Overview

Dataset statistics

Number of variables11
Number of observations10000
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory986.3 KiB
Average record size in memory101.0 B

Variable types

Categorical6
Numeric5

Dataset

Description제주도 내 상권분석을 위한 유동인구에 따른 카드 매출액 변화 데이터 활용 매쉬업 결과 정보입니다. - 읍면동, 업종명, 이용금액, 거주인구 등 정보 제공 - 거주인구, 근무인구, 방문인구는 해당 유동인구 수의 연월별 합계 ※ 유동인구는 01~24시 해당 시간 정각 측정 인구 (머문 시간(분)/60분) - 제주빅데이터센터 데이터 활용
Author제주데이터허브
URLhttps://www.jejudatahub.net/data/view/data/748

Alerts

데이터기준일자 has constant value ""Constant
읍면동명 is highly overall correlated with 거주인구 and 3 other fieldsHigh correlation
시도명 is highly overall correlated with 읍면동명High correlation
이용자수 is highly overall correlated with 이용금액High correlation
이용금액 is highly overall correlated with 이용자수High correlation
거주인구 is highly overall correlated with 근무인구 and 2 other fieldsHigh correlation
근무인구 is highly overall correlated with 거주인구 and 2 other fieldsHigh correlation
방문인구 is highly overall correlated with 거주인구 and 2 other fieldsHigh correlation

Reproduction

Analysis started2023-12-11 19:53:38.591773
Analysis finished2023-12-11 19:53:45.052578
Duration6.46 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

년월
Categorical

Distinct12
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2018-12-01
862 
2018-05-01
849 
2018-02-01
848 
2018-11-01
846 
2018-10-01
844 
Other values (7)
5751 

Length

Max length10
Median length10
Mean length10
Min length10

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2018-04-01
2nd row2018-02-01
3rd row2018-12-01
4th row2018-09-01
5th row2018-05-01

Common Values

ValueCountFrequency (%)
2018-12-01 862
8.6%
2018-05-01 849
8.5%
2018-02-01 848
8.5%
2018-11-01 846
8.5%
2018-10-01 844
8.4%
2018-06-01 842
8.4%
2018-01-01 840
8.4%
2018-04-01 837
8.4%
2018-03-01 829
8.3%
2018-08-01 814
8.1%
Other values (2) 1589
15.9%

Length

2023-12-12T04:53:45.589371image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
2018-12-01 862
8.6%
2018-05-01 849
8.5%
2018-02-01 848
8.5%
2018-11-01 846
8.5%
2018-10-01 844
8.4%
2018-06-01 842
8.4%
2018-01-01 840
8.4%
2018-04-01 837
8.4%
2018-03-01 829
8.3%
2018-08-01 814
8.1%
Other values (2) 1589
15.9%

시도명
Categorical

HIGH CORRELATION 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
제주시
5939 
서귀포시
4061 

Length

Max length4
Median length3
Mean length3.4061
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row서귀포시
2nd row서귀포시
3rd row서귀포시
4th row제주시
5th row서귀포시

Common Values

ValueCountFrequency (%)
제주시 5939
59.4%
서귀포시 4061
40.6%

Length

2023-12-12T04:53:45.807656image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T04:53:46.003793image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
제주시 5939
59.4%
서귀포시 4061
40.6%

읍면동명
Categorical

HIGH CORRELATION 

Distinct43
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
노형동
 
324
연동
 
297
애월읍
 
286
중문동
 
274
대륜동
 
269
Other values (38)
8550 

Length

Max length4
Median length3
Mean length3.1531
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row정방동
2nd row표선면
3rd row중문동
4th row삼도2동
5th row성산읍

Common Values

ValueCountFrequency (%)
노형동 324
 
3.2%
연동 297
 
3.0%
애월읍 286
 
2.9%
중문동 274
 
2.7%
대륜동 269
 
2.7%
성산읍 268
 
2.7%
송산동 268
 
2.7%
천지동 262
 
2.6%
조천읍 262
 
2.6%
한림읍 259
 
2.6%
Other values (33) 7231
72.3%

Length

2023-12-12T04:53:46.201757image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
노형동 324
 
3.2%
연동 297
 
3.0%
애월읍 286
 
2.9%
중문동 274
 
2.7%
대륜동 269
 
2.7%
성산읍 268
 
2.7%
송산동 268
 
2.7%
천지동 262
 
2.6%
조천읍 262
 
2.6%
한림읍 259
 
2.6%
Other values (33) 7231
72.3%

업종명
Categorical

Distinct41
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
중식 음식점업
 
411
체인화 편의점
 
397
차량용 주유소 운영업
 
395
한식 음식점업
 
388
스포츠 및 레크레이션 용품 임대업
 
383
Other values (36)
8026 

Length

Max length23
Median length18
Mean length9.3781
Min length3

Unique

Unique2 ?
Unique (%)< 0.1%

Sample

1st row슈퍼마켓
2nd row수산물 소매업
3rd row육류 소매업
4th row수산물 소매업
5th row한식 음식점업

Common Values

ValueCountFrequency (%)
중식 음식점업 411
 
4.1%
체인화 편의점 397
 
4.0%
차량용 주유소 운영업 395
 
4.0%
한식 음식점업 388
 
3.9%
스포츠 및 레크레이션 용품 임대업 383
 
3.8%
수산물 소매업 381
 
3.8%
서양식 음식점업 381
 
3.8%
과실 및 채소 소매업 378
 
3.8%
슈퍼마켓 376
 
3.8%
육류 소매업 373
 
3.7%
Other values (31) 6137
61.4%

Length

2023-12-12T04:53:46.423671image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
소매업 2685
 
10.1%
및 2364
 
8.9%
음식점업 2207
 
8.3%
기타 1197
 
4.5%
운영업 745
 
2.8%
차량용 689
 
2.6%
주점업 573
 
2.2%
임대업 516
 
1.9%
그외 425
 
1.6%
중식 411
 
1.6%
Other values (59) 14674
55.4%

성별
Categorical

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
남성
5048 
여성
4952 

Length

Max length2
Median length2
Mean length2
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row남성
2nd row남성
3rd row남성
4th row남성
5th row여성

Common Values

ValueCountFrequency (%)
남성 5048
50.5%
여성 4952
49.5%

Length

2023-12-12T04:53:46.594837image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T04:53:46.742728image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
남성 5048
50.5%
여성 4952
49.5%

이용자수
Real number (ℝ)

HIGH CORRELATION 

Distinct3323
Distinct (%)33.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1794.4129
Minimum1
Maximum58298
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2023-12-12T04:53:46.899994image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile3
Q149
median302
Q31423
95-th percentile8181.15
Maximum58298
Range58297
Interquartile range (IQR)1374

Descriptive statistics

Standard deviation4490.6033
Coefficient of variation (CV)2.5025474
Kurtosis38.145013
Mean1794.4129
Median Absolute Deviation (MAD)292
Skewness5.4160878
Sum17944129
Variance20165518
MonotonicityNot monotonic
2023-12-12T04:53:47.076080image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 278
 
2.8%
2 188
 
1.9%
3 149
 
1.5%
4 107
 
1.1%
5 100
 
1.0%
6 90
 
0.9%
10 68
 
0.7%
8 67
 
0.7%
9 63
 
0.6%
7 59
 
0.6%
Other values (3313) 8831
88.3%
ValueCountFrequency (%)
1 278
2.8%
2 188
1.9%
3 149
1.5%
4 107
 
1.1%
5 100
 
1.0%
6 90
 
0.9%
7 59
 
0.6%
8 67
 
0.7%
9 63
 
0.6%
10 68
 
0.7%
ValueCountFrequency (%)
58298 1
< 0.1%
56760 1
< 0.1%
55584 1
< 0.1%
51625 1
< 0.1%
49414 1
< 0.1%
48921 1
< 0.1%
47127 1
< 0.1%
45366 1
< 0.1%
45240 1
< 0.1%
44534 1
< 0.1%

이용금액
Real number (ℝ)

HIGH CORRELATION 

Distinct9180
Distinct (%)91.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean64844155
Minimum10
Maximum4.3910021 × 109
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2023-12-12T04:53:47.279063image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum10
5-th percentile211000
Q12861595
median12978375
Q352739335
95-th percentile2.7738587 × 108
Maximum4.3910021 × 109
Range4.3910021 × 109
Interquartile range (IQR)49877740

Descriptive statistics

Standard deviation1.9687226 × 108
Coefficient of variation (CV)3.0360833
Kurtosis187.19216
Mean64844155
Median Absolute Deviation (MAD)12025625
Skewness11.214753
Sum6.4844155 × 1011
Variance3.8758685 × 1016
MonotonicityNot monotonic
2023-12-12T04:53:47.487455image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
300000 19
 
0.2%
100000 18
 
0.2%
1000000 16
 
0.2%
30000 12
 
0.1%
360000 12
 
0.1%
50000 11
 
0.1%
200000 10
 
0.1%
400000 10
 
0.1%
140000 9
 
0.1%
130000 9
 
0.1%
Other values (9170) 9874
98.7%
ValueCountFrequency (%)
10 1
< 0.1%
3000 1
< 0.1%
4000 2
< 0.1%
5000 2
< 0.1%
5500 1
< 0.1%
6000 1
< 0.1%
7000 2
< 0.1%
8000 1
< 0.1%
9000 1
< 0.1%
9200 1
< 0.1%
ValueCountFrequency (%)
4391002140 1
< 0.1%
4345519583 1
< 0.1%
4309621652 1
< 0.1%
4045929200 1
< 0.1%
4018183724 1
< 0.1%
4013452471 1
< 0.1%
4001553782 1
< 0.1%
3788967419 1
< 0.1%
3721220778 1
< 0.1%
3589002089 1
< 0.1%

거주인구
Real number (ℝ)

HIGH CORRELATION 

Distinct1032
Distinct (%)10.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean4664109.7
Minimum213253.17
Maximum19467053
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2023-12-12T04:53:47.692255image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum213253.17
5-th percentile402965.92
Q11221338.1
median3194734.5
Q35866142.9
95-th percentile16327005
Maximum19467053
Range19253800
Interquartile range (IQR)4644804.8

Descriptive statistics

Standard deviation4686196.1
Coefficient of variation (CV)1.0047354
Kurtosis1.5320498
Mean4664109.7
Median Absolute Deviation (MAD)2116611.8
Skewness1.5299541
Sum4.6641097 × 1010
Variance2.1960434 × 1013
MonotonicityNot monotonic
2023-12-12T04:53:47.888376image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
17017916.99 20
 
0.2%
13430836.84 19
 
0.2%
4464409.881 19
 
0.2%
2757162.07 18
 
0.2%
3089646.846000001 17
 
0.2%
4142818.862 17
 
0.2%
5277397.413 17
 
0.2%
2829743.893 17
 
0.2%
561886.33 16
 
0.2%
5908012.602000001 16
 
0.2%
Other values (1022) 9824
98.2%
ValueCountFrequency (%)
213253.169 9
0.1%
213398.466 13
0.1%
219401.158 13
0.1%
219840.339 13
0.1%
221094.292 13
0.1%
223108.432 10
0.1%
225844.784 8
0.1%
226380.076 13
0.1%
226467.081 12
0.1%
228373.353 7
0.1%
ValueCountFrequency (%)
19467052.8 9
0.1%
19199874.63 15
0.1%
19146042.33 14
0.1%
19138352.46 9
0.1%
19090066.16 11
0.1%
19038959.21 12
0.1%
19028369.03 9
0.1%
18992897.83 12
0.1%
18842018.01 7
0.1%
18391229.26 12
0.1%

근무인구
Real number (ℝ)

HIGH CORRELATION 

Distinct1032
Distinct (%)10.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean544376.26
Minimum2967.608
Maximum3437408.3
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2023-12-12T04:53:48.080048image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum2967.608
5-th percentile31915.676
Q1168553
median303409.97
Q3600189.61
95-th percentile2113166.7
Maximum3437408.3
Range3434440.7
Interquartile range (IQR)431636.61

Descriptive statistics

Standard deviation625802.81
Coefficient of variation (CV)1.1495777
Kurtosis3.6645011
Mean544376.26
Median Absolute Deviation (MAD)182789.65
Skewness2.0442727
Sum5.4437626 × 109
Variance3.9162915 × 1011
MonotonicityNot monotonic
2023-12-12T04:53:48.268329image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
2226804.913 20
 
0.2%
1460704.35 19
 
0.2%
475355.838 19
 
0.2%
260975.58 18
 
0.2%
287131.482 17
 
0.2%
514682.92 17
 
0.2%
320704.932 17
 
0.2%
270851.029 17
 
0.2%
32340.602000000006 16
 
0.2%
426007.634 16
 
0.2%
Other values (1022) 9824
98.2%
ValueCountFrequency (%)
2967.608 4
< 0.1%
5913.985 2
 
< 0.1%
6635.201999999998 3
< 0.1%
6856.399 1
 
< 0.1%
7019.6590000000015 6
0.1%
7225.915 4
< 0.1%
8255.918 4
< 0.1%
8283.974 3
< 0.1%
10596.408 3
< 0.1%
11497.749 3
< 0.1%
ValueCountFrequency (%)
3437408.315 10
0.1%
3363620.957 10
0.1%
3040767.155 10
0.1%
3022343.935 7
0.1%
2981939.649 12
0.1%
2919056.784 15
0.1%
2894276.7610000004 11
0.1%
2812190.255 11
0.1%
2752951.568 12
0.1%
2742973.072 9
0.1%

방문인구
Real number (ℝ)

HIGH CORRELATION 

Distinct1032
Distinct (%)10.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2883430.2
Minimum216134.01
Maximum9916068.1
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2023-12-12T04:53:48.420774image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum216134.01
5-th percentile572308.46
Q11437124.4
median2249571.1
Q33560749.7
95-th percentile8087304.4
Maximum9916068.1
Range9699934.1
Interquartile range (IQR)2123625.3

Descriptive statistics

Standard deviation2138909
Coefficient of variation (CV)0.74179323
Kurtosis1.4112751
Mean2883430.2
Median Absolute Deviation (MAD)953664.98
Skewness1.4414614
Sum2.8834302 × 1010
Variance4.5749317 × 1012
MonotonicityNot monotonic
2023-12-12T04:53:48.585243image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
8319719.981000002 20
 
0.2%
7682651.956 19
 
0.2%
2888155.74 19
 
0.2%
1980737.547 18
 
0.2%
2270733.005 17
 
0.2%
3091138.703 17
 
0.2%
2135243.93 17
 
0.2%
1877488.439 17
 
0.2%
560607.698 16
 
0.2%
2235881.592 16
 
0.2%
Other values (1022) 9824
98.2%
ValueCountFrequency (%)
216134.009 9
0.1%
225378.253 1
 
< 0.1%
226302.016 3
 
< 0.1%
236683.042 6
0.1%
238853.185 6
0.1%
261658.388 3
 
< 0.1%
278129.635 4
< 0.1%
291059.503 9
0.1%
305737.68100000004 3
 
< 0.1%
311433.79600000003 2
 
< 0.1%
ValueCountFrequency (%)
9916068.083 9
0.1%
9672143.105 11
0.1%
9481340.19 10
0.1%
9450680.221 11
0.1%
9321998.543 15
0.1%
9285792.902 11
0.1%
9174876.077 10
0.1%
9158670.365 13
0.1%
9122711.298 13
0.1%
9013636.648 9
0.1%

데이터기준일자
Categorical

CONSTANT 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2020-12-15
10000 

Length

Max length10
Median length10
Mean length10
Min length10

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2020-12-15
2nd row2020-12-15
3rd row2020-12-15
4th row2020-12-15
5th row2020-12-15

Common Values

ValueCountFrequency (%)
2020-12-15 10000
100.0%

Length

2023-12-12T04:53:48.726232image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T04:53:48.818166image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2020-12-15 10000
100.0%

Interactions

2023-12-12T04:53:43.732498image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T04:53:40.378174image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T04:53:41.019474image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T04:53:41.776051image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T04:53:42.761523image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T04:53:43.888107image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T04:53:40.524252image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T04:53:41.149807image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T04:53:41.950560image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T04:53:42.980854image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T04:53:44.058974image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T04:53:40.650116image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T04:53:41.270387image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T04:53:42.121956image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T04:53:43.162158image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T04:53:44.247423image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T04:53:40.779395image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T04:53:41.436407image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T04:53:42.337188image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T04:53:43.368032image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T04:53:44.412289image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T04:53:40.913703image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T04:53:41.634215image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T04:53:42.545559image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T04:53:43.549474image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-12T04:53:48.890388image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
년월시도명읍면동명업종명성별이용자수이용금액거주인구근무인구방문인구
년월1.0000.0000.0000.0000.0000.0000.0000.0970.2090.216
시도명0.0001.0001.0000.1310.0000.0790.0710.6160.4640.539
읍면동명0.0001.0001.0000.4210.0000.3390.3310.9660.8860.931
업종명0.0000.1310.4211.0000.0000.5920.7400.2370.1720.197
성별0.0000.0000.0000.0001.0000.0820.0600.2850.3120.275
이용자수0.0000.0790.3390.5920.0821.0000.6970.3410.3030.294
이용금액0.0000.0710.3310.7400.0600.6971.0000.2120.2010.191
거주인구0.0970.6160.9660.2370.2850.3410.2121.0000.8860.876
근무인구0.2090.4640.8860.1720.3120.3030.2010.8861.0000.867
방문인구0.2160.5390.9310.1970.2750.2940.1910.8760.8671.000
2023-12-12T04:53:49.038908image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
성별읍면동명년월시도명업종명
성별1.0000.0000.0000.0000.000
읍면동명0.0001.0000.0000.9980.090
년월0.0000.0001.0000.0000.000
시도명0.0000.9980.0001.0000.110
업종명0.0000.0900.0000.1101.000
2023-12-12T04:53:49.153538image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
이용자수이용금액거주인구근무인구방문인구년월시도명읍면동명업종명성별
이용자수1.0000.9120.0920.1200.1190.0000.0610.1230.2460.063
이용금액0.9121.0000.1230.1590.1660.0000.0530.1320.3890.045
거주인구0.0920.1231.0000.8760.8580.0400.4770.7870.0830.218
근무인구0.1200.1590.8761.0000.9330.0890.3560.5580.0600.239
방문인구0.1190.1660.8580.9331.0000.0920.4150.6660.0690.211
년월0.0000.0000.0400.0890.0921.0000.0000.0000.0000.000
시도명0.0610.0530.4770.3560.4150.0001.0000.9980.1100.000
읍면동명0.1230.1320.7870.5580.6660.0000.9981.0000.0900.000
업종명0.2460.3890.0830.0600.0690.0000.1100.0901.0000.000
성별0.0630.0450.2180.2390.2110.0000.0000.0000.0001.000

Missing values

2023-12-12T04:53:44.622636image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-12T04:53:44.924607image/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

년월시도명읍면동명업종명성별이용자수이용금액거주인구근무인구방문인구데이터기준일자
73412018-04-01서귀포시정방동슈퍼마켓남성389363950250624443.328119246.4421439513.0582020-12-15
30702018-02-01서귀포시표선면수산물 소매업남성243187690002829743.893270851.0291877488.4392020-12-15
255662018-12-01서귀포시중문동육류 소매업남성1270002866793.837265745.8671765529.7992020-12-15
193252018-09-01제주시삼도2동수산물 소매업남성596556001474095.824153513.9772084023.62020-12-15
93862018-05-01서귀포시성산읍한식 음식점업여성99684549086003796360.852225576.1023440399.6552020-12-15
260692018-12-01제주시아라동기타 외국식 음식점업남성8572328828012407192.851722756.6354387350.5942020-12-15
247372018-11-01제주시조천읍체인화 편의점여성7144710937206085454.983581740.7253741559.3132020-12-15
79492018-04-01제주시아라동슈퍼마켓남성1529427169475011806145.312290300.494799434.0452020-12-15
76552018-04-01제주시노형동화장품 및 방향제 소매업여성7264887063017684482.722211734.0847096947.7272020-12-15
196552018-09-01제주시오라동차량용 주유소 운영업여성34971577485834394878.956395192.3083518785.1812020-12-15
년월시도명읍면동명업종명성별이용자수이용금액거주인구근무인구방문인구데이터기준일자
31852018-02-01제주시건입동체인화 편의점남성6840627863502269540.354345884.9882454989.7742020-12-15
234642018-11-01서귀포시표선면그외 기타 종합 소매업남성317800003092265.073372820.2142181496.7662020-12-15
55312018-03-01제주시노형동일반유흥 주점업남성3784686250015957811.251658369.6138715472.5362020-12-15
240802018-11-01제주시용담2동빵 및 과자류 소매업여성1886216199903418431.576943700.3783686837.4832020-12-15
112302018-05-01제주시화북동건강보조식품 소매업남성2948366108048314.7891333269.2653347152.1652020-12-15
197282018-09-01제주시용담1동욕탕업남성95400002028443.509191715.6631501244.0662020-12-15
48312018-03-01서귀포시송산동슈퍼마켓여성14603394586200544988.14930946.818461049.0752020-12-15
120502018-06-01서귀포시천지동비알콜 음료점업남성259426393610226467.08130692.63642132.6572020-12-15
241292018-11-01제주시연동면세점여성945105597815523299.492087077.3787141387.4532020-12-15
148842018-07-01제주시삼양동화장품 및 방향제 소매업여성361104044617183083.239299782.2791789571.6352020-12-15