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

읍면동명 is highly overall correlated with 거주인구 and 3 other fieldsHigh correlation
년월 is highly overall correlated with 데이터기준일자High correlation
데이터기준일자 is highly overall correlated with 년월High 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 19:54:27.727908
Analysis finished2023-12-11 19:54:33.769754
Duration6.04 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

년월
Categorical

HIGH CORRELATION 

Distinct12
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2020-08
895 
2020-03-01
849 
2020-06
843 
2020-09
843 
2020-11
837 
Other values (7)
5733 

Length

Max length10
Median length7
Mean length7.9966
Min length7

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2020-04-01
2nd row2020-11
3rd row2020-08
4th row2020-08
5th row2020-06

Common Values

ValueCountFrequency (%)
2020-08 895
8.9%
2020-03-01 849
8.5%
2020-06 843
8.4%
2020-09 843
8.4%
2020-11 837
8.4%
2020-01-01 834
8.3%
2020-07 832
8.3%
2020-02-01 831
8.3%
2020-12 817
8.2%
2020-04-01 808
8.1%
Other values (2) 1611
16.1%

Length

2023-12-12T04:54:33.855672image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
2020-08 895
8.9%
2020-03-01 849
8.5%
2020-06 843
8.4%
2020-09 843
8.4%
2020-11 837
8.4%
2020-01-01 834
8.3%
2020-07 832
8.3%
2020-02-01 831
8.3%
2020-12 817
8.2%
2020-04-01 808
8.1%
Other values (2) 1611
16.1%

시도명
Categorical

HIGH CORRELATION 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
제주시
5963 
서귀포시
4037 

Length

Max length4
Median length3
Mean length3.4037
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
제주시 5963
59.6%
서귀포시 4037
40.4%

Length

2023-12-12T04:54:34.029142image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T04:54:34.180317image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
제주시 5963
59.6%
서귀포시 4037
40.4%

읍면동명
Categorical

HIGH CORRELATION 

Distinct43
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
성산읍
 
288
노형동
 
286
연동
 
282
조천읍
 
281
안덕면
 
273
Other values (38)
8590 

Length

Max length4
Median length3
Mean length3.1596
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row구좌읍
2nd row용담1동
3rd row삼양동
4th row용담2동
5th row노형동

Common Values

ValueCountFrequency (%)
성산읍 288
 
2.9%
노형동 286
 
2.9%
연동 282
 
2.8%
조천읍 281
 
2.8%
안덕면 273
 
2.7%
구좌읍 267
 
2.7%
이도2동 266
 
2.7%
천지동 266
 
2.7%
아라동 265
 
2.6%
정방동 260
 
2.6%
Other values (33) 7266
72.7%

Length

2023-12-12T04:54:34.371271image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
성산읍 288
 
2.9%
노형동 286
 
2.9%
연동 282
 
2.8%
조천읍 281
 
2.8%
안덕면 273
 
2.7%
구좌읍 267
 
2.7%
이도2동 266
 
2.7%
천지동 266
 
2.7%
아라동 265
 
2.6%
정방동 260
 
2.6%
Other values (33) 7266
72.7%

업종명
Categorical

Distinct40
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
한식 음식점업
 
411
중식 음식점업
 
404
수산물 소매업
 
403
스포츠 및 레크레이션 용품 임대업
 
400
비알콜 음료점업
 
388
Other values (35)
7994 

Length

Max length23
Median length18
Mean length9.3332
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row과실 및 채소 소매업
2nd row슈퍼마켓
3rd row슈퍼마켓
4th row욕탕업
5th row중식 음식점업

Common Values

ValueCountFrequency (%)
한식 음식점업 411
 
4.1%
중식 음식점업 404
 
4.0%
수산물 소매업 403
 
4.0%
스포츠 및 레크레이션 용품 임대업 400
 
4.0%
비알콜 음료점업 388
 
3.9%
체인화 편의점 387
 
3.9%
과실 및 채소 소매업 382
 
3.8%
슈퍼마켓 373
 
3.7%
서양식 음식점업 366
 
3.7%
빵 및 과자류 소매업 364
 
3.6%
Other values (30) 6122
61.2%

Length

2023-12-12T04:54:35.091781image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
소매업 2735
 
10.3%
및 2396
 
9.1%
음식점업 2165
 
8.2%
기타 1197
 
4.5%
운영업 728
 
2.8%
차량용 627
 
2.4%
주점업 550
 
2.1%
임대업 479
 
1.8%
그외 430
 
1.6%
한식 411
 
1.6%
Other values (58) 14719
55.7%

성별
Categorical

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
여성
5026 
남성
4974 

Length

Max length2
Median length2
Mean length2
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
여성 5026
50.3%
남성 4974
49.7%

Length

2023-12-12T04:54:35.289319image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T04:54:35.418359image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
여성 5026
50.3%
남성 4974
49.7%

이용자수
Real number (ℝ)

HIGH CORRELATION 

Distinct3189
Distinct (%)31.9%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1666.4995
Minimum1
Maximum71865
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2023-12-12T04:54:35.592092image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile2
Q144
median262
Q31332.25
95-th percentile7850.7
Maximum71865
Range71864
Interquartile range (IQR)1288.25

Descriptive statistics

Standard deviation4313.1626
Coefficient of variation (CV)2.5881571
Kurtosis49.960679
Mean1666.4995
Median Absolute Deviation (MAD)254
Skewness5.9916323
Sum16664995
Variance18603372
MonotonicityNot monotonic
2023-12-12T04:54:35.829812image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 329
 
3.3%
2 216
 
2.2%
3 139
 
1.4%
4 117
 
1.2%
5 100
 
1.0%
10 82
 
0.8%
6 78
 
0.8%
7 73
 
0.7%
8 69
 
0.7%
9 65
 
0.7%
Other values (3179) 8732
87.3%
ValueCountFrequency (%)
1 329
3.3%
2 216
2.2%
3 139
1.4%
4 117
 
1.2%
5 100
 
1.0%
6 78
 
0.8%
7 73
 
0.7%
8 69
 
0.7%
9 65
 
0.7%
10 82
 
0.8%
ValueCountFrequency (%)
71865 1
< 0.1%
64096 1
< 0.1%
60261 1
< 0.1%
54656 1
< 0.1%
53876 1
< 0.1%
52260 1
< 0.1%
51007 1
< 0.1%
49253 1
< 0.1%
48787 1
< 0.1%
47405 1
< 0.1%

이용금액
Real number (ℝ)

HIGH CORRELATION 

Distinct9121
Distinct (%)91.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean54266701
Minimum1000
Maximum4.9247364 × 109
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2023-12-12T04:54:36.074172image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1000
5-th percentile170000
Q12499528
median11572350
Q344013900
95-th percentile2.3891873 × 108
Maximum4.9247364 × 109
Range4.9247354 × 109
Interquartile range (IQR)41514372

Descriptive statistics

Standard deviation1.5371071 × 108
Coefficient of variation (CV)2.8325052
Kurtosis247.78839
Mean54266701
Median Absolute Deviation (MAD)10700850
Skewness11.883568
Sum5.4266701 × 1011
Variance2.3626984 × 1016
MonotonicityNot monotonic
2023-12-12T04:54:36.287383image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
20000 16
 
0.2%
100000 14
 
0.1%
50000 14
 
0.1%
150000 14
 
0.1%
1000000 13
 
0.1%
10000 13
 
0.1%
300000 12
 
0.1%
15000 12
 
0.1%
90000 11
 
0.1%
30000 11
 
0.1%
Other values (9111) 9870
98.7%
ValueCountFrequency (%)
1000 1
 
< 0.1%
1500 1
 
< 0.1%
2000 5
0.1%
4000 1
 
< 0.1%
4800 1
 
< 0.1%
5000 4
< 0.1%
6000 1
 
< 0.1%
7000 1
 
< 0.1%
8000 1
 
< 0.1%
9500 2
 
< 0.1%
ValueCountFrequency (%)
4924736450 1
< 0.1%
3942726490 1
< 0.1%
3701322388 1
< 0.1%
3593992569 1
< 0.1%
2958377350 1
< 0.1%
2914525523 1
< 0.1%
2055938826 1
< 0.1%
1800613924 1
< 0.1%
1709934543 1
< 0.1%
1701888402 1
< 0.1%

거주인구
Real number (ℝ)

HIGH CORRELATION 

Distinct1030
Distinct (%)10.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean5032481.6
Minimum196296.75
Maximum21639882
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2023-12-12T04:54:36.503319image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum196296.75
5-th percentile407668.41
Q11415424.2
median3637081.3
Q36540608.9
95-th percentile16349297
Maximum21639882
Range21443586
Interquartile range (IQR)5125184.7

Descriptive statistics

Standard deviation4788392.7
Coefficient of variation (CV)0.9514973
Kurtosis1.2771929
Mean5032481.6
Median Absolute Deviation (MAD)2411201.4
Skewness1.4159296
Sum5.0324816 × 1010
Variance2.2928704 × 1013
MonotonicityNot monotonic
2023-12-12T04:54:36.756696image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
7056442.6779999975 19
 
0.2%
7653049.872 18
 
0.2%
505822.394 18
 
0.2%
16349297.23 18
 
0.2%
5227524.722 18
 
0.2%
5173331.363 17
 
0.2%
2463541.358 17
 
0.2%
659487.011 17
 
0.2%
744157.164 17
 
0.2%
6995098.621 17
 
0.2%
Other values (1020) 9824
98.2%
ValueCountFrequency (%)
196296.746 13
0.1%
220789.33 12
0.1%
221895.54 6
0.1%
231272.56 14
0.1%
238014.459 13
0.1%
242124.276 12
0.1%
242274.699 13
0.1%
243258.954 10
0.1%
246007.449 8
0.1%
247665.602 14
0.1%
ValueCountFrequency (%)
21639882.259 11
0.1%
21405678.87 14
0.1%
19912741.82 10
0.1%
19672663.203 16
0.2%
19623453.56 14
0.1%
19175754.12 12
0.1%
19109834.513 10
0.1%
18959968.76 9
0.1%
18924298.579 16
0.2%
18863136.695 12
0.1%

근무인구
Real number (ℝ)

HIGH CORRELATION 

Distinct1030
Distinct (%)10.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean483776.64
Minimum5829.597
Maximum2591498.6
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2023-12-12T04:54:37.088721image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum5829.597
5-th percentile32418.635
Q1168792.98
median307969.84
Q3557378.97
95-th percentile1727602.2
Maximum2591498.6
Range2585669
Interquartile range (IQR)388585.99

Descriptive statistics

Standard deviation502761.08
Coefficient of variation (CV)1.0392421
Kurtosis2.9336396
Mean483776.64
Median Absolute Deviation (MAD)186956.97
Skewness1.8621117
Sum4.8377664 × 109
Variance2.527687 × 1011
MonotonicityNot monotonic
2023-12-12T04:54:37.349073image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
488701.323 19
 
0.2%
887300.798 18
 
0.2%
201244.411 18
 
0.2%
1520843.383 18
 
0.2%
445407.076 18
 
0.2%
688792.794 17
 
0.2%
221892.116 17
 
0.2%
50370.402 17
 
0.2%
176680.215 17
 
0.2%
580405.183 17
 
0.2%
Other values (1020) 9824
98.2%
ValueCountFrequency (%)
5829.597 7
0.1%
6636.32 5
0.1%
7688.905 9
0.1%
8765.668 6
0.1%
10468.095 6
0.1%
10606.683 4
 
< 0.1%
10608.113 6
0.1%
12167.883999999998 3
 
< 0.1%
13687.431 10
0.1%
13689.824 10
0.1%
ValueCountFrequency (%)
2591498.593 11
0.1%
2485078.24 13
0.1%
2440585.828 16
0.2%
2322003.057 11
0.1%
2315415.662 14
0.1%
2265002.675 12
0.1%
2248123.207 6
 
0.1%
2230228.506 7
0.1%
2188120.358 5
 
0.1%
2139343.065 8
0.1%

방문인구
Real number (ℝ)

HIGH CORRELATION 

Distinct1030
Distinct (%)10.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2670173.8
Minimum177058.14
Maximum9337130.4
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2023-12-12T04:54:37.611953image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum177058.14
5-th percentile529003.27
Q11340685.6
median2116118
Q33382573.2
95-th percentile7404723.1
Maximum9337130.4
Range9160072.2
Interquartile range (IQR)2041887.6

Descriptive statistics

Standard deviation1963272.1
Coefficient of variation (CV)0.73526004
Kurtosis1.4233981
Mean2670173.8
Median Absolute Deviation (MAD)909054.28
Skewness1.4001704
Sum2.6701738 × 1010
Variance3.8544372 × 1012
MonotonicityNot monotonic
2023-12-12T04:54:37.864594image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
2722665.9080000003 19
 
0.2%
4368473.302 18
 
0.2%
1406337.064 18
 
0.2%
5553362.02 18
 
0.2%
2385448.91 18
 
0.2%
3205080.907 17
 
0.2%
2116117.95 17
 
0.2%
668226.025 17
 
0.2%
1494432.928 17
 
0.2%
4991744.338 17
 
0.2%
Other values (1020) 9824
98.2%
ValueCountFrequency (%)
177058.139 10
0.1%
187115.478 1
 
< 0.1%
190312.364 6
0.1%
193783.656 8
0.1%
193865.387 10
0.1%
194410.369 8
0.1%
214849.256 7
0.1%
220455.767 6
0.1%
226890.426 9
0.1%
231609.932 3
 
< 0.1%
ValueCountFrequency (%)
9337130.36 9
0.1%
9293212.671 14
0.1%
9066111.907 12
0.1%
8887326.531 8
0.1%
8859818.095 9
0.1%
8670501.644 12
0.1%
8589876.204 11
0.1%
8566799.066 14
0.1%
8453565.529 11
0.1%
8441884.429 14
0.1%

데이터기준일자
Categorical

HIGH CORRELATION 

Distinct3
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2021-07-26
4195 
2020-12-15
3322 
2021-07-30
2483 

Length

Max length10
Median length10
Mean length10
Min length10

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2020-12-15
2nd row2021-07-26
3rd row2021-07-26
4th row2021-07-26
5th row2021-07-30

Common Values

ValueCountFrequency (%)
2021-07-26 4195
41.9%
2020-12-15 3322
33.2%
2021-07-30 2483
24.8%

Length

2023-12-12T04:54:38.100063image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T04:54:38.311303image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2021-07-26 4195
41.9%
2020-12-15 3322
33.2%
2021-07-30 2483
24.8%

Interactions

2023-12-12T04:54:32.778302image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T04:54:29.966470image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T04:54:30.746882image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T04:54:31.496630image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T04:54:32.091795image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T04:54:32.923219image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T04:54:30.132516image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T04:54:30.928911image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T04:54:31.625399image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T04:54:32.229312image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T04:54:33.034421image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T04:54:30.274407image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T04:54:31.087340image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T04:54:31.744565image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T04:54:32.379558image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T04:54:33.158077image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T04:54:30.411964image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T04:54:31.221128image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T04:54:31.856324image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T04:54:32.530855image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T04:54:33.289052image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T04:54:30.582749image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T04:54:31.373594image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T04:54:31.978731image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T04:54:32.661570image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-12T04:54:38.459267image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
년월시도명읍면동명업종명성별이용자수이용금액거주인구근무인구방문인구데이터기준일자
년월1.0000.0000.0000.0000.0000.0100.0160.1620.2050.2261.000
시도명0.0001.0001.0000.1560.0000.0550.0530.5780.4740.5270.003
읍면동명0.0001.0001.0000.4310.0000.2650.2250.9500.8940.9140.000
업종명0.0000.1560.4311.0000.0000.5470.5680.2430.1880.2020.000
성별0.0000.0000.0000.0001.0000.0780.0500.2430.1720.2280.000
이용자수0.0100.0550.2650.5470.0781.0000.7600.3110.2730.2820.026
이용금액0.0160.0530.2250.5680.0500.7601.0000.2300.2360.2740.000
거주인구0.1620.5780.9500.2430.2430.3110.2301.0000.9000.8580.107
근무인구0.2050.4740.8940.1880.1720.2730.2360.9001.0000.8800.154
방문인구0.2260.5270.9140.2020.2280.2820.2740.8580.8801.0000.134
데이터기준일자1.0000.0030.0000.0000.0000.0260.0000.1070.1540.1341.000
2023-12-12T04:54:38.698737image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
성별읍면동명년월데이터기준일자시도명업종명
성별1.0000.0000.0000.0000.0000.000
읍면동명0.0001.0000.0000.0000.9980.093
년월0.0000.0001.0001.0000.0000.000
데이터기준일자0.0000.0001.0001.0000.0050.000
시도명0.0000.9980.0000.0051.0000.124
업종명0.0000.0930.0000.0000.1241.000
2023-12-12T04:54:38.921007image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
이용자수이용금액거주인구근무인구방문인구년월시도명읍면동명업종명성별데이터기준일자
이용자수1.0000.9140.0690.0890.0930.0040.0420.0940.2050.0600.015
이용금액0.9141.0000.1100.1360.1470.0070.0410.0790.2160.0380.000
거주인구0.0690.1101.0000.8980.8610.0690.4470.7240.0800.1860.064
근무인구0.0890.1360.8981.0000.9510.0870.3640.5760.0610.1330.092
방문인구0.0930.1470.8610.9511.0000.0970.4050.6190.0660.1750.081
년월0.0040.0070.0690.0870.0971.0000.0000.0000.0000.0001.000
시도명0.0420.0410.4470.3640.4050.0001.0000.9980.1240.0000.005
읍면동명0.0940.0790.7240.5760.6190.0000.9981.0000.0930.0000.000
업종명0.2050.2160.0800.0610.0660.0000.1240.0931.0000.0000.000
성별0.0600.0380.1860.1330.1750.0000.0000.0000.0001.0000.000
데이터기준일자0.0150.0000.0640.0920.0811.0000.0050.0000.0000.0001.000

Missing values

2023-12-12T04:54:33.463167image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-12T04:54:33.679684image/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
84252020-04-01제주시구좌읍과실 및 채소 소매업남성11235849004540419.536435303.4792140634.422020-12-15
227362020-11제주시용담1동슈퍼마켓남성949151892302023969.84203424.6861520305.4592021-07-26
162602020-08제주시삼양동슈퍼마켓남성123632768907137577549.744292124.2141981408.722021-07-26
159132020-08제주시용담2동욕탕업여성36855033003720183.924552192.025104010.9842021-07-26
131472020-06제주시노형동중식 음식점업남성28147563700016374871.6121800228.6617615077.9612021-07-30
233692020-11제주시이도2동욕탕업여성190246100019672663.2032440585.8288275836.6292021-07-26
194072020-09서귀포시대륜동차량용 주유소 운영업여성1561677145854973021.99457157.6422233418.5372021-07-26
144432020-07제주시우도면차량용 주유소 운영업남성1979061939491704.1426872.596529003.2672021-07-30
119232020-06제주시한림읍휴양콘도 운영업여성6658273696051705.76424914.4412689599.9542021-07-30
111512020-05서귀포시중앙동서양식 음식점업여성213545092340824574.585184866.7211351827.622021-07-30
년월시도명읍면동명업종명성별이용자수이용금액거주인구근무인구방문인구데이터기준일자
224612020-10서귀포시천지동비알콜 음료점업여성476241921680270366.03326034.779657256.0792021-07-26
41222020-02-01제주시도두동차량용 주유소 운영업여성49620742445373578.01251074.33828662.762020-12-15
229142020-11제주시애월읍관광 민예품 및 선물용품 소매업여성33446821061012468682.7421082458.7387726192.5082021-07-26
185542020-09제주시아라동그외 기타 종합 소매업여성11408000014197262.0871431645.8614913050.4032021-07-26
267142020-12서귀포시중문동욕탕업여성150004021981.486243921.0261545775.092021-07-26
253622020-12제주시조천읍그외 기타 종합 소매업여성2032789990107799655.306596147.0333143068.4012021-07-26
121672020-06제주시우도면중식 음식점업여성5017867000342520.76116279.872287567.3552021-07-30
241732020-11제주시건입동일반유흥 주점업여성4435720002480763.435244921.4842103043.562021-07-26
222392020-10서귀포시중문동스포츠 및 레크레이션 용품 임대업남성594229764003533425.031238794.7122399959.9912021-07-26
175962020-08제주시노형동중식 음식점업여성16004444660018726627.6941882608.4826861370.4452021-07-26