Overview

Dataset statistics

Number of variables13
Number of observations3480
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory377.4 KiB
Average record size in memory111.0 B

Variable types

Numeric5
Categorical8

Dataset

Description대전광역시 서구 상권별 시간대별유동인구 현황 (상권코드, 상권명, 성별코드, 시간대코드, 시간대, 행정동코드, 행정동명, 유동인구수, 시간당평균유동인구수, 데이터생성일자) 데이터를 제공합니다.
URLhttps://www.data.go.kr/data/15109009/fileData.do

Alerts

기준년 has constant value ""Constant
데이터생성일자 has constant value ""Constant
성별 is highly overall correlated with 성별코드High correlation
성별코드 is highly overall correlated with 성별High correlation
시간대 is highly overall correlated with 시간대코드High correlation
시간대코드 is highly overall correlated with 시간대High correlation
순번 is highly overall correlated with 기준월High correlation
기준월 is highly overall correlated with 순번High correlation
상권코드 is highly overall correlated with 상권명 and 1 other fieldsHigh correlation
행정동코드 is highly overall correlated with 상권명 and 1 other fieldsHigh correlation
상권명 is highly overall correlated with 상권코드 and 2 other fieldsHigh correlation
행정동명 is highly overall correlated with 상권코드 and 2 other fieldsHigh correlation
순번 has unique valuesUnique

Reproduction

Analysis started2023-12-12 11:58:05.674533
Analysis finished2023-12-12 11:58:09.781041
Duration4.11 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

순번
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct3480
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1740.5
Minimum1
Maximum3480
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size30.7 KiB
2023-12-12T20:58:09.872882image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile174.95
Q1870.75
median1740.5
Q32610.25
95-th percentile3306.05
Maximum3480
Range3479
Interquartile range (IQR)1739.5

Descriptive statistics

Standard deviation1004.7338
Coefficient of variation (CV)0.57726733
Kurtosis-1.2
Mean1740.5
Median Absolute Deviation (MAD)870
Skewness0
Sum6056940
Variance1009490
MonotonicityStrictly increasing
2023-12-12T20:58:10.051866image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 1
 
< 0.1%
2326 1
 
< 0.1%
2315 1
 
< 0.1%
2316 1
 
< 0.1%
2317 1
 
< 0.1%
2318 1
 
< 0.1%
2319 1
 
< 0.1%
2320 1
 
< 0.1%
2321 1
 
< 0.1%
2322 1
 
< 0.1%
Other values (3470) 3470
99.7%
ValueCountFrequency (%)
1 1
< 0.1%
2 1
< 0.1%
3 1
< 0.1%
4 1
< 0.1%
5 1
< 0.1%
6 1
< 0.1%
7 1
< 0.1%
8 1
< 0.1%
9 1
< 0.1%
10 1
< 0.1%
ValueCountFrequency (%)
3480 1
< 0.1%
3479 1
< 0.1%
3478 1
< 0.1%
3477 1
< 0.1%
3476 1
< 0.1%
3475 1
< 0.1%
3474 1
< 0.1%
3473 1
< 0.1%
3472 1
< 0.1%
3471 1
< 0.1%

기준년
Categorical

CONSTANT 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size27.3 KiB
2021
3480 

Length

Max length4
Median length4
Mean length4
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2021
2nd row2021
3rd row2021
4th row2021
5th row2021

Common Values

ValueCountFrequency (%)
2021 3480
100.0%

Length

2023-12-12T20:58:10.219217image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T20:58:10.337816image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2021 3480
100.0%

기준월
Real number (ℝ)

HIGH CORRELATION 

Distinct12
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean6.5
Minimum1
Maximum12
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size30.7 KiB
2023-12-12T20:58:10.463934image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q13.75
median6.5
Q39.25
95-th percentile12
Maximum12
Range11
Interquartile range (IQR)5.5

Descriptive statistics

Standard deviation3.4525486
Coefficient of variation (CV)0.53116133
Kurtosis-1.2168072
Mean6.5
Median Absolute Deviation (MAD)3
Skewness0
Sum22620
Variance11.920092
MonotonicityIncreasing
2023-12-12T20:58:10.600120image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=12)
ValueCountFrequency (%)
1 290
8.3%
2 290
8.3%
3 290
8.3%
4 290
8.3%
5 290
8.3%
6 290
8.3%
7 290
8.3%
8 290
8.3%
9 290
8.3%
10 290
8.3%
Other values (2) 580
16.7%
ValueCountFrequency (%)
1 290
8.3%
2 290
8.3%
3 290
8.3%
4 290
8.3%
5 290
8.3%
6 290
8.3%
7 290
8.3%
8 290
8.3%
9 290
8.3%
10 290
8.3%
ValueCountFrequency (%)
12 290
8.3%
11 290
8.3%
10 290
8.3%
9 290
8.3%
8 290
8.3%
7 290
8.3%
6 290
8.3%
5 290
8.3%
4 290
8.3%
3 290
8.3%

상권코드
Real number (ℝ)

HIGH CORRELATION 

Distinct14
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean7.8965517
Minimum1
Maximum14
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size30.7 KiB
2023-12-12T20:58:10.719358image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile2
Q14
median8
Q312
95-th percentile14
Maximum14
Range13
Interquartile range (IQR)8

Descriptive statistics

Standard deviation4.2297744
Coefficient of variation (CV)0.53564828
Kurtosis-1.3828717
Mean7.8965517
Median Absolute Deviation (MAD)4
Skewness-0.05381327
Sum27480
Variance17.890991
MonotonicityNot monotonic
2023-12-12T20:58:10.848523image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=14)
ValueCountFrequency (%)
2 360
10.3%
3 360
10.3%
13 360
10.3%
14 360
10.3%
5 240
 
6.9%
6 240
 
6.9%
7 240
 
6.9%
9 240
 
6.9%
10 240
 
6.9%
11 240
 
6.9%
Other values (4) 600
17.2%
ValueCountFrequency (%)
1 120
 
3.4%
2 360
10.3%
3 360
10.3%
4 120
 
3.4%
5 240
6.9%
6 240
6.9%
7 240
6.9%
8 120
 
3.4%
9 240
6.9%
10 240
6.9%
ValueCountFrequency (%)
14 360
10.3%
13 360
10.3%
12 240
6.9%
11 240
6.9%
10 240
6.9%
9 240
6.9%
8 120
 
3.4%
7 240
6.9%
6 240
6.9%
5 240
6.9%

상권명
Categorical

HIGH CORRELATION 

Distinct14
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size27.3 KiB
한민시장 주변 상권
360 
롯데백화점 주변 상권
360 
대전시청역 주변 상권
360 
서구 보건소 주변 상권
360 
이마트 둔산점 주변 상권
240 
Other values (9)
1800 

Length

Max length23
Median length19
Mean length13.137931
Min length10

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row가수원상점가 주변 상권
2nd row가수원상점가 주변 상권
3rd row한민시장 주변 상권
4th row한민시장 주변 상권
5th row한민시장 주변 상권

Common Values

ValueCountFrequency (%)
한민시장 주변 상권 360
10.3%
롯데백화점 주변 상권 360
10.3%
대전시청역 주변 상권 360
10.3%
서구 보건소 주변 상권 360
10.3%
이마트 둔산점 주변 상권 240
 
6.9%
사학연금회관 뒤편(토요코인호텔) 주변 상권 240
 
6.9%
대주프라자 주변 상권 240
 
6.9%
둔산3동상점가 주변 상권 240
 
6.9%
도마큰시장 주변 상권 240
 
6.9%
이마트 트레이더스 월평점 주변 상권 240
 
6.9%
Other values (4) 600
17.2%

Length

2023-12-12T20:58:10.999329image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
상권 3480
29.6%
주변 3480
29.6%
이마트 480
 
4.1%
한민시장 360
 
3.1%
롯데백화점 360
 
3.1%
대전시청역 360
 
3.1%
서구 360
 
3.1%
보건소 360
 
3.1%
도마큰시장 240
 
2.0%
세이디에스탄방점 240
 
2.0%
Other values (10) 2040
17.3%

행정동코드
Real number (ℝ)

HIGH CORRELATION 

Distinct17
Distinct (%)0.5%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean3.0170594 × 109
Minimum3.017052 × 109
Maximum3.017066 × 109
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size30.7 KiB
2023-12-12T20:58:11.125378image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum3.017052 × 109
5-th percentile3.017053 × 109
Q13.017056 × 109
median3.0170588 × 109
Q33.017063 × 109
95-th percentile3.017065 × 109
Maximum3.017066 × 109
Range14000
Interquartile range (IQR)7000

Descriptive statistics

Standard deviation3852.6096
Coefficient of variation (CV)1.2769419 × 10-6
Kurtosis-1.1331088
Mean3.0170594 × 109
Median Absolute Deviation (MAD)3300
Skewness0.034460827
Sum1.0499367 × 1013
Variance14842600
MonotonicityNot monotonic
2023-12-12T20:58:11.282003image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=17)
ValueCountFrequency (%)
3017064000 600
17.2%
3017055500 480
13.8%
3017063000 360
10.3%
3017058700 240
 
6.9%
3017056000 240
 
6.9%
3017059700 240
 
6.9%
3017059000 120
 
3.4%
3017052000 120
 
3.4%
3017065000 120
 
3.4%
3017058800 120
 
3.4%
Other values (7) 840
24.1%
ValueCountFrequency (%)
3017052000 120
 
3.4%
3017053000 120
 
3.4%
3017055000 120
 
3.4%
3017055500 480
13.8%
3017056000 240
6.9%
3017057000 120
 
3.4%
3017057500 120
 
3.4%
3017058600 120
 
3.4%
3017058700 240
6.9%
3017058800 120
 
3.4%
ValueCountFrequency (%)
3017066000 120
 
3.4%
3017065000 120
 
3.4%
3017064000 600
17.2%
3017063000 360
10.3%
3017059700 240
 
6.9%
3017059600 120
 
3.4%
3017059000 120
 
3.4%
3017058800 120
 
3.4%
3017058700 240
 
6.9%
3017058600 120
 
3.4%

행정동명
Categorical

HIGH CORRELATION 

Distinct17
Distinct (%)0.5%
Missing0
Missing (%)0.0%
Memory size27.3 KiB
둔산2동
600 
탄방동
480 
둔산1동
360 
월평2동
240 
괴정동
240 
Other values (12)
1560 

Length

Max length4
Median length4
Mean length3.6206897
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row가수원동
2nd row가수원동
3rd row괴정동
4th row괴정동
5th row가장동

Common Values

ValueCountFrequency (%)
둔산2동 600
17.2%
탄방동 480
13.8%
둔산1동 360
10.3%
월평2동 240
 
6.9%
괴정동 240
 
6.9%
관저2동 240
 
6.9%
가수원동 120
 
3.4%
가장동 120
 
3.4%
내동 120
 
3.4%
용문동 120
 
3.4%
Other values (7) 840
24.1%

Length

2023-12-12T20:58:11.431484image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
둔산2동 600
17.2%
탄방동 480
13.8%
둔산1동 360
10.3%
월평2동 240
 
6.9%
괴정동 240
 
6.9%
관저2동 240
 
6.9%
월평1동 120
 
3.4%
둔산3동 120
 
3.4%
월평3동 120
 
3.4%
도마2동 120
 
3.4%
Other values (7) 840
24.1%

성별코드
Categorical

HIGH CORRELATION 

Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size27.3 KiB
f
1740 
m
1740 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowf
2nd rowm
3rd rowf
4th rowm
5th rowf

Common Values

ValueCountFrequency (%)
f 1740
50.0%
m 1740
50.0%

Length

2023-12-12T20:58:11.593031image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T20:58:11.713119image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
f 1740
50.0%
m 1740
50.0%

성별
Categorical

HIGH CORRELATION 

Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size27.3 KiB
여성
1740 
남성
1740 

Length

Max length2
Median length2
Mean length2
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
여성 1740
50.0%
남성 1740
50.0%

Length

2023-12-12T20:58:11.830037image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T20:58:11.967618image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
여성 1740
50.0%
남성 1740
50.0%

시간대코드
Categorical

HIGH CORRELATION 

Distinct5
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size27.3 KiB
1
696 
2
696 
3
696 
4
696 
5
696 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row1
2nd row1
3rd row1
4th row1
5th row1

Common Values

ValueCountFrequency (%)
1 696
20.0%
2 696
20.0%
3 696
20.0%
4 696
20.0%
5 696
20.0%

Length

2023-12-12T20:58:12.110790image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T20:58:12.599104image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
1 696
20.0%
2 696
20.0%
3 696
20.0%
4 696
20.0%
5 696
20.0%

시간대
Categorical

HIGH CORRELATION 

Distinct5
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size27.3 KiB
출근
696 
주간
696 
퇴근
696 
저녁
696 
야간
696 

Length

Max length2
Median length2
Mean length2
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
출근 696
20.0%
주간 696
20.0%
퇴근 696
20.0%
저녁 696
20.0%
야간 696
20.0%

Length

2023-12-12T20:58:12.795278image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T20:58:12.927942image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
출근 696
20.0%
주간 696
20.0%
퇴근 696
20.0%
저녁 696
20.0%
야간 696
20.0%

비율
Real number (ℝ)

Distinct1440
Distinct (%)41.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean50
Minimum31.31
Maximum68.69
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size30.7 KiB
2023-12-12T20:58:13.071946image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum31.31
5-th percentile42.8795
Q147.3275
median50
Q352.6725
95-th percentile57.1205
Maximum68.69
Range37.38
Interquartile range (IQR)5.345

Descriptive statistics

Standard deviation4.3335509
Coefficient of variation (CV)0.086671019
Kurtosis0.77605635
Mean50
Median Absolute Deviation (MAD)2.675
Skewness-3.0534253 × 10-17
Sum174000
Variance18.779664
MonotonicityNot monotonic
2023-12-12T20:58:13.250324image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
48.74 9
 
0.3%
51.26 9
 
0.3%
50.78 8
 
0.2%
50.23 8
 
0.2%
52.47 8
 
0.2%
47.53 8
 
0.2%
49.22 8
 
0.2%
49.77 8
 
0.2%
51.14 7
 
0.2%
48.78 7
 
0.2%
Other values (1430) 3400
97.7%
ValueCountFrequency (%)
31.31 1
< 0.1%
33.22 1
< 0.1%
33.6 1
< 0.1%
34.18 1
< 0.1%
34.33 1
< 0.1%
35.0 1
< 0.1%
35.64 1
< 0.1%
35.94 1
< 0.1%
35.95 1
< 0.1%
35.98 1
< 0.1%
ValueCountFrequency (%)
68.69 1
< 0.1%
66.78 1
< 0.1%
66.4 1
< 0.1%
65.82 1
< 0.1%
65.67 1
< 0.1%
65.0 1
< 0.1%
64.36 1
< 0.1%
64.06 1
< 0.1%
64.05 1
< 0.1%
64.02 1
< 0.1%

데이터생성일자
Categorical

CONSTANT 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size27.3 KiB
2023-05-10
3480 

Length

Max length10
Median length10
Mean length10
Min length10

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2023-05-10
2nd row2023-05-10
3rd row2023-05-10
4th row2023-05-10
5th row2023-05-10

Common Values

ValueCountFrequency (%)
2023-05-10 3480
100.0%

Length

2023-12-12T20:58:13.397168image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T20:58:13.492339image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2023-05-10 3480
100.0%

Interactions

2023-12-12T20:58:08.741137image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T20:58:06.560306image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T20:58:07.136376image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T20:58:07.626848image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T20:58:08.103632image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T20:58:08.855608image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T20:58:06.670471image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T20:58:07.250545image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T20:58:07.719333image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T20:58:08.215714image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T20:58:08.974239image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T20:58:06.779570image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T20:58:07.335935image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T20:58:07.814420image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T20:58:08.324566image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T20:58:09.111412image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T20:58:06.884919image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T20:58:07.415240image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T20:58:07.901643image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T20:58:08.441470image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T20:58:09.259732image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T20:58:07.017499image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T20:58:07.527401image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T20:58:08.002016image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T20:58:08.571913image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-12T20:58:13.555802image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
순번기준월상권코드상권명행정동코드행정동명성별코드성별시간대코드시간대비율
순번1.0000.9820.0000.0000.0000.0000.0000.0000.3630.3630.000
기준월0.9821.0000.0000.0000.0000.0000.0000.0000.0000.0000.000
상권코드0.0000.0001.0001.0000.8680.9350.0000.0000.0000.0000.374
상권명0.0000.0001.0001.0000.9430.9520.0000.0000.0000.0000.361
행정동코드0.0000.0000.8680.9431.0001.0000.0000.0000.0000.0000.235
행정동명0.0000.0000.9350.9521.0001.0000.0000.0000.0000.0000.398
성별코드0.0000.0000.0000.0000.0000.0001.0001.0000.0000.0000.427
성별0.0000.0000.0000.0000.0000.0001.0001.0000.0000.0000.427
시간대코드0.3630.0000.0000.0000.0000.0000.0000.0001.0001.0000.419
시간대0.3630.0000.0000.0000.0000.0000.0000.0001.0001.0000.419
비율0.0000.0000.3740.3610.2350.3980.4270.4270.4190.4191.000
2023-12-12T20:58:13.692443image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
성별성별코드시간대행정동명상권명시간대코드
성별1.0000.9990.0000.0000.0000.000
성별코드0.9991.0000.0000.0000.0000.000
시간대0.0000.0001.0000.0000.0001.000
행정동명0.0000.0000.0001.0000.7440.000
상권명0.0000.0000.0000.7441.0000.000
시간대코드0.0000.0001.0000.0000.0001.000
2023-12-12T20:58:13.843661image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
순번기준월상권코드행정동코드비율상권명행정동명성별코드성별시간대코드시간대
순번1.0000.9970.0170.0040.0000.0000.0000.0000.0000.1590.159
기준월0.9971.0000.0000.0000.0000.0000.0000.0000.0000.0000.000
상권코드0.0170.0001.0000.2270.0000.9990.7360.0000.0000.0000.000
행정동코드0.0040.0000.2271.0000.0000.8000.9990.0000.0000.0000.000
비율0.0000.0000.0000.0001.0000.1540.1660.3280.3280.1870.187
상권명0.0000.0000.9990.8000.1541.0000.7440.0000.0000.0000.000
행정동명0.0000.0000.7360.9990.1660.7441.0000.0000.0000.0000.000
성별코드0.0000.0000.0000.0000.3280.0000.0001.0000.9990.0000.000
성별0.0000.0000.0000.0000.3280.0000.0000.9991.0000.0000.000
시간대코드0.1590.0000.0000.0000.1870.0000.0000.0000.0001.0001.000
시간대0.1590.0000.0000.0000.1870.0000.0000.0000.0001.0001.000

Missing values

2023-12-12T20:58:09.444099image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-12T20:58:09.679909image/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

순번기준년기준월상권코드상권명행정동코드행정동명성별코드성별시간대코드시간대비율데이터생성일자
01202111가수원상점가 주변 상권3017059000가수원동f여성1출근45.762023-05-10
12202111가수원상점가 주변 상권3017059000가수원동m남성1출근54.242023-05-10
23202112한민시장 주변 상권3017056000괴정동f여성1출근47.52023-05-10
34202112한민시장 주변 상권3017056000괴정동m남성1출근52.52023-05-10
45202112한민시장 주변 상권3017057000가장동f여성1출근51.972023-05-10
56202112한민시장 주변 상권3017057000가장동m남성1출근48.032023-05-10
67202112한민시장 주변 상권3017057500내동f여성1출근50.892023-05-10
78202112한민시장 주변 상권3017057500내동m남성1출근49.112023-05-10
89202113롯데백화점 주변 상권3017055000용문동f여성1출근51.662023-05-10
910202113롯데백화점 주변 상권3017055000용문동m남성1출근48.342023-05-10
순번기준년기준월상권코드상권명행정동코드행정동명성별코드성별시간대코드시간대비율데이터생성일자
3470347120211213대전시청역 주변 상권3017063000둔산1동f여성5야간40.042023-05-10
3471347220211213대전시청역 주변 상권3017063000둔산1동m남성5야간59.962023-05-10
3472347320211213대전시청역 주변 상권3017064000둔산2동f여성5야간35.982023-05-10
3473347420211213대전시청역 주변 상권3017064000둔산2동m남성5야간64.022023-05-10
3474347520211214서구 보건소 주변 상권3017058700월평2동f여성5야간42.752023-05-10
3475347620211214서구 보건소 주변 상권3017058700월평2동m남성5야간57.252023-05-10
3476347720211214서구 보건소 주변 상권3017064000둔산2동f여성5야간42.772023-05-10
3477347820211214서구 보건소 주변 상권3017064000둔산2동m남성5야간57.232023-05-10
3478347920211214서구 보건소 주변 상권3017065000만년동f여성5야간43.452023-05-10
3479348020211214서구 보건소 주변 상권3017065000만년동m남성5야간56.552023-05-10