.0%
4128555200 1
 
3.3%
4128555100 4
13.3%

대분류
Categorical

Distinct8
Distinct (%)26.7%
Missing0
Missing (%)0.0%
Memory size372.0 B
소매
8 
음식
7 
학문/교육
5 
생활서비스
4 
의료
3 
Other values (3)
3 

Length

Max length8
Median length2
Mean length3.1333333
Min length2

Unique

Unique3 ?
Unique (%)10.0%

Sample

1st row소매
2nd row소매
3rd row학문/교육
4th row음식
5th row스포츠

Common Values

ValueCountFrequency (%)
소매 8
26.7%
음식 7
23.3%
학문/교육 5
16.7%
생활서비스 4
13.3%
의료 3
 
10.0%
스포츠 1
 
3.3%
관광/여가/오락 1
 
3.3%
숙박 1
 
3.3%

Length

2023-12-10T23:24:40.135387image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T23:24:40.264263image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
소매 8
26.7%
음식 7
23.3%
학문/교육 5
16.7%
생활서비스 4
13.3%
의료 3
 
10.0%
스포츠 1
 
3.3%
관광/여가/오락 1
 
3.3%
숙박 1
 
3.3%

중분류
Text

Distinct27
Distinct (%)90.0%
Missing0
Missing (%)0.0%
Memory size372.0 B
2023-12-10T23:24:40.497823image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length12
Median length9.5
Mean length6.0666667
Min length2

Characters and Unicode

Total characters182
Distinct characters98
Distinct categories4 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique24 ?
Unique (%)80.0%

Sample

1st row의복
2nd row사진/광학/정밀기기
3rd row학원-보습교습입시
4th row중식
5th row운동시설
ValueCountFrequency (%)
의복 2
 
6.7%
한식 2
 
6.7%
학원-예능취미체육 2
 
6.7%
개인/가정용품수리 1
 
3.3%
애견/애완/동물 1
 
3.3%
병원 1
 
3.3%
운송/배달/택배 1
 
3.3%
취미/오락관련소매 1
 
3.3%
유아교육 1
 
3.3%
수의업 1
 
3.3%
Other values (17) 17
56.7%
2023-12-10T23:24:41.011991image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
/ 23
 
12.6%
식 7
 
3.8%
기 5
 
2.7%
학 4
 
2.2%
원 4
 
2.2%
육 4
 
2.2%
의 3
 
1.6%
방 3
 
1.6%
물 3
 
1.6%
시 3
 
1.6%
Other values (88) 123
67.6%

Most occurring categories

ValueCountFrequency (%)
Other Letter 154
84.6%
Other Punctuation 23
 
12.6%
Dash Punctuation 3
 
1.6%
Uppercase Letter 2
 
1.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
식 7
 
4.5%
기 5
 
3.2%
학 4
 
2.6%
원 4
 
2.6%
육 4
 
2.6%
의 3
 
1.9%
방 3
 
1.9%
물 3
 
1.9%
시 3
 
1.9%
교 3
 
1.9%
Other values (84) 115
74.7%
Uppercase Letter
ValueCountFrequency (%)
P 1
50.0%
C 1
50.0%
Other Punctuation
ValueCountFrequency (%)
/ 23
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 3
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 154
84.6%
Common 26
 
14.3%
Latin 2
 
1.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
식 7
 
4.5%
기 5
 
3.2%
학 4
 
2.6%
원 4
 
2.6%
육 4
 
2.6%
의 3
 
1.9%
방 3
 
1.9%
물 3
 
1.9%
시 3
 
1.9%
교 3
 
1.9%
Other values (84) 115
74.7%
Common
ValueCountFrequency (%)
/ 23
88.5%
- 3
 
11.5%
Latin
ValueCountFrequency (%)
P 1
50.0%
C 1
50.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 154
84.6%
ASCII 28
 
15.4%

Most frequent character per block

ASCII
ValueCountFrequency (%)
/ 23
82.1%
- 3
 
10.7%
P 1
 
3.6%
C 1
 
3.6%
Hangul
ValueCountFrequency (%)
식 7
 
4.5%
기 5
 
3.2%
학 4
 
2.6%
원 4
 
2.6%
육 4
 
2.6%
의 3
 
1.9%
방 3
 
1.9%
물 3
 
1.9%
시 3
 
1.9%
교 3
 
1.9%
Other values (84) 115
74.7%

소비액
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct30
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean11045908
Minimum10335.59
Maximum2.3206834 × 108
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size402.0 B
2023-12-10T23:24:41.213645image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum10335.59
5-th percentile23065.591
Q1163185.07
median1164818.7
Q35202297
95-th percentile20315141
Maximum2.3206834 × 108
Range2.32058 × 108
Interquartile range (IQR)5039111.9

Descriptive statistics

Standard deviation42096185
Coefficient of variation (CV)3.8110207
Kurtosis28.902461
Mean11045908
Median Absolute Deviation (MAD)1140530.1
Skewness5.3379358
Sum3.3137725 × 108
Variance1.7720888 × 1015
MonotonicityNot monotonic
2023-12-10T23:24:41.395389image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=30)
ValueCountFrequency (%)
968756.95 1
 
3.3%
73423.73 1
 
3.3%
6560116.82 1
 
3.3%
236340.49 1
 
3.3%
232068335.33 1
 
3.3%
325006.05 1
 
3.3%
138799.93 1
 
3.3%
36519.08 1
 
3.3%
5079830.95 1
 
3.3%
5243118.97 1
 
3.3%
Other values (20) 20
66.7%
ValueCountFrequency (%)
10335.59 1
3.3%
12058.19 1
3.3%
36519.08 1
3.3%
50648.55 1
3.3%
73178.69 1
3.3%
73423.73 1
3.3%
118435.36 1
3.3%
138799.93 1
3.3%
236340.49 1
3.3%
237718.56 1
3.3%
ValueCountFrequency (%)
232068335.33 1
3.3%
26729894.1 1
3.3%
12474887.4 1
3.3%
8998692.11 1
3.3%
7099595.79 1
3.3%
6620995.25 1
3.3%
6560116.82 1
3.3%
5243118.97 1
3.3%
5079830.95 1
3.3%
4156025.77 1
3.3%

전체 인구
Real number (ℝ)

HIGH CORRELATION 

Distinct13
Distinct (%)43.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean72459.45
Minimum12286.66
Maximum145729.35
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size402.0 B
2023-12-10T23:24:41.543982image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum12286.66
5-th percentile16104.37
Q150530.71
median68328.21
Q383166.702
95-th percentile145729.35
Maximum145729.35
Range133442.69
Interquartile range (IQR)32635.993

Descriptive statistics

Standard deviation40397.486
Coefficient of variation (CV)0.55751852
Kurtosis-0.22607474
Mean72459.45
Median Absolute Deviation (MAD)19087.445
Skewness0.63590018
Sum2173783.5
Variance1.6319568 × 109
MonotonicityNot monotonic
2023-12-10T23:24:41.680948image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=13)
ValueCountFrequency (%)
145729.35 5
16.7%
69891.85 4
13.3%
49060.2 3
10.0%
20770.46 3
10.0%
59320.75 3
10.0%
70961.54 2
 
6.7%
12286.66 2
 
6.7%
54942.24 2
 
6.7%
67662.16 2
 
6.7%
87235.09 1
 
3.3%
Other values (3) 3
10.0%
ValueCountFrequency (%)
12286.66 2
6.7%
20770.46 3
10.0%
49060.2 3
10.0%
54942.24 2
6.7%
59320.75 3
10.0%
67662.16 2
6.7%
68994.26 1
 
3.3%
69891.85 4
13.3%
70961.54 2
6.7%
87235.09 1
 
3.3%
ValueCountFrequency (%)
145729.35 5
16.7%
107976.47 1
 
3.3%
102204.11 1
 
3.3%
87235.09 1
 
3.3%
70961.54 2
 
6.7%
69891.85 4
13.3%
68994.26 1
 
3.3%
67662.16 2
 
6.7%
59320.75 3
10.0%
54942.24 2
 
6.7%

1인당 소비액
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct30
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean175.58133
Minimum0.07
Maximum3320.39
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size402.0 B
2023-12-10T23:24:41.801363image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0.07
5-th percentile0.554
Q12.3375
median17.97
Q393.4075
95-th percentile390.499
Maximum3320.39
Range3320.32
Interquartile range (IQR)91.07

Descriptive statistics

Standard deviation602.85731
Coefficient of variation (CV)3.4334932
Kurtosis28.080129
Mean175.58133
Median Absolute Deviation (MAD)17.41
Skewness5.2329323
Sum5267.44
Variance363436.94
MonotonicityNot monotonic
2023-12-10T23:24:41.921543image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=30)
ValueCountFrequency (%)
19.75 1
 
3.3%
0.5 1
 
3.3%
95.08 1
 
3.3%
3.38 1
 
3.3%
3320.39 1
 
3.3%
4.65 1
 
3.3%
1.99 1
 
3.3%
0.62 1
 
3.3%
85.63 1
 
3.3%
88.39 1
 
3.3%
Other values (20) 20
66.7%
ValueCountFrequency (%)
0.07 1
3.3%
0.5 1
3.3%
0.62 1
3.3%
0.81 1
3.3%
0.92 1
3.3%
0.98 1
3.3%
1.63 1
3.3%
1.99 1
3.3%
3.38 1
3.3%
3.52 1
3.3%
ValueCountFrequency (%)
3320.39 1
3.3%
433.24 1
3.3%
338.26 1
3.3%
184.37 1
3.3%
183.42 1
3.3%
150.81 1
3.3%
100.05 1
3.3%
95.08 1
3.3%
88.39 1
3.3%
85.63 1
3.3%

1인당 소비액 표준편차
Categorical

CONSTANT 

Distinct1
Distinct (%)3.3%
Missing0
Missing (%)0.0%
Memory size372.0 B
555.96
30 

Length

Max length6
Median length6
Mean length6
Min length6

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row555.96
2nd row555.96
3rd row555.96
4th row555.96
5th row555.96

Common Values

ValueCountFrequency (%)
555.96 30
100.0%

Length

2023-12-10T23:24:42.066088image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T23:24:42.161057image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
555.96 30
100.0%

유동 인구 소비융합지수
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct30
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean31.582333
Minimum0.01
Maximum597.24
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size402.0 B
2023-12-10T23:24:42.260462image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0.01
5-th percentile0.099
Q10.4225
median3.23
Q316.8
95-th percentile70.2395
Maximum597.24
Range597.23
Interquartile range (IQR)16.3775

Descriptive statistics

Standard deviation108.43608
Coefficient of variation (CV)3.433441
Kurtosis28.080182
Mean31.582333
Median Absolute Deviation (MAD)3.13
Skewness5.2329397
Sum947.47
Variance11758.383
MonotonicityNot monotonic
2023-12-10T23:24:42.462941image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=30)
ValueCountFrequency (%)
3.55 1
 
3.3%
0.09 1
 
3.3%
17.1 1
 
3.3%
0.61 1
 
3.3%
597.24 1
 
3.3%
0.84 1
 
3.3%
0.36 1
 
3.3%
0.11 1
 
3.3%
15.4 1
 
3.3%
15.9 1
 
3.3%
Other values (20) 20
66.7%
ValueCountFrequency (%)
0.01 1
3.3%
0.09 1
3.3%
0.11 1
3.3%
0.15 1
3.3%
0.17 1
3.3%
0.18 1
3.3%
0.29 1
3.3%
0.36 1
3.3%
0.61 1
3.3%
0.63 1
3.3%
ValueCountFrequency (%)
597.24 1
3.3%
77.93 1
3.3%
60.84 1
3.3%
33.16 1
3.3%
32.99 1
3.3%
27.13 1
3.3%
18.0 1
3.3%
17.1 1
3.3%
15.9 1
3.3%
15.4 1
3.3%

Interactions

2023-12-10T23:24:37.818387image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T23:24:35.577493image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T23:24:36.288474image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T23:24:36.721696image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T23:24:37.264859image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T23:24:37.938575image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T23:24:35.660903image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T23:24:36.373975image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T23:24:36.837672image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T23:24:37.366940image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T23:24:38.058658image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T23:24:35.738604image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T23:24:36.461384image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T23:24:36.954635image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T23:24:37.449023image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T23:24:38.189304image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T23:24:35.829981image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T23:24:36.541325image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T23:24:37.061459image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T23:24:37.588306image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T23:24:38.318763image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T23:24:35.918251image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T23:24:36.628981image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T23:24:37.172834image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T23:24:37.695750image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-10T23:24:42.566694image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
시군구명행정동명행정동 코드대분류중분류소비액전체 인구1인당 소비액유동 인구 소비융합지수
시군구명1.0001.0000.9930.3500.0000.0000.8350.1520.152
행정동명1.0001.0001.0000.0000.8840.0001.0000.0000.000
행정동 코드0.9931.0001.0000.3450.6420.0000.6140.1490.149
대분류0.3500.0000.3451.0001.0000.0000.0000.3280.328
중분류0.0000.8840.6421.0001.0000.0000.0000.0000.000
소비액0.0000.0000.0000.0000.0001.0000.0000.9320.932
전체 인구0.8351.0000.6140.0000.0000.0001.0000.0000.000
1인당 소비액0.1520.0000.1490.3280.0000.9320.0001.0001.000
유동 인구 소비융합지수0.1520.0000.1490.3280.0000.9320.0001.0001.000
2023-12-10T23:24:42.728219image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
행정동명대분류시군구명
행정동명1.0000.0000.779
대분류0.0001.0000.215
시군구명0.7790.2151.000
2023-12-10T23:24:42.882628image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
행정동 코드소비액전체 인구1인당 소비액유동 인구 소비융합지수시군구명행정동명대분류
행정동 코드1.0000.044-0.8580.2970.2970.9280.7790.215
소비액0.0441.000-0.0590.9490.9490.0000.0000.000
전체 인구-0.858-0.0591.000-0.314-0.3140.6240.8790.000
1인당 소비액0.2970.949-0.3141.0001.0000.2420.0000.178
유동 인구 소비융합지수0.2970.949-0.3141.0001.0000.2420.0000.178
시군구명0.9280.0000.6240.2420.2421.0000.7790.215
행정동명0.7790.0000.8790.0000.0000.7791.0000.000
대분류0.2150.0000.0000.1780.1780.2150.0001.000

Missing values

2023-12-10T23:24:38.514570image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-10T23:24:38.766714image/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 코드대분류중분류소비액전체 인구1인당 소비액1인당 소비액 표준편차유동 인구 소비융합지수
02019-01경기도가평군가평읍4182025000소매의복968756.9549060.219.75555.963.55
12019-01경기도가평군가평읍4182025000소매사진/광학/정밀기기794438.5849060.216.19555.962.91
22019-01경기도가평군가평읍4182025000학문/교육학원-보습교습입시3493671.5549060.271.21555.9612.81
32019-01경기도가평군상면4182033000음식중식73178.6920770.463.52555.960.63
42019-01경기도가평군상면4182033000스포츠운동시설3132396.8920770.46150.81555.9627.13
52019-01경기도가평군상면4182033000음식한식8998692.1120770.46433.24555.9677.93
62019-01경기도가평군설악면4182031000관광/여가/오락PC/오락/당구/볼링등349719.3870961.544.93555.960.89
72019-01경기도가평군설악면4182031000음식분식7099595.7970961.54100.05555.9618.0
82019-01경기도가평군조종면4182034500소매철물/난방/건설자재소매12058.1912286.660.98555.960.18
92019-01경기도가평군조종면4182034500음식별식/퓨전요리4156025.7712286.66338.26555.9660.84
기준년월시도명시군구명행정동명행정동 코드대분류중분류소비액전체 인구1인당 소비액1인당 소비액 표준편차유동 인구 소비융합지수
202019-01경기도고양시대화동4128757000음식다방/커피숍/카페12474887.467662.16184.37555.9633.16
212019-01경기도고양시대화동4128757000학문/교육기타교육기관2653249.2467662.1639.21555.967.05
222019-01경기도고양시마두1동4128556000음식일식5243118.9759320.7588.39555.9615.9
232019-01경기도고양시마두1동4128556000의료수의업5079830.9559320.7585.63555.9615.4
242019-01경기도고양시마두1동4128556000학문/교육유아교육36519.0859320.750.62555.960.11
252019-01경기도고양시백석1동4128555100소매취미/오락관련소매138799.9369891.851.99555.960.36
262019-01경기도고양시백석1동4128555100생활서비스운송/배달/택배325006.0569891.854.65555.960.84
272019-01경기도고양시백석1동4128555100의료병원232068335.3369891.853320.39555.96597.24
282019-01경기도고양시백석1동4128555100학문/교육학원-예능취미체육236340.4969891.853.38555.960.61
292019-01경기도고양시백석2동4128555200의료약국/한약방6560116.8268994.2695.08555.9617.1