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 19:53:50.796041
Analysis finished2023-12-11 19:53:57.841314
Duration7.05 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
2019-06-01
876 
2019-04-01
869 
2019-05-01
858 
2019-07-01
852 
2019-12-01
845 
Other values (7)
5700 

Length

Max length10
Median length10
Mean length10
Min length10

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2019-06-01
2nd row2019-10-01
3rd row2019-01-01
4th row2019-02-01
5th row2019-12-01

Common Values

ValueCountFrequency (%)
2019-06-01 876
8.8%
2019-04-01 869
8.7%
2019-05-01 858
8.6%
2019-07-01 852
8.5%
2019-12-01 845
8.5%
2019-03-01 841
8.4%
2019-08-01 830
8.3%
2019-10-01 825
8.2%
2019-11-01 812
8.1%
2019-01-01 810
8.1%
Other values (2) 1582
15.8%

Length

2023-12-12T04:53:57.923259image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
2019-06-01 876
8.8%
2019-04-01 869
8.7%
2019-05-01 858
8.6%
2019-07-01 852
8.5%
2019-12-01 845
8.5%
2019-03-01 841
8.4%
2019-08-01 830
8.3%
2019-10-01 825
8.2%
2019-11-01 812
8.1%
2019-01-01 810
8.1%
Other values (2) 1582
15.8%

시도명
Categorical

HIGH CORRELATION 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
제주시
5994 
서귀포시
4006 

Length

Max length4
Median length3
Mean length3.4006
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
제주시 5994
59.9%
서귀포시 4006
40.1%

Length

2023-12-12T04:53:58.077223image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T04:53:58.180602image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
제주시 5994
59.9%
서귀포시 4006
40.1%

읍면동명
Categorical

HIGH CORRELATION 

Distinct43
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
연동
 
313
노형동
 
299
애월읍
 
286
조천읍
 
274
정방동
 
273
Other values (38)
8555 

Length

Max length4
Median length3
Mean length3.159
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row이호동
2nd row성산읍
3rd row한경면
4th row이도1동
5th row건입동

Common Values

ValueCountFrequency (%)
연동 313
 
3.1%
노형동 299
 
3.0%
애월읍 286
 
2.9%
조천읍 274
 
2.7%
정방동 273
 
2.7%
천지동 273
 
2.7%
송산동 271
 
2.7%
중문동 270
 
2.7%
이도2동 269
 
2.7%
성산읍 266
 
2.7%
Other values (33) 7206
72.1%

Length

2023-12-12T04:53:58.311707image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
연동 313
 
3.1%
노형동 299
 
3.0%
애월읍 286
 
2.9%
조천읍 274
 
2.7%
정방동 273
 
2.7%
천지동 273
 
2.7%
송산동 271
 
2.7%
중문동 270
 
2.7%
이도2동 269
 
2.7%
성산읍 266
 
2.7%
Other values (33) 7206
72.1%

업종명
Categorical

Distinct40
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
서양식 음식점업
 
418
비알콜 음료점업
 
392
한식 음식점업
 
390
체인화 편의점
 
374
중식 음식점업
 
372
Other values (35)
8054 

Length

Max length23
Median length17
Mean length9.2976
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row한식 음식점업
2nd row육류 소매업
3rd row기타음식료품위주종합소매업
4th row일반유흥 주점업
5th row면세점

Common Values

ValueCountFrequency (%)
서양식 음식점업 418
 
4.2%
비알콜 음료점업 392
 
3.9%
한식 음식점업 390
 
3.9%
체인화 편의점 374
 
3.7%
중식 음식점업 372
 
3.7%
빵 및 과자류 소매업 371
 
3.7%
수산물 소매업 370
 
3.7%
일식 음식점업 365
 
3.6%
과실 및 채소 소매업 362
 
3.6%
욕탕업 355
 
3.5%
Other values (30) 6231
62.3%

Length

2023-12-12T04:53:58.488296image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
소매업 2685
 
10.2%
및 2301
 
8.8%
음식점업 2190
 
8.3%
기타 1218
 
4.6%
운영업 678
 
2.6%
차량용 656
 
2.5%
주점업 545
 
2.1%
임대업 486
 
1.9%
그외 453
 
1.7%
서양식 418
 
1.6%
Other values (58) 14601
55.7%

성별
Categorical

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
여성
5008 
남성
4992 

Length

Max length2
Median length2
Mean length2
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
여성 5008
50.1%
남성 4992
49.9%

Length

2023-12-12T04:53:58.745888image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T04:53:58.883395image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
여성 5008
50.1%
남성 4992
49.9%

이용자수
Real number (ℝ)

HIGH CORRELATION 

Distinct3305
Distinct (%)33.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1795.05
Minimum1
Maximum70060
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2023-12-12T04:53:59.039095image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile2
Q147
median283
Q31403.25
95-th percentile8317.65
Maximum70060
Range70059
Interquartile range (IQR)1356.25

Descriptive statistics

Standard deviation4589.7257
Coefficient of variation (CV)2.556879
Kurtosis46.678547
Mean1795.05
Median Absolute Deviation (MAD)275
Skewness5.8495025
Sum17950500
Variance21065582
MonotonicityNot monotonic
2023-12-12T04:53:59.225826image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 301
 
3.0%
2 225
 
2.2%
3 147
 
1.5%
5 109
 
1.1%
4 108
 
1.1%
6 92
 
0.9%
7 75
 
0.8%
8 73
 
0.7%
10 72
 
0.7%
9 69
 
0.7%
Other values (3295) 8729
87.3%
ValueCountFrequency (%)
1 301
3.0%
2 225
2.2%
3 147
1.5%
4 108
 
1.1%
5 109
 
1.1%
6 92
 
0.9%
7 75
 
0.8%
8 73
 
0.7%
9 69
 
0.7%
10 72
 
0.7%
ValueCountFrequency (%)
70060 1
< 0.1%
65378 1
< 0.1%
63263 1
< 0.1%
58466 1
< 0.1%
57408 1
< 0.1%
55839 1
< 0.1%
51911 1
< 0.1%
50336 1
< 0.1%
47708 1
< 0.1%
47018 1
< 0.1%

이용금액
Real number (ℝ)

HIGH CORRELATION 

Distinct9174
Distinct (%)91.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean61477051
Minimum100
Maximum4.8163802 × 109
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2023-12-12T04:53:59.415636image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum100
5-th percentile180000
Q12782662.5
median12576625
Q348274312
95-th percentile2.6211502 × 108
Maximum4.8163802 × 109
Range4.8163801 × 109
Interquartile range (IQR)45491650

Descriptive statistics

Standard deviation1.946373 × 108
Coefficient of variation (CV)3.1660155
Kurtosis206.19745
Mean61477051
Median Absolute Deviation (MAD)11658425
Skewness12.007086
Sum6.1477051 × 1011
Variance3.7883677 × 1016
MonotonicityNot monotonic
2023-12-12T04:53:59.608391image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1000000 20
 
0.2%
50000 20
 
0.2%
100000 15
 
0.1%
30000 15
 
0.1%
200000 14
 
0.1%
160000 14
 
0.1%
300000 12
 
0.1%
90000 11
 
0.1%
80000 10
 
0.1%
10000 9
 
0.1%
Other values (9164) 9860
98.6%
ValueCountFrequency (%)
100 1
 
< 0.1%
3000 2
 
< 0.1%
5000 5
0.1%
7000 2
 
< 0.1%
8000 2
 
< 0.1%
9000 2
 
< 0.1%
10000 9
0.1%
10370 1
 
< 0.1%
11000 4
< 0.1%
11400 1
 
< 0.1%
ValueCountFrequency (%)
4816380183 1
< 0.1%
4440910748 1
< 0.1%
3970084104 1
< 0.1%
3912078532 1
< 0.1%
3855243012 1
< 0.1%
3839193071 1
< 0.1%
3751274593 1
< 0.1%
3749433105 1
< 0.1%
3606498961 1
< 0.1%
3542584434 1
< 0.1%

거주인구
Real number (ℝ)

HIGH CORRELATION 

Distinct1032
Distinct (%)10.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean4722758.7
Minimum185817.58
Maximum19352085
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2023-12-12T04:53:59.809151image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum185817.58
5-th percentile385533.43
Q11255678.8
median3253482.6
Q36114788.2
95-th percentile15659820
Maximum19352085
Range19166268
Interquartile range (IQR)4859109.4

Descriptive statistics

Standard deviation4612861.6
Coefficient of variation (CV)0.97673033
Kurtosis1.2160295
Mean4722758.7
Median Absolute Deviation (MAD)2193534.9
Skewness1.4281522
Sum4.7227587 × 1010
Variance2.1278492 × 1013
MonotonicityNot monotonic
2023-12-12T04:53:59.998227image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
15504269.03 19
 
0.2%
10856882.63 18
 
0.2%
10782188.76 18
 
0.2%
13905538.49 17
 
0.2%
15149020.7 17
 
0.2%
2708768.275 17
 
0.2%
14090484.83 17
 
0.2%
10880308.3 17
 
0.2%
5620829.033 17
 
0.2%
6258044.257 17
 
0.2%
Other values (1022) 9826
98.3%
ValueCountFrequency (%)
185817.575 10
0.1%
190564.986 6
0.1%
191908.037 14
0.1%
192693.778 13
0.1%
194248.202 12
0.1%
197786.853 12
0.1%
198207.466 13
0.1%
201361.915 8
0.1%
206430.637 7
0.1%
208970.796 12
0.1%
ValueCountFrequency (%)
19352085.34 10
0.1%
19145721.99 16
0.2%
18897441.71 11
0.1%
18421167.86 13
0.1%
18405498.61 17
0.2%
18348701.93 15
0.1%
18226719.4 7
0.1%
18160160.56 13
0.1%
18124222.88 14
0.1%
18080014.54 13
0.1%

근무인구
Real number (ℝ)

HIGH CORRELATION 

Distinct1032
Distinct (%)10.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean552168.93
Minimum3301.481
Maximum3275360
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2023-12-12T04:54:00.199695image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum3301.481
5-th percentile33357.813
Q1172265.23
median319047.5
Q3602260.68
95-th percentile2081647.8
Maximum3275360
Range3272058.6
Interquartile range (IQR)429995.45

Descriptive statistics

Standard deviation627793.25
Coefficient of variation (CV)1.1369587
Kurtosis3.3382994
Mean552168.93
Median Absolute Deviation (MAD)205764.4
Skewness1.9790896
Sum5.5216893 × 109
Variance3.9412436 × 1011
MonotonicityNot monotonic
2023-12-12T04:54:00.409094image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1963645.948 19
 
0.2%
1444599.2869999998 18
 
0.2%
860492.553 18
 
0.2%
1956756.226 17
 
0.2%
2262903.751 17
 
0.2%
227993.159 17
 
0.2%
3043785.067 17
 
0.2%
1002922.709 17
 
0.2%
422080.598 17
 
0.2%
814030.6440000002 17
 
0.2%
Other values (1022) 9826
98.3%
ValueCountFrequency (%)
3301.481 5
0.1%
7533.6219999999985 5
0.1%
7603.1219999999985 5
0.1%
8330.804 5
0.1%
8713.513 3
< 0.1%
9425.755 5
0.1%
9750.506 7
0.1%
10715.673 7
0.1%
10896.112 4
< 0.1%
12902.112 6
0.1%
ValueCountFrequency (%)
3275360.034 11
0.1%
3251243.742 11
0.1%
3043785.067 17
0.2%
2932173.915 10
0.1%
2901765.0160000008 13
0.1%
2872824.2830000008 7
0.1%
2829636.622 13
0.1%
2725101.8010000004 13
0.1%
2722201.137 9
0.1%
2685439.958 15
0.1%

방문인구
Real number (ℝ)

HIGH CORRELATION 

Distinct1032
Distinct (%)10.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2922786.9
Minimum251028.65
Maximum9975291.3
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2023-12-12T04:54:00.619215image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum251028.65
5-th percentile566539.11
Q11421777.2
median2284575.3
Q33597041.8
95-th percentile8055783.2
Maximum9975291.3
Range9724262.6
Interquartile range (IQR)2175264.7

Descriptive statistics

Standard deviation2153754.4
Coefficient of variation (CV)0.73688381
Kurtosis1.0079455
Mean2922786.9
Median Absolute Deviation (MAD)1014677.2
Skewness1.3215947
Sum2.9227869 × 1010
Variance4.6386578 × 1012
MonotonicityNot monotonic
2023-12-12T04:54:00.822732image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
7468216.261 19
 
0.2%
8178566.342 18
 
0.2%
6523232.677999998 18
 
0.2%
8370081.459 17
 
0.2%
8290556.121 17
 
0.2%
1965062.092 17
 
0.2%
4652011.45 17
 
0.2%
6747223.262 17
 
0.2%
3528132.685 17
 
0.2%
4791595.508 17
 
0.2%
Other values (1022) 9826
98.3%
ValueCountFrequency (%)
251028.651 7
0.1%
275168.38300000003 4
 
< 0.1%
279864.895 4
 
< 0.1%
281188.096 7
0.1%
301279.899 12
0.1%
301697.269 5
0.1%
302999.327 5
0.1%
304398.373 5
0.1%
305131.51300000004 7
0.1%
315947.262 7
0.1%
ValueCountFrequency (%)
9975291.283 8
0.1%
9617632.271 15
0.1%
9293477.873 15
0.1%
9277162.684 13
0.1%
9039616.781 11
0.1%
9032547.797 10
0.1%
8894917.008 12
0.1%
8837433.499 14
0.1%
8836434.441 6
 
0.1%
8787576.825 8
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

2023-12-12T04:54:01.018315image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T04:54:01.141649image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2020-12-15 10000
100.0%

Interactions

2023-12-12T04:53:56.823394image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T04:53:52.896564image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T04:53:53.868165image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T04:53:54.786661image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T04:53:56.080257image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T04:53:56.948082image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T04:53:53.075552image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T04:53:54.051370image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T04:53:54.981803image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T04:53:56.213990image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T04:53:57.083616image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T04:53:53.270408image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T04:53:54.216369image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T04:53:55.187651image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T04:53:56.358145image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T04:53:57.239738image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T04:53:53.474348image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T04:53:54.414330image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T04:53:55.806062image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T04:53:56.530325image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T04:53:57.362170image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T04:53:53.672910image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T04:53:54.598861image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T04:53:55.940709image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T04:53:56.677690image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-12T04:54:01.239552image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
년월시도명읍면동명업종명성별이용자수이용금액거주인구근무인구방문인구
년월1.0000.0050.0000.0000.0000.0000.0140.1220.2160.231
시도명0.0051.0001.0000.1600.0000.0650.0610.6140.4690.561
읍면동명0.0001.0001.0000.4200.0000.3030.2880.9670.8880.934
업종명0.0000.1600.4201.0000.0000.5690.7620.2490.1660.210
성별0.0000.0000.0000.0001.0000.0730.0600.2360.2620.280
이용자수0.0000.0650.3030.5690.0731.0000.7980.2830.2600.276
이용금액0.0140.0610.2880.7620.0600.7981.0000.2490.2550.244
거주인구0.1220.6140.9670.2490.2360.2830.2491.0000.8920.877
근무인구0.2160.4690.8880.1660.2620.2600.2550.8921.0000.859
방문인구0.2310.5610.9340.2100.2800.2760.2440.8770.8591.000
2023-12-12T04:54:01.499281image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
성별읍면동명년월시도명업종명
성별1.0000.0000.0000.0000.000
읍면동명0.0001.0000.0000.9980.090
년월0.0000.0001.0000.0040.000
시도명0.0000.9980.0041.0000.127
업종명0.0000.0900.0000.1271.000
2023-12-12T04:54:01.657763image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
이용자수이용금액거주인구근무인구방문인구년월시도명읍면동명업종명성별
이용자수1.0000.9110.0740.1050.1140.0000.0500.1090.2160.056
이용금액0.9111.0000.1120.1440.1610.0060.0460.1030.3540.046
거주인구0.0740.1121.0000.8850.8620.0510.4750.7910.0820.181
근무인구0.1050.1440.8851.0000.9380.0920.3600.5620.0540.201
방문인구0.1140.1610.8620.9381.0000.0990.4320.6730.0690.215
년월0.0000.0060.0510.0920.0991.0000.0040.0000.0000.000
시도명0.0500.0460.4750.3600.4320.0041.0000.9980.1270.000
읍면동명0.1090.1030.7910.5620.6730.0000.9981.0000.0900.000
업종명0.2160.3540.0820.0540.0690.0000.1270.0901.0000.000
성별0.0560.0460.1810.2010.2150.0000.0000.0000.0001.000

Missing values

2023-12-12T04:53:57.542767image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-12T04:53:57.751056image/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
129262019-06-01제주시이호동한식 음식점업남성1346789292001052435.865123931.4241219995.882020-12-15
209262019-10-01서귀포시성산읍육류 소매업여성5642173004006659.515291471.6733523476.3272020-12-15
2012019-01-01제주시한경면기타음식료품위주종합소매업남성1636475533202129770.455214431.4621242081.6222020-12-15
44412019-02-01제주시이도1동일반유흥 주점업여성2995700002241976.476511746.4662687576.2022020-12-15
260732019-12-01제주시건입동면세점여성287195942202205347.574224861.2272106991.6872020-12-15
180882019-08-01제주시추자면과실 및 채소 소매업남성622778650492003.62249668.259654939.5022020-12-15
149122019-07-01제주시삼도1동차량용 주유소 운영업여성19290563003296321.551316703.2322168044.5582020-12-15
119672019-06-01서귀포시예래동차량용 주유소 운영업남성30201338248891012650.974326657.7232293125.0142020-12-15
203212019-09-01제주시조천읍비알콜 음료점업남성922108523206227596.757742696.7294161751.2072020-12-15
54602019-03-01제주시건입동육류 소매업남성11390281802101667.361312539.1322553998.8942020-12-15
년월시도명읍면동명업종명성별이용자수이용금액거주인구근무인구방문인구데이터기준일자
31542019-02-01제주시도두동자동차 임대업여성145166506114367950.96148779.7271157272.9962020-12-15
196342019-09-01제주시삼양동기타 외국식 음식점업여성22843376007026194.752229772.9871426120.3412020-12-15
9362019-01-01제주시삼양동피자, 햄버거, 샌드위치 및 유사 음식점업남성1386217560387372510.381268078.6131947804.1412020-12-15
175292019-08-01제주시오라동골프장 운영업여성386498257304595132.062460048.7743954181.4192020-12-15
23402019-02-01서귀포시남원읍골프장 운영업여성9151119159563653130.834239332.6222161952.6262020-12-15
164742019-08-01서귀포시안덕면중식 음식점업여성25477927004142465.617540683.0345114133.292020-12-15
201312019-09-01제주시이도2동그외 기타 종합 소매업여성11217000016805924.322388031.2487974368.1412020-12-15
271062019-12-01제주시일도1동체인화 편의점여성282434381910531185.588107756.1941207258.0342020-12-15
198822019-09-01제주시외도동비알콜 음료점업여성69757412923617092.854182735.5821470646.8462020-12-15
48602019-03-01서귀포시성산읍일반유흥 주점업남성425909480004556978.618442555.7063044277.482020-12-15