Overview

Dataset statistics

Number of variables13
Number of observations10000
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory1.1 MiB
Average record size in memory119.0 B

Variable types

Numeric5
Categorical8

Dataset

Description대전광역시 서구 행정동별 시간대별 유동인구 현황(기준년, 기준월, 행정동코드, 행정동명, 성별코드, 성별, 시간대코드, 시간대, 유동인구수, 시간당 평균 유동인구수 등) 데이터를 제공합니다.
URLhttps://www.data.go.kr/data/15109026/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
행정동코드 is highly overall correlated with 행정동명High correlation
요일코드 is highly overall correlated with 요일High correlation
행정동명 is highly overall correlated with 행정동코드High correlation
요일 is highly overall correlated with 요일코드High correlation
순번 has unique valuesUnique
요일코드 has 1482 (14.8%) zerosZeros

Reproduction

Analysis started2023-12-12 13:10:38.459362
Analysis finished2023-12-12 13:10:43.238175
Duration4.78 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

순번
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct10000
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean9710.7398
Minimum1
Maximum19320
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2023-12-12T22:10:43.308870image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1030.95
Q14921.75
median9707.5
Q314522.25
95-th percentile18360.05
Maximum19320
Range19319
Interquartile range (IQR)9600.5

Descriptive statistics

Standard deviation5555.6666
Coefficient of variation (CV)0.57211569
Kurtosis-1.2025036
Mean9710.7398
Median Absolute Deviation (MAD)4801
Skewness-0.0045511439
Sum97107398
Variance30865432
MonotonicityNot monotonic
2023-12-12T22:10:43.470942image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
3507 1
 
< 0.1%
4967 1
 
< 0.1%
101 1
 
< 0.1%
12435 1
 
< 0.1%
15061 1
 
< 0.1%
3171 1
 
< 0.1%
2670 1
 
< 0.1%
16702 1
 
< 0.1%
734 1
 
< 0.1%
9229 1
 
< 0.1%
Other values (9990) 9990
99.9%
ValueCountFrequency (%)
1 1
< 0.1%
5 1
< 0.1%
6 1
< 0.1%
12 1
< 0.1%
13 1
< 0.1%
16 1
< 0.1%
18 1
< 0.1%
21 1
< 0.1%
23 1
< 0.1%
24 1
< 0.1%
ValueCountFrequency (%)
19320 1
< 0.1%
19318 1
< 0.1%
19316 1
< 0.1%
19315 1
< 0.1%
19313 1
< 0.1%
19311 1
< 0.1%
19310 1
< 0.1%
19309 1
< 0.1%
19307 1
< 0.1%
19306 1
< 0.1%

기준년
Categorical

CONSTANT 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2021
10000 

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 10000
100.0%

Length

2023-12-12T22:10:43.605552image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T22:10:43.693673image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2021 10000
100.0%

기준월
Real number (ℝ)

HIGH CORRELATION 

Distinct12
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean6.53
Minimum1
Maximum12
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2023-12-12T22:10:43.792224image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q14
median7
Q310
95-th percentile12
Maximum12
Range11
Interquartile range (IQR)6

Descriptive statistics

Standard deviation3.4401284
Coefficient of variation (CV)0.52681905
Kurtosis-1.2174494
Mean6.53
Median Absolute Deviation (MAD)3
Skewness-0.0065755396
Sum65300
Variance11.834483
MonotonicityNot monotonic
2023-12-12T22:10:43.896731image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=12)
ValueCountFrequency (%)
4 860
8.6%
11 855
8.6%
9 853
8.5%
6 843
8.4%
10 839
8.4%
2 837
8.4%
3 829
8.3%
8 826
8.3%
7 826
8.3%
12 825
8.2%
Other values (2) 1607
16.1%
ValueCountFrequency (%)
1 789
7.9%
2 837
8.4%
3 829
8.3%
4 860
8.6%
5 818
8.2%
6 843
8.4%
7 826
8.3%
8 826
8.3%
9 853
8.5%
10 839
8.4%
ValueCountFrequency (%)
12 825
8.2%
11 855
8.6%
10 839
8.4%
9 853
8.5%
8 826
8.3%
7 826
8.3%
6 843
8.4%
5 818
8.2%
4 860
8.6%
3 829
8.3%

행정동코드
Real number (ℝ)

HIGH CORRELATION 

Distinct23
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean3.017058 × 109
Minimum3.017051 × 109
Maximum3.017066 × 109
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2023-12-12T22:10:43.995420image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum3.017051 × 109
5-th percentile3.017052 × 109
Q13.017055 × 109
median3.0170582 × 109
Q33.0170597 × 109
95-th percentile3.017065 × 109
Maximum3.017066 × 109
Range15000
Interquartile range (IQR)4700

Descriptive statistics

Standard deviation3905.7015
Coefficient of variation (CV)1.2945397 × 10-6
Kurtosis-0.48345829
Mean3.017058 × 109
Median Absolute Deviation (MAD)2200
Skewness0.27042679
Sum3.017058 × 1013
Variance15254504
MonotonicityNot monotonic
2023-12-12T22:10:44.110563image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=23)
ValueCountFrequency (%)
3017057500 453
 
4.5%
3017064000 453
 
4.5%
3017058700 451
 
4.5%
3017055000 447
 
4.5%
3017053500 444
 
4.4%
3017057000 443
 
4.4%
3017058100 442
 
4.4%
3017058600 441
 
4.4%
3017055500 441
 
4.4%
3017065000 440
 
4.4%
Other values (13) 5545
55.5%
ValueCountFrequency (%)
3017051000 404
4.0%
3017052000 419
4.2%
3017053000 438
4.4%
3017053500 444
4.4%
3017054000 429
4.3%
3017055000 447
4.5%
3017055500 441
4.4%
3017056000 435
4.3%
3017057000 443
4.4%
3017057500 453
4.5%
ValueCountFrequency (%)
3017066000 435
4.3%
3017065000 440
4.4%
3017064000 453
4.5%
3017063000 437
4.4%
3017060000 425
4.2%
3017059700 430
4.3%
3017059600 431
4.3%
3017059000 433
4.3%
3017058800 400
4.0%
3017058700 451
4.5%

행정동명
Categorical

HIGH CORRELATION 

Distinct23
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
내동
 
453
둔산2동
 
453
월평2동
 
451
용문동
 
447
정림동
 
444
Other values (18)
7752 

Length

Max length4
Median length4
Mean length3.4757
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row변동
2nd row용문동
3rd row관저2동
4th row월평3동
5th row변동

Common Values

ValueCountFrequency (%)
내동 453
 
4.5%
둔산2동 453
 
4.5%
월평2동 451
 
4.5%
용문동 447
 
4.5%
정림동 444
 
4.4%
가장동 443
 
4.4%
갈마1동 442
 
4.4%
월평1동 441
 
4.4%
탄방동 441
 
4.4%
만년동 440
 
4.4%
Other values (13) 5545
55.5%

Length

2023-12-12T22:10:44.247252image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
내동 453
 
4.5%
둔산2동 453
 
4.5%
월평2동 451
 
4.5%
용문동 447
 
4.5%
정림동 444
 
4.4%
가장동 443
 
4.4%
갈마1동 442
 
4.4%
월평1동 441
 
4.4%
탄방동 441
 
4.4%
만년동 440
 
4.4%
Other values (13) 5545
55.5%

요일코드
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct7
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2.9766
Minimum0
Maximum6
Zeros1482
Zeros (%)14.8%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2023-12-12T22:10:44.356804image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q11
median3
Q35
95-th percentile6
Maximum6
Range6
Interquartile range (IQR)4

Descriptive statistics

Standard deviation2.0050572
Coefficient of variation (CV)0.67360654
Kurtosis-1.25017
Mean2.9766
Median Absolute Deviation (MAD)2
Skewness0.0099283027
Sum29766
Variance4.0202545
MonotonicityNot monotonic
2023-12-12T22:10:44.541582image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=7)
ValueCountFrequency (%)
0 1482
14.8%
4 1447
14.5%
3 1440
14.4%
1 1429
14.3%
6 1419
14.2%
2 1400
14.0%
5 1383
13.8%
ValueCountFrequency (%)
0 1482
14.8%
1 1429
14.3%
2 1400
14.0%
3 1440
14.4%
4 1447
14.5%
5 1383
13.8%
6 1419
14.2%
ValueCountFrequency (%)
6 1419
14.2%
5 1383
13.8%
4 1447
14.5%
3 1440
14.4%
2 1400
14.0%
1 1429
14.3%
0 1482
14.8%

요일
Categorical

HIGH CORRELATION 

Distinct7
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
일요일
1482 
목요일
1447 
수요일
1440 
월요일
1429 
토요일
1419 
Other values (2)
2783 

Length

Max length3
Median length3
Mean length3
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row일요일
2nd row월요일
3rd row수요일
4th row토요일
5th row금요일

Common Values

ValueCountFrequency (%)
일요일 1482
14.8%
목요일 1447
14.5%
수요일 1440
14.4%
월요일 1429
14.3%
토요일 1419
14.2%
화요일 1400
14.0%
금요일 1383
13.8%

Length

2023-12-12T22:10:44.713171image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T22:10:44.862613image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
일요일 1482
14.8%
목요일 1447
14.5%
수요일 1440
14.4%
월요일 1429
14.3%
토요일 1419
14.2%
화요일 1400
14.0%
금요일 1383
13.8%

시간대코드
Categorical

HIGH CORRELATION 

Distinct5
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
4
2039 
1
2018 
5
2008 
3
1985 
2
1950 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row4
2nd row2
3rd row1
4th row1
5th row2

Common Values

ValueCountFrequency (%)
4 2039
20.4%
1 2018
20.2%
5 2008
20.1%
3 1985
19.9%
2 1950
19.5%

Length

2023-12-12T22:10:45.015512image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T22:10:45.137242image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
4 2039
20.4%
1 2018
20.2%
5 2008
20.1%
3 1985
19.9%
2 1950
19.5%

시간대
Categorical

HIGH CORRELATION 

Distinct5
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
저녁
2039 
출근
2018 
야간
2008 
퇴근
1985 
주간
1950 

Length

Max length2
Median length2
Mean length2
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
저녁 2039
20.4%
출근 2018
20.2%
야간 2008
20.1%
퇴근 1985
19.9%
주간 1950
19.5%

Length

2023-12-12T22:10:45.292678image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T22:10:45.420909image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
저녁 2039
20.4%
출근 2018
20.2%
야간 2008
20.1%
퇴근 1985
19.9%
주간 1950
19.5%

성별코드
Categorical

HIGH CORRELATION 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
m
5040 
f
4960 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
m 5040
50.4%
f 4960
49.6%

Length

2023-12-12T22:10:45.589556image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T22:10:45.698338image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
m 5040
50.4%
f 4960
49.6%

성별
Categorical

HIGH CORRELATION 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
남성
5040 
여성
4960 

Length

Max length2
Median length2
Mean length2
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
남성 5040
50.4%
여성 4960
49.6%

Length

2023-12-12T22:10:45.815976image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T22:10:45.921442image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
남성 5040
50.4%
여성 4960
49.6%

비율
Real number (ℝ)

Distinct1774
Distinct (%)17.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean49.976891
Minimum27.01
Maximum72.99
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2023-12-12T22:10:46.369876image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum27.01
5-th percentile44.1795
Q147.98
median49.96
Q351.99
95-th percentile55.7305
Maximum72.99
Range45.98
Interquartile range (IQR)4.01

Descriptive statistics

Standard deviation3.7040663
Coefficient of variation (CV)0.074115581
Kurtosis4.0564794
Mean49.976891
Median Absolute Deviation (MAD)2
Skewness0.052463066
Sum499768.91
Variance13.720107
MonotonicityNot monotonic
2023-12-12T22:10:46.581994image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
48.46 24
 
0.2%
49.86 24
 
0.2%
52.32 23
 
0.2%
50.33 23
 
0.2%
50.74 22
 
0.2%
49.53 22
 
0.2%
49.84 21
 
0.2%
49.73 21
 
0.2%
48.12 21
 
0.2%
47.97 20
 
0.2%
Other values (1764) 9779
97.8%
ValueCountFrequency (%)
27.01 1
< 0.1%
28.4 1
< 0.1%
28.57 1
< 0.1%
29.13 1
< 0.1%
29.47 1
< 0.1%
29.68 1
< 0.1%
30.86 1
< 0.1%
30.87 1
< 0.1%
30.88 1
< 0.1%
30.89 1
< 0.1%
ValueCountFrequency (%)
72.99 1
< 0.1%
71.6 1
< 0.1%
71.43 1
< 0.1%
70.88 1
< 0.1%
70.32 2
< 0.1%
69.31 1
< 0.1%
69.26 1
< 0.1%
69.14 1
< 0.1%
69.11 1
< 0.1%
68.8 1
< 0.1%

데이터생성일자
Categorical

CONSTANT 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2023-05-10
10000 

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 10000
100.0%

Length

2023-12-12T22:10:46.733290image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T22:10:46.839780image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2023-05-10 10000
100.0%

Interactions

2023-12-12T22:10:42.449112image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T22:10:40.091941image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T22:10:40.710533image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T22:10:41.301256image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T22:10:41.931962image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T22:10:42.538944image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T22:10:40.212505image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T22:10:40.828885image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T22:10:41.451549image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T22:10:42.052213image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T22:10:42.624143image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T22:10:40.328721image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T22:10:40.942768image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T22:10:41.588856image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T22:10:42.139615image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T22:10:42.734155image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T22:10:40.465629image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T22:10:41.062871image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T22:10:41.702814image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T22:10:42.254707image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T22:10:42.845933image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T22:10:40.578142image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T22:10:41.196490image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T22:10:41.817968image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T22:10:42.351589image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-12T22:10:46.914935image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
순번기준월행정동코드행정동명요일코드요일시간대코드시간대성별코드성별비율
순번1.0000.9820.2120.2610.0000.0000.0000.0000.0000.0000.111
기준월0.9821.0000.0000.0000.0000.0000.0000.0000.0000.0000.083
행정동코드0.2120.0001.0001.0000.0000.0000.0000.0000.0000.0000.279
행정동명0.2610.0001.0001.0000.0000.0000.0000.0000.0000.0000.640
요일코드0.0000.0000.0000.0001.0001.0000.0000.0000.0000.0000.026
요일0.0000.0000.0000.0001.0001.0000.0000.0000.0000.0000.026
시간대코드0.0000.0000.0000.0000.0000.0001.0001.0000.0000.0000.280
시간대0.0000.0000.0000.0000.0000.0001.0001.0000.0000.0000.280
성별코드0.0000.0000.0000.0000.0000.0000.0000.0001.0001.0000.307
성별0.0000.0000.0000.0000.0000.0000.0000.0001.0001.0000.307
비율0.1110.0830.2790.6400.0260.0260.2800.2800.3070.3071.000
2023-12-12T22:10:47.083799image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
성별성별코드시간대행정동명시간대코드요일
성별1.0001.0000.0000.0000.0000.000
성별코드1.0001.0000.0000.0000.0000.000
시간대0.0000.0001.0000.0001.0000.000
행정동명0.0000.0000.0001.0000.0000.000
시간대코드0.0000.0001.0000.0001.0000.000
요일0.0000.0000.0000.0000.0001.000
2023-12-12T22:10:47.220673image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
순번기준월행정동코드요일코드비율행정동명요일시간대코드시간대성별코드성별
순번1.0000.9970.0780.007-0.0060.0990.0000.0000.0000.0000.000
기준월0.9971.000-0.0050.005-0.0060.0000.0000.0000.0000.0000.000
행정동코드0.078-0.0051.000-0.020-0.0050.9990.0000.0000.0000.0000.000
요일코드0.0070.005-0.0201.0000.0110.0001.0000.0000.0000.0000.000
비율-0.006-0.006-0.0050.0111.0000.2970.0130.1200.1200.2350.235
행정동명0.0990.0000.9990.0000.2971.0000.0000.0000.0000.0000.000
요일0.0000.0000.0001.0000.0130.0001.0000.0000.0000.0000.000
시간대코드0.0000.0000.0000.0000.1200.0000.0001.0001.0000.0000.000
시간대0.0000.0000.0000.0000.1200.0000.0001.0001.0000.0000.000
성별코드0.0000.0000.0000.0000.2350.0000.0000.0000.0001.0001.000
성별0.0000.0000.0000.0000.2350.0000.0000.0000.0001.0001.000

Missing values

2023-12-12T22:10:42.977008image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-12T22:10:43.145411image/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

순번기준년기준월행정동코드행정동명요일코드요일시간대코드시간대성별코드성별비율데이터생성일자
35063507202133017054000변동0일요일4저녁f여성48.992023-05-10
16462164632021113017055000용문동1월요일2주간f여성52.612023-05-10
60516052202143017059700관저2동3수요일1출근m남성46.292023-05-10
90909091202163017058800월평3동6토요일1출근f여성47.752023-05-10
18043180442021123017054000변동5금요일2주간m남성49.512023-05-10
46884689202133017064000둔산2동6토요일5야간f여성41.422023-05-10
17558175592021113017064000둔산2동5금요일5야간f여성44.142023-05-10
76657666202153017059700관저2동3수요일3퇴근m남성47.452023-05-10
59865987202143017059600관저1동3수요일4저녁f여성52.282023-05-10
1254112542202183017060000기성동1월요일1출근m남성69.262023-05-10
순번기준년기준월행정동코드행정동명요일코드요일시간대코드시간대성별코드성별비율데이터생성일자
18074180752021123017055000용문동1월요일3퇴근f여성51.432023-05-10
1005310054202173017055000용문동4목요일2주간m남성47.662023-05-10
47514752202133017065000만년동6토요일1출근m남성57.082023-05-10
17653176542021113017066000둔산3동1월요일2주간m남성41.282023-05-10
85508551202163017056000괴정동1월요일1출근f여성49.952023-05-10
14531454202113017064000둔산2동5금요일2주간m남성48.82023-05-10
14563145642021103017052000도마1동0일요일2주간m남성52.362023-05-10
38953896202133017057500내동4목요일3퇴근m남성45.892023-05-10
61026103202143017060000기성동1월요일2주간f여성41.542023-05-10
16197161982021113017052000도마1동2화요일4저녁m남성51.522023-05-10