Overview

Dataset statistics

Number of variables13
Number of observations10000
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory1.2 MiB
Average record size in memory124.0 B

Variable types

Numeric12
Categorical1

Dataset

Description해당 데이터는 경기도 수원시의 일평균 유동인구 데이터로 격자정보, 성별 인구 수, 연령대별 인구 수 데이터를 포함합니다.
Author경기도 수원시
URLhttps://www.data.go.kr/data/15096300/fileData.do

Alerts

데이터기준일자 has constant value ""Constant
격자 id 번호 is highly overall correlated with 좌측 격자 위치 and 1 other fieldsHigh correlation
좌측 격자 위치 is highly overall correlated with 격자 id 번호 and 1 other fieldsHigh correlation
상단 격자 위치 is highly overall correlated with 하단 격자 위치High correlation
우측 격자 위치 is highly overall correlated with 격자 id 번호 and 1 other fieldsHigh correlation
하단 격자 위치 is highly overall correlated with 상단 격자 위치High correlation
일평균 유동인구 is highly overall correlated with 일평균 남성 유동인구 and 5 other fieldsHigh correlation
일평균 남성 유동인구 is highly overall correlated with 일평균 유동인구 and 5 other fieldsHigh correlation
일평균 여성 유동인구 is highly overall correlated with 일평균 유동인구 and 5 other fieldsHigh correlation
0세_20세 미만 일평균 유동인구 is highly overall correlated with 일평균 유동인구 and 5 other fieldsHigh correlation
20세_40세 미만 일평균 유동인구 is highly overall correlated with 일평균 유동인구 and 5 other fieldsHigh correlation
40세_65세 미만 일평균 유동인구 is highly overall correlated with 일평균 유동인구 and 5 other fieldsHigh correlation
65세 이상 일평균 유동인구 is highly overall correlated with 일평균 유동인구 and 5 other fieldsHigh correlation
격자 id 번호 has unique valuesUnique

Reproduction

Analysis started2023-12-12 20:53:25.568896
Analysis finished2023-12-12 20:53:46.892930
Duration21.32 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

격자 id 번호
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct10000
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean9869.6797
Minimum73
Maximum19804
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2023-12-13T05:53:47.230131image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum73
5-th percentile2280.95
Q16156.75
median10129.5
Q313444.25
95-th percentile17318.1
Maximum19804
Range19731
Interquartile range (IQR)7287.5

Descriptive statistics

Standard deviation4624.3195
Coefficient of variation (CV)0.46853795
Kurtosis-0.87689447
Mean9869.6797
Median Absolute Deviation (MAD)3680
Skewness-0.011966234
Sum98696797
Variance21384331
MonotonicityNot monotonic
2023-12-13T05:53:47.392354image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
11274 1
 
< 0.1%
15366 1
 
< 0.1%
10360 1
 
< 0.1%
6137 1
 
< 0.1%
3951 1
 
< 0.1%
6737 1
 
< 0.1%
16081 1
 
< 0.1%
12050 1
 
< 0.1%
6305 1
 
< 0.1%
11570 1
 
< 0.1%
Other values (9990) 9990
99.9%
ValueCountFrequency (%)
73 1
< 0.1%
74 1
< 0.1%
75 1
< 0.1%
76 1
< 0.1%
77 1
< 0.1%
78 1
< 0.1%
79 1
< 0.1%
81 1
< 0.1%
82 1
< 0.1%
84 1
< 0.1%
ValueCountFrequency (%)
19804 1
< 0.1%
19796 1
< 0.1%
19795 1
< 0.1%
19794 1
< 0.1%
19793 1
< 0.1%
19792 1
< 0.1%
19667 1
< 0.1%
19666 1
< 0.1%
19665 1
< 0.1%
19663 1
< 0.1%

좌측 격자 위치
Real number (ℝ)

HIGH CORRELATION 

Distinct144
Distinct (%)1.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean312171.88
Minimum305077
Maximum319377
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2023-12-13T05:53:47.554327image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum305077
5-th percentile306677
Q1309477
median312377
Q3314777
95-th percentile317577
Maximum319377
Range14300
Interquartile range (IQR)5300

Descriptive statistics

Standard deviation3349.6767
Coefficient of variation (CV)0.010730232
Kurtosis-0.87724263
Mean312171.88
Median Absolute Deviation (MAD)2700
Skewness-0.014536487
Sum3.1217188 × 109
Variance11220334
MonotonicityNot monotonic
2023-12-13T05:53:47.697929image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
312877 126
 
1.3%
312977 121
 
1.2%
313377 121
 
1.2%
313277 119
 
1.2%
313077 118
 
1.2%
312677 117
 
1.2%
313477 115
 
1.1%
312777 114
 
1.1%
313177 111
 
1.1%
308977 108
 
1.1%
Other values (134) 8830
88.3%
ValueCountFrequency (%)
305077 12
 
0.1%
305177 19
0.2%
305277 22
0.2%
305377 22
0.2%
305477 21
0.2%
305577 31
0.3%
305677 31
0.3%
305777 30
0.3%
305877 31
0.3%
305977 32
0.3%
ValueCountFrequency (%)
319377 6
 
0.1%
319277 12
 
0.1%
319177 14
 
0.1%
319077 17
0.2%
318977 19
0.2%
318877 25
0.2%
318777 26
0.3%
318677 32
0.3%
318577 35
0.4%
318477 31
0.3%

상단 격자 위치
Real number (ℝ)

HIGH CORRELATION 

Distinct137
Distinct (%)1.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean520093.47
Minimum514268
Maximum527868
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2023-12-13T05:53:47.835492image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum514268
5-th percentile515668
Q1517868
median519968
Q3522168
95-th percentile525068
Maximum527868
Range13600
Interquartile range (IQR)4300

Descriptive statistics

Standard deviation2887.0628
Coefficient of variation (CV)0.0055510461
Kurtosis-0.59808607
Mean520093.47
Median Absolute Deviation (MAD)2100
Skewness0.25399606
Sum5.2009347 × 109
Variance8335131.8
MonotonicityNot monotonic
2023-12-13T05:53:48.012805image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
518768 127
 
1.3%
521468 127
 
1.3%
518568 127
 
1.3%
518668 124
 
1.2%
518268 124
 
1.2%
521668 124
 
1.2%
521768 123
 
1.2%
518468 123
 
1.2%
521568 123
 
1.2%
518368 122
 
1.2%
Other values (127) 8756
87.6%
ValueCountFrequency (%)
514268 4
 
< 0.1%
514368 13
 
0.1%
514468 11
 
0.1%
514568 13
 
0.1%
514668 10
 
0.1%
514768 15
 
0.1%
514868 28
0.3%
514968 33
0.3%
515068 42
0.4%
515168 57
0.6%
ValueCountFrequency (%)
527868 2
 
< 0.1%
527768 6
 
0.1%
527668 8
0.1%
527568 7
 
0.1%
527468 9
0.1%
527368 10
0.1%
527268 15
0.1%
527168 19
0.2%
527068 17
0.2%
526968 17
0.2%

우측 격자 위치
Real number (ℝ)

HIGH CORRELATION 

Distinct144
Distinct (%)1.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean312271.88
Minimum305177
Maximum319477
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2023-12-13T05:53:48.165801image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum305177
5-th percentile306777
Q1309577
median312477
Q3314877
95-th percentile317677
Maximum319477
Range14300
Interquartile range (IQR)5300

Descriptive statistics

Standard deviation3349.6767
Coefficient of variation (CV)0.010726796
Kurtosis-0.87724263
Mean312271.88
Median Absolute Deviation (MAD)2700
Skewness-0.014536487
Sum3.1227188 × 109
Variance11220334
MonotonicityNot monotonic
2023-12-13T05:53:48.338614image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
312977 126
 
1.3%
313077 121
 
1.2%
313477 121
 
1.2%
313377 119
 
1.2%
313177 118
 
1.2%
312777 117
 
1.2%
313577 115
 
1.1%
312877 114
 
1.1%
313277 111
 
1.1%
309077 108
 
1.1%
Other values (134) 8830
88.3%
ValueCountFrequency (%)
305177 12
 
0.1%
305277 19
0.2%
305377 22
0.2%
305477 22
0.2%
305577 21
0.2%
305677 31
0.3%
305777 31
0.3%
305877 30
0.3%
305977 31
0.3%
306077 32
0.3%
ValueCountFrequency (%)
319477 6
 
0.1%
319377 12
 
0.1%
319277 14
 
0.1%
319177 17
0.2%
319077 19
0.2%
318977 25
0.2%
318877 26
0.3%
318777 32
0.3%
318677 35
0.4%
318577 31
0.3%

하단 격자 위치
Real number (ℝ)

HIGH CORRELATION 

Distinct137
Distinct (%)1.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean519993.47
Minimum514168
Maximum527768
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2023-12-13T05:53:48.518454image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum514168
5-th percentile515568
Q1517768
median519868
Q3522068
95-th percentile524968
Maximum527768
Range13600
Interquartile range (IQR)4300

Descriptive statistics

Standard deviation2887.0628
Coefficient of variation (CV)0.0055521136
Kurtosis-0.59808607
Mean519993.47
Median Absolute Deviation (MAD)2100
Skewness0.25399606
Sum5.1999347 × 109
Variance8335131.8
MonotonicityNot monotonic
2023-12-13T05:53:48.660603image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
518668 127
 
1.3%
521368 127
 
1.3%
518468 127
 
1.3%
518568 124
 
1.2%
518168 124
 
1.2%
521568 124
 
1.2%
521668 123
 
1.2%
518368 123
 
1.2%
521468 123
 
1.2%
518268 122
 
1.2%
Other values (127) 8756
87.6%
ValueCountFrequency (%)
514168 4
 
< 0.1%
514268 13
 
0.1%
514368 11
 
0.1%
514468 13
 
0.1%
514568 10
 
0.1%
514668 15
 
0.1%
514768 28
0.3%
514868 33
0.3%
514968 42
0.4%
515068 57
0.6%
ValueCountFrequency (%)
527768 2
 
< 0.1%
527668 6
 
0.1%
527568 8
0.1%
527468 7
 
0.1%
527368 9
0.1%
527268 10
0.1%
527168 15
0.1%
527068 19
0.2%
526968 17
0.2%
526868 17
0.2%

일평균 유동인구
Real number (ℝ)

HIGH CORRELATION 

Distinct9445
Distinct (%)94.5%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean639.86527
Minimum1
Maximum44293.321
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2023-12-13T05:53:48.861891image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile6.112
Q155.424672
median260.75498
Q3782.59249
95-th percentile2213.6745
Maximum44293.321
Range44292.321
Interquartile range (IQR)727.16781

Descriptive statistics

Standard deviation1341.6337
Coefficient of variation (CV)2.096744
Kurtosis224.06973
Mean639.86527
Median Absolute Deviation (MAD)240.55916
Skewness10.99815
Sum6398652.7
Variance1799980.9
MonotonicityNot monotonic
2023-12-13T05:53:49.048793image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
9.071428572 59
 
0.6%
20.1958209 57
 
0.6%
7.045 47
 
0.5%
6.112 38
 
0.4%
26.14117647 32
 
0.3%
13.07058824 13
 
0.1%
6.022857144 10
 
0.1%
10.24923077 10
 
0.1%
1.085 9
 
0.1%
319.0951912 9
 
0.1%
Other values (9435) 9716
97.2%
ValueCountFrequency (%)
1.0 6
0.1%
1.01 4
< 0.1%
1.02 3
< 0.1%
1.025 1
 
< 0.1%
1.03 2
 
< 0.1%
1.035 3
< 0.1%
1.036666667 1
 
< 0.1%
1.04 1
 
< 0.1%
1.046 1
 
< 0.1%
1.05 1
 
< 0.1%
ValueCountFrequency (%)
44293.32052 1
< 0.1%
35012.94246 1
< 0.1%
25254.28528 1
< 0.1%
24299.1644 1
< 0.1%
23702.18779 1
< 0.1%
23328.2129 1
< 0.1%
21763.16489 1
< 0.1%
18088.25167 1
< 0.1%
17718.54538 1
< 0.1%
17085.45314 1
< 0.1%

일평균 남성 유동인구
Real number (ℝ)

HIGH CORRELATION 

Distinct9445
Distinct (%)94.5%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean331.31112
Minimum0.34428571
Maximum21596.663
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2023-12-13T05:53:49.198748image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0.34428571
5-th percentile3.5383145
Q131.208007
median135.1159
Q3397.6154
95-th percentile1148.3177
Maximum21596.663
Range21596.319
Interquartile range (IQR)366.40739

Descriptive statistics

Standard deviation696.84765
Coefficient of variation (CV)2.103303
Kurtosis195.57647
Mean331.31112
Median Absolute Deviation (MAD)123.41807
Skewness10.466248
Sum3313111.2
Variance485596.65
MonotonicityNot monotonic
2023-12-13T05:53:49.364970image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
5.257142856 59
 
0.6%
10.55402985 57
 
0.6%
4.435 47
 
0.5%
3.256 38
 
0.4%
13.5794958 32
 
0.3%
6.7897479 13
 
0.1%
5.514285716 10
 
0.1%
5.36 10
 
0.1%
163.3389071 9
 
0.1%
90.65311476 9
 
0.1%
Other values (9435) 9716
97.2%
ValueCountFrequency (%)
0.344285714 1
 
< 0.1%
0.48 1
 
< 0.1%
0.51 1
 
< 0.1%
0.52 3
< 0.1%
0.5775 1
 
< 0.1%
0.585 1
 
< 0.1%
0.586 1
 
< 0.1%
0.59 1
 
< 0.1%
0.596666667 1
 
< 0.1%
0.6 1
 
< 0.1%
ValueCountFrequency (%)
21596.66333 1
< 0.1%
17032.64986 1
< 0.1%
14782.80448 1
< 0.1%
12885.22243 1
< 0.1%
12284.22661 1
< 0.1%
11354.26303 1
< 0.1%
9975.088279 1
< 0.1%
9426.277786 1
< 0.1%
9193.894671 1
< 0.1%
8928.252268 1
< 0.1%

일평균 여성 유동인구
Real number (ℝ)

HIGH CORRELATION 

Distinct9434
Distinct (%)94.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean308.55415
Minimum0
Maximum22696.657
Zeros1
Zeros (%)< 0.1%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2023-12-13T05:53:49.540637image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile2.142
Q123.974298
median121.18525
Q3382.40843
95-th percentile1074.5859
Maximum22696.657
Range22696.657
Interquartile range (IQR)358.43413

Descriptive statistics

Standard deviation656.23885
Coefficient of variation (CV)2.1268191
Kurtosis261.80838
Mean308.55415
Median Absolute Deviation (MAD)113.82827
Skewness11.775255
Sum3085541.5
Variance430649.43
MonotonicityNot monotonic
2023-12-13T05:53:49.667942image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
3.814285716 59
 
0.6%
9.641791044 57
 
0.6%
2.61 47
 
0.5%
2.856 39
 
0.4%
12.56168067 33
 
0.3%
6.280840336 13
 
0.1%
4.889230768 10
 
0.1%
0.47 10
 
0.1%
0.508571428 10
 
0.1%
88.53836064 9
 
0.1%
Other values (9424) 9713
97.1%
ValueCountFrequency (%)
0.0 1
< 0.1%
0.01 1
< 0.1%
0.075068493 1
< 0.1%
0.1 1
< 0.1%
0.100645162 1
< 0.1%
0.123333333 2
< 0.1%
0.1390625 1
< 0.1%
0.150967743 1
< 0.1%
0.170967743 1
< 0.1%
0.1825 1
< 0.1%
ValueCountFrequency (%)
22696.65719 1
< 0.1%
17980.2926 1
< 0.1%
14324.07612 1
< 0.1%
12970.05866 1
< 0.1%
11973.94986 1
< 0.1%
9241.498169 1
< 0.1%
8919.383305 1
< 0.1%
8877.942459 1
< 0.1%
8790.293116 1
< 0.1%
8062.317486 1
< 0.1%

0세_20세 미만 일평균 유동인구
Real number (ℝ)

HIGH CORRELATION 

Distinct9333
Distinct (%)93.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean49.677341
Minimum0
Maximum3950.9463
Zeros4
Zeros (%)< 0.1%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2023-12-13T05:53:49.794945image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0.10664709
Q12.7046672
median16.819636
Q357.950129
95-th percentile187.72342
Maximum3950.9463
Range3950.9463
Interquartile range (IQR)55.245461

Descriptive statistics

Standard deviation109.29847
Coefficient of variation (CV)2.2001674
Kurtosis245.69041
Mean49.677341
Median Absolute Deviation (MAD)16.268263
Skewness10.918615
Sum496773.41
Variance11946.155
MonotonicityNot monotonic
2023-12-13T05:53:49.943441image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.06 69
 
0.7%
0.05 57
 
0.6%
0.344477612 57
 
0.6%
0.136 41
 
0.4%
0.305882352 34
 
0.3%
0.04 32
 
0.3%
0.152941176 13
 
0.1%
0.08 13
 
0.1%
0.03 13
 
0.1%
0.025 10
 
0.1%
Other values (9323) 9661
96.6%
ValueCountFrequency (%)
0.0 4
< 0.1%
8.44e-05 1
 
< 0.1%
0.003333333 2
 
< 0.1%
0.004 1
 
< 0.1%
0.005 4
< 0.1%
0.009999999 2
 
< 0.1%
0.01 8
0.1%
0.010727273 1
 
< 0.1%
0.0109375 1
 
< 0.1%
0.011891892 1
 
< 0.1%
ValueCountFrequency (%)
3950.946284 1
< 0.1%
2698.766476 1
< 0.1%
1946.447432 1
< 0.1%
1796.327978 1
< 0.1%
1656.003333 1
< 0.1%
1621.94306 1
< 0.1%
1478.113087 1
< 0.1%
1386.56235 1
< 0.1%
1330.528907 1
< 0.1%
1312.263853 1
< 0.1%

20세_40세 미만 일평균 유동인구
Real number (ℝ)

HIGH CORRELATION 

Distinct9431
Distinct (%)94.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean258.27229
Minimum0.15
Maximum18900.091
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2023-12-13T05:53:50.122686image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0.15
5-th percentile1.5057143
Q120.743201
median95.229836
Q3288.12494
95-th percentile892.52579
Maximum18900.091
Range18899.941
Interquartile range (IQR)267.38174

Descriptive statistics

Standard deviation611.24198
Coefficient of variation (CV)2.3666572
Kurtosis223.78048
Mean258.27229
Median Absolute Deviation (MAD)89.308109
Skewness11.446566
Sum2582722.9
Variance373616.76
MonotonicityNot monotonic
2023-12-13T05:53:50.262417image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1.505714284 59
 
0.6%
4.349253732 57
 
0.6%
1.215 47
 
0.5%
1.368 41
 
0.4%
3.924033612 34
 
0.3%
1.962016806 13
 
0.1%
4.588571428 10
 
0.1%
3.295384616 10
 
0.1%
0.325 10
 
0.1%
51.45693988 9
 
0.1%
Other values (9421) 9710
97.1%
ValueCountFrequency (%)
0.15 1
 
< 0.1%
0.155 3
< 0.1%
0.2175 1
 
< 0.1%
0.22 1
 
< 0.1%
0.24 1
 
< 0.1%
0.245 1
 
< 0.1%
0.25 1
 
< 0.1%
0.26625 1
 
< 0.1%
0.274545455 1
 
< 0.1%
0.286 1
 
< 0.1%
ValueCountFrequency (%)
18900.09104 1
< 0.1%
16307.29924 1
< 0.1%
13249.47339 1
< 0.1%
12390.24997 1
< 0.1%
11762.15074 1
< 0.1%
10848.90719 1
< 0.1%
9875.943879 1
< 0.1%
8089.279207 1
< 0.1%
7994.564317 1
< 0.1%
7754.935355 1
< 0.1%

40세_65세 미만 일평균 유동인구
Real number (ℝ)

HIGH CORRELATION 

Distinct9435
Distinct (%)94.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean279.83769
Minimum0.2
Maximum18193.205
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2023-12-13T05:53:50.395257image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0.2
5-th percentile3.329403
Q125.431565
median115.71492
Q3350.43038
95-th percentile971.57689
Maximum18193.205
Range18193.005
Interquartile range (IQR)324.99882

Descriptive statistics

Standard deviation562.2058
Coefficient of variation (CV)2.0090425
Kurtosis207.55535
Mean279.83769
Median Absolute Deviation (MAD)105.46969
Skewness10.510567
Sum2798376.9
Variance316075.36
MonotonicityNot monotonic
2023-12-13T05:53:50.532437image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
6.56 59
 
0.6%
13.31761194 57
 
0.6%
5.15 47
 
0.5%
3.96 38
 
0.4%
17.93613445 32
 
0.3%
8.968067226 13
 
0.1%
4.57846154 10
 
0.1%
1.171428572 10
 
0.1%
117.5462295 9
 
0.1%
84.65322404 9
 
0.1%
Other values (9425) 9716
97.2%
ValueCountFrequency (%)
0.2 1
 
< 0.1%
0.34 1
 
< 0.1%
0.386666667 2
< 0.1%
0.410560748 1
 
< 0.1%
0.411666667 1
 
< 0.1%
0.42 2
< 0.1%
0.43 1
 
< 0.1%
0.47 1
 
< 0.1%
0.475714286 1
 
< 0.1%
0.48 4
< 0.1%
ValueCountFrequency (%)
18193.20541 1
< 0.1%
14288.48973 1
< 0.1%
11069.0115 1
< 0.1%
10306.18279 1
< 0.1%
9532.144481 1
< 0.1%
8853.066311 1
< 0.1%
8051.301284 1
< 0.1%
7843.437268 1
< 0.1%
7103.277513 1
< 0.1%
7022.0394 1
< 0.1%

65세 이상 일평균 유동인구
Real number (ℝ)

HIGH CORRELATION 

Distinct9361
Distinct (%)93.6%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean52.077945
Minimum0
Maximum3249.0778
Zeros1
Zeros (%)< 0.1%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2023-12-13T05:53:50.693637image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0.44200327
Q13.6887832
median19.993593
Q365.508675
95-th percentile197.76058
Maximum3249.0778
Range3249.0778
Interquartile range (IQR)61.819892

Descriptive statistics

Standard deviation95.16946
Coefficient of variation (CV)1.8274427
Kurtosis168.46666
Mean52.077945
Median Absolute Deviation (MAD)18.792202
Skewness8.3477754
Sum520779.45
Variance9057.2261
MonotonicityNot monotonic
2023-12-13T05:53:50.856678image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.945714284 59
 
0.6%
2.184477612 57
 
0.6%
0.63 48
 
0.5%
0.648 41
 
0.4%
3.975126052 33
 
0.3%
1.987563026 13
 
0.1%
0.148571428 10
 
0.1%
1.024615384 10
 
0.1%
0.06 9
 
0.1%
0.1275 9
 
0.1%
Other values (9351) 9711
97.1%
ValueCountFrequency (%)
0.0 1
 
< 0.1%
0.000126582 1
 
< 0.1%
0.016849315 1
 
< 0.1%
0.02 4
< 0.1%
0.022897196 1
 
< 0.1%
0.025714286 1
 
< 0.1%
0.02962963 1
 
< 0.1%
0.03 1
 
< 0.1%
0.034603175 1
 
< 0.1%
0.0375 1
 
< 0.1%
ValueCountFrequency (%)
3249.077787 1
< 0.1%
1718.387022 1
< 0.1%
1444.968552 1
< 0.1%
1367.349372 1
< 0.1%
1239.504317 1
< 0.1%
1168.186339 1
< 0.1%
1150.833251 1
< 0.1%
1102.088661 1
< 0.1%
1089.663306 1
< 0.1%
1039.64418 1
< 0.1%

데이터기준일자
Categorical

CONSTANT 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2021-11-30
10000 

Length

Max length10
Median length10
Mean length10
Min length10

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2021-11-30
2nd row2021-11-30
3rd row2021-11-30
4th row2021-11-30
5th row2021-11-30

Common Values

ValueCountFrequency (%)
2021-11-30 10000
100.0%

Length

2023-12-13T05:53:50.986409image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T05:53:51.094556image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2021-11-30 10000
100.0%

Interactions

2023-12-13T05:53:45.201269image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T05:53:28.900801image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T05:53:30.259377image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T05:53:31.697184image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T05:53:33.071925image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T05:53:34.858012image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T05:53:36.424321image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T05:53:37.856896image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T05:53:39.350434image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T05:53:40.529458image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T05:53:42.054459image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T05:53:43.528156image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T05:53:45.337723image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T05:53:29.004847image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T05:53:30.386092image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T05:53:31.807783image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T05:53:33.433012image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T05:53:34.973560image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T05:53:36.541132image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T05:53:38.004638image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T05:53:39.467307image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T05:53:40.924127image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T05:53:42.141737image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T05:53:43.675784image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T05:53:45.441015image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T05:53:29.100306image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T05:53:30.523832image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T05:53:31.945108image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T05:53:33.537697image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T05:53:35.109606image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T05:53:36.672168image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T05:53:38.120231image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T05:53:39.592050image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T05:53:41.045328image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T05:53:42.238441image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T05:53:43.818263image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T05:53:45.545751image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T05:53:29.221003image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T05:53:30.673099image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T05:53:32.069759image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T05:53:33.672640image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T05:53:35.232991image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T05:53:36.797154image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T05:53:38.242766image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T05:53:39.726238image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T05:53:41.144967image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T05:53:42.346305image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T05:53:43.962687image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T05:53:45.651860image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T05:53:29.326898image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T05:53:30.807724image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T05:53:32.194932image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T05:53:33.876146image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T05:53:35.364123image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T05:53:36.908934image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T05:53:38.391993image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T05:53:39.829795image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T05:53:41.244749image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T05:53:42.456801image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T05:53:44.130398image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T05:53:45.777374image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T05:53:29.437562image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T05:53:30.916704image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T05:53:32.303287image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T05:53:34.010828image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T05:53:35.479108image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T05:53:37.034335image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T05:53:38.516368image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T05:53:39.926525image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T05:53:41.341614image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T05:53:42.584587image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T05:53:44.288933image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T05:53:45.891394image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T05:53:29.538076image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T05:53:31.026724image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T05:53:32.400177image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T05:53:34.138369image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T05:53:35.588135image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T05:53:37.145164image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T05:53:38.642426image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T05:53:40.007539image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T05:53:41.436182image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T05:53:42.686827image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T05:53:44.398722image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T05:53:45.997624image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T05:53:29.649555image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T05:53:31.129288image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T05:53:32.490170image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T05:53:34.237175image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T05:53:35.700657image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T05:53:37.269467image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T05:53:38.766760image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T05:53:40.085459image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T05:53:41.521592image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T05:53:42.797442image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T05:53:44.529672image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T05:53:46.125632image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T05:53:29.744169image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T05:53:31.236605image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T05:53:32.596537image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T05:53:34.352765image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T05:53:35.849944image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T05:53:37.401380image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T05:53:38.873993image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T05:53:40.167738image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T05:53:41.617092image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T05:53:42.922350image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T05:53:44.662163image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T05:53:46.251043image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T05:53:29.894657image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T05:53:31.353542image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T05:53:32.723804image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T05:53:34.476333image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T05:53:36.002375image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T05:53:37.517721image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T05:53:38.989449image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T05:53:40.261993image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T05:53:41.746798image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T05:53:43.127924image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T05:53:44.802873image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T05:53:46.364125image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T05:53:30.029426image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T05:53:31.481717image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T05:53:32.839746image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T05:53:34.620064image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T05:53:36.136790image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T05:53:37.628246image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T05:53:39.109502image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T05:53:40.352822image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T05:53:41.862437image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T05:53:43.302883image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T05:53:44.928094image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T05:53:46.488353image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T05:53:30.150386image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T05:53:31.590035image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T05:53:32.964152image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T05:53:34.746779image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T05:53:36.289352image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T05:53:37.731297image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T05:53:39.222422image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T05:53:40.447326image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T05:53:41.962727image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T05:53:43.408819image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T05:53:45.074799image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-13T05:53:51.182605image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
격자 id 번호좌측 격자 위치상단 격자 위치우측 격자 위치하단 격자 위치일평균 유동인구일평균 남성 유동인구일평균 여성 유동인구0세_20세 미만 일평균 유동인구20세_40세 미만 일평균 유동인구40세_65세 미만 일평균 유동인구65세 이상 일평균 유동인구
격자 id 번호1.0001.0000.4511.0000.4510.0460.0600.0590.0550.0830.0440.070
좌측 격자 위치1.0001.0000.4481.0000.4480.0470.0600.0600.0520.0830.0450.070
상단 격자 위치0.4510.4481.0000.4481.0000.0500.0580.0460.0410.0780.0390.050
우측 격자 위치1.0001.0000.4481.0000.4480.0470.0600.0600.0520.0830.0450.070
하단 격자 위치0.4510.4481.0000.4481.0000.0500.0580.0460.0410.0780.0390.050
일평균 유동인구0.0460.0470.0500.0470.0501.0000.9470.9520.8850.9420.9560.903
일평균 남성 유동인구0.0600.0600.0580.0600.0580.9471.0000.9790.8810.9440.9920.908
일평균 여성 유동인구0.0590.0600.0460.0600.0460.9520.9791.0000.9020.9370.9900.917
0세_20세 미만 일평균 유동인구0.0550.0520.0410.0520.0410.8850.8810.9021.0000.8840.8940.962
20세_40세 미만 일평균 유동인구0.0830.0830.0780.0830.0780.9420.9440.9370.8841.0000.9240.898
40세_65세 미만 일평균 유동인구0.0440.0450.0390.0450.0390.9560.9920.9900.8940.9241.0000.920
65세 이상 일평균 유동인구0.0700.0700.0500.0700.0500.9030.9080.9170.9620.8980.9201.000
2023-12-13T05:53:51.695756image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
격자 id 번호좌측 격자 위치상단 격자 위치우측 격자 위치하단 격자 위치일평균 유동인구일평균 남성 유동인구일평균 여성 유동인구0세_20세 미만 일평균 유동인구20세_40세 미만 일평균 유동인구40세_65세 미만 일평균 유동인구65세 이상 일평균 유동인구
격자 id 번호1.0001.000-0.0751.000-0.0750.2770.2810.2680.2300.2950.2650.200
좌측 격자 위치1.0001.000-0.0671.000-0.0670.2760.2790.2670.2290.2940.2630.199
상단 격자 위치-0.075-0.0671.000-0.0671.000-0.173-0.189-0.144-0.123-0.212-0.158-0.096
우측 격자 위치1.0001.000-0.0671.000-0.0670.2760.2790.2670.2290.2940.2630.199
하단 격자 위치-0.075-0.0671.000-0.0671.000-0.173-0.189-0.144-0.123-0.212-0.158-0.096
일평균 유동인구0.2770.276-0.1730.276-0.1731.0000.9970.9940.9430.9910.9950.952
일평균 남성 유동인구0.2810.279-0.1890.279-0.1890.9971.0000.9830.9260.9920.9900.940
일평균 여성 유동인구0.2680.267-0.1440.267-0.1440.9940.9831.0000.9580.9790.9920.963
0세_20세 미만 일평균 유동인구0.2300.229-0.1230.229-0.1230.9430.9260.9581.0000.9210.9370.926
20세_40세 미만 일평균 유동인구0.2950.294-0.2120.294-0.2120.9910.9920.9790.9211.0000.9760.917
40세_65세 미만 일평균 유동인구0.2650.263-0.1580.263-0.1580.9950.9900.9920.9370.9761.0000.961
65세 이상 일평균 유동인구0.2000.199-0.0960.199-0.0960.9520.9400.9630.9260.9170.9611.000

Missing values

2023-12-13T05:53:46.637783image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-13T05:53:46.815492image/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

격자 id 번호좌측 격자 위치상단 격자 위치우측 격자 위치하단 격자 위치일평균 유동인구일평균 남성 유동인구일평균 여성 유동인구0세_20세 미만 일평균 유동인구20세_40세 미만 일평균 유동인구40세_65세 미만 일평균 유동인구65세 이상 일평균 유동인구데이터기준일자
644411274313177518368313277518268495.477131269.680929225.79620227.737213162.134016248.00218657.6037162021-11-30
48959302311777522368311877522268555.287214258.769517296.51769737.320031176.55795261.18834280.220892021-11-30
831413713314977522868315077522768177.8429794.91357382.9293974.42352854.5905585.10215233.7267412021-11-30
31316690309877521368309977521268693.657108322.671756370.985352110.936626212.00412329.02302441.6933382021-11-30
4093795431077751916831087751906844.97029828.48725216.4830471.5325515.67370124.8978162.8662312021-11-30
75381259831417752396831427752386818.45645711.6377546.8187020.4690883.72223211.7657892.4993482021-11-30
581240630677752196830687752186820.33850312.2485998.0899041.3393637.8037589.4057011.7896822021-11-30
5979107713128775272683129775271686.5957143.8285712.7671430.091.0528574.740.7128572021-11-30
3089661530977751506830987751496811.9609945.6438866.3171080.5935844.7479225.6789760.9405122021-11-30
1056518179318177517868318277517768620.341257289.678197330.66306101.903689183.280738306.78393428.3728962021-11-30
격자 id 번호좌측 격자 위치상단 격자 위치우측 격자 위치하단 격자 위치일평균 유동인구일평균 남성 유동인구일평균 여성 유동인구0세_20세 미만 일평균 유동인구20세_40세 미만 일평균 유동인구40세_65세 미만 일평균 유동인구65세 이상 일평균 유동인구데이터기준일자
62501106531307752546831317752536826.14117613.57949612.5616810.3058823.92403417.9361343.9751262021-11-30
3777753531047751966831057751956849.52582131.69895317.8268681.65000116.9353427.6637133.2767672021-11-30
20355288308877523568308977523468201.00188597.255443103.74644219.31360869.89661588.88674322.9049192021-11-30
8035132673146775260683147775259683.52252.21751.3050.0250.60752.5750.3152021-11-30
1071318828318677521968318777521868515.319426288.19694227.12248632.970574156.65071262.19603863.5021042021-11-30
31836743309877516068309977515968389.539277187.726649201.81262821.215516155.706273177.85734434.7601452021-11-30
9920162663167775159683168775158682522.3619671202.917351319.444618212.943061099.611057.737568152.0713392021-11-30
10731188633186775184683187775183681839.373579819.2193991020.15418189.601831774.650984761.394071113.7266942021-11-30
10923671307677519668307777519568112.45558656.97329555.4822916.74419348.51317848.4661578.7320582021-11-30
5699104553125775174683126775173681394.240601758.784508635.45609367.367268503.76918661.697049161.4071042021-11-30