Overview

Dataset statistics

Number of variables6
Number of observations121
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory6.4 KiB
Average record size in memory54.1 B

Variable types

DateTime1
Numeric5

Dataset

Description서대문구 독립공원 유동인구 센서에서 측정된 2024년 1월 1일부터 2024년 4월 30일까지 일일 유동인구 데이터입니다.
Author서울특별시 서대문구
URLhttps://www.data.go.kr/data/15126748/fileData.do

Alerts

전체 is highly overall correlated with (R1) 독립관앞 and 3 other fieldsHigh correlation
(R1) 독립관앞 is highly overall correlated with 전체 and 3 other fieldsHigh correlation
(R2) 산책로 is highly overall correlated with 전체 and 3 other fieldsHigh correlation
(R3) 방문자센터앞 is highly overall correlated with 전체 and 3 other fieldsHigh correlation
(R4) CU편의점 is highly overall correlated with 전체 and 3 other fieldsHigh correlation
날짜 has unique valuesUnique

Reproduction

Analysis started2024-05-04 08:03:44.042931
Analysis finished2024-05-04 08:03:54.608998
Duration10.57 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

날짜
Date

UNIQUE 

Distinct121
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size1.1 KiB
Minimum2024-01-01 00:00:00
Maximum2024-04-30 00:00:00
2024-05-04T08:03:55.174769image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-04T08:03:55.926099image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

전체
Real number (ℝ)

HIGH CORRELATION 

Distinct120
Distinct (%)99.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1933.0661
Minimum118
Maximum7391
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.2 KiB
2024-05-04T08:03:56.503272image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum118
5-th percentile888
Q11200
median1731
Q32325
95-th percentile3940
Maximum7391
Range7273
Interquartile range (IQR)1125

Descriptive statistics

Standard deviation1022.2151
Coefficient of variation (CV)0.52880503
Kurtosis5.897536
Mean1933.0661
Median Absolute Deviation (MAD)576
Skewness1.8016571
Sum233901
Variance1044923.7
MonotonicityNot monotonic
2024-05-04T08:03:57.244349image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1498 2
 
1.7%
1869 1
 
0.8%
3876 1
 
0.8%
1425 1
 
0.8%
1340 1
 
0.8%
2138 1
 
0.8%
1751 1
 
0.8%
890 1
 
0.8%
3875 1
 
0.8%
3598 1
 
0.8%
Other values (110) 110
90.9%
ValueCountFrequency (%)
118 1
0.8%
659 1
0.8%
799 1
0.8%
800 1
0.8%
846 1
0.8%
861 1
0.8%
888 1
0.8%
890 1
0.8%
891 1
0.8%
923 1
0.8%
ValueCountFrequency (%)
7391 1
0.8%
4218 1
0.8%
4181 1
0.8%
4086 1
0.8%
3984 1
0.8%
3955 1
0.8%
3940 1
0.8%
3876 1
0.8%
3875 1
0.8%
3598 1
0.8%

(R1) 독립관앞
Real number (ℝ)

HIGH CORRELATION 

Distinct115
Distinct (%)95.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1141.8926
Minimum85
Maximum3759
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.2 KiB
2024-05-04T08:03:57.714856image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum85
5-th percentile585
Q1763
median1054
Q31354
95-th percentile1998
Maximum3759
Range3674
Interquartile range (IQR)591

Descriptive statistics

Standard deviation493.34746
Coefficient of variation (CV)0.43204367
Kurtosis5.5302474
Mean1141.8926
Median Absolute Deviation (MAD)295
Skewness1.5539046
Sum138169
Variance243391.71
MonotonicityNot monotonic
2024-05-04T08:03:58.288725image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
633 2
 
1.7%
1051 2
 
1.7%
544 2
 
1.7%
916 2
 
1.7%
876 2
 
1.7%
638 2
 
1.7%
925 1
 
0.8%
982 1
 
0.8%
1344 1
 
0.8%
1045 1
 
0.8%
Other values (105) 105
86.8%
ValueCountFrequency (%)
85 1
0.8%
536 1
0.8%
544 2
1.7%
552 1
0.8%
582 1
0.8%
585 1
0.8%
614 1
0.8%
615 1
0.8%
616 1
0.8%
620 1
0.8%
ValueCountFrequency (%)
3759 1
0.8%
2280 1
0.8%
2111 1
0.8%
2102 1
0.8%
2098 1
0.8%
2070 1
0.8%
1998 1
0.8%
1951 1
0.8%
1882 1
0.8%
1872 1
0.8%

(R2) 산책로
Real number (ℝ)

HIGH CORRELATION 

Distinct89
Distinct (%)73.6%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean134.6281
Minimum5
Maximum302
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.2 KiB
2024-05-04T08:03:58.743297image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum5
5-th percentile64
Q1105
median131
Q3167
95-th percentile221
Maximum302
Range297
Interquartile range (IQR)62

Descriptive statistics

Standard deviation47.465976
Coefficient of variation (CV)0.35257109
Kurtosis0.69555275
Mean134.6281
Median Absolute Deviation (MAD)28
Skewness0.42148183
Sum16290
Variance2253.0189
MonotonicityNot monotonic
2024-05-04T08:03:59.191453image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
147 3
 
2.5%
126 3
 
2.5%
137 3
 
2.5%
140 3
 
2.5%
120 3
 
2.5%
159 2
 
1.7%
177 2
 
1.7%
112 2
 
1.7%
196 2
 
1.7%
122 2
 
1.7%
Other values (79) 96
79.3%
ValueCountFrequency (%)
5 1
0.8%
43 1
0.8%
50 1
0.8%
55 1
0.8%
59 1
0.8%
61 1
0.8%
64 1
0.8%
65 1
0.8%
68 1
0.8%
75 1
0.8%
ValueCountFrequency (%)
302 1
0.8%
245 1
0.8%
239 1
0.8%
226 1
0.8%
222 2
1.7%
221 1
0.8%
212 1
0.8%
201 1
0.8%
200 1
0.8%
196 2
1.7%

(R3) 방문자센터앞
Real number (ℝ)

HIGH CORRELATION 

Distinct83
Distinct (%)68.6%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean124.58678
Minimum24
Maximum920
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.2 KiB
2024-05-04T08:03:59.867428image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum24
5-th percentile66
Q188
median113
Q3142
95-th percentile193
Maximum920
Range896
Interquartile range (IQR)54

Descriptive statistics

Standard deviation84.805529
Coefficient of variation (CV)0.68069447
Kurtosis65.452779
Mean124.58678
Median Absolute Deviation (MAD)27
Skewness7.1766382
Sum15075
Variance7191.9778
MonotonicityNot monotonic
2024-05-04T08:04:00.310007image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
83 5
 
4.1%
88 5
 
4.1%
132 3
 
2.5%
105 3
 
2.5%
85 3
 
2.5%
116 3
 
2.5%
86 3
 
2.5%
101 3
 
2.5%
112 3
 
2.5%
151 2
 
1.7%
Other values (73) 88
72.7%
ValueCountFrequency (%)
24 1
0.8%
53 1
0.8%
56 1
0.8%
59 1
0.8%
62 1
0.8%
66 2
1.7%
67 1
0.8%
68 1
0.8%
70 2
1.7%
72 2
1.7%
ValueCountFrequency (%)
920 1
0.8%
372 1
0.8%
209 1
0.8%
206 1
0.8%
204 1
0.8%
194 1
0.8%
193 1
0.8%
183 1
0.8%
182 1
0.8%
175 1
0.8%

(R4) CU편의점
Real number (ℝ)

HIGH CORRELATION 

Distinct116
Distinct (%)95.9%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean768.42975
Minimum17
Maximum3880
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.2 KiB
2024-05-04T08:04:00.781142image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum17
5-th percentile199
Q1359
median544
Q3945
95-th percentile1929
Maximum3880
Range3863
Interquartile range (IQR)586

Descriptive statistics

Standard deviation601.0104
Coefficient of variation (CV)0.78212796
Kurtosis5.4986686
Mean768.42975
Median Absolute Deviation (MAD)261
Skewness1.934186
Sum92980
Variance361213.5
MonotonicityNot monotonic
2024-05-04T08:04:01.386831image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
347 2
 
1.7%
1191 2
 
1.7%
1679 2
 
1.7%
1067 2
 
1.7%
481 2
 
1.7%
351 1
 
0.8%
750 1
 
0.8%
454 1
 
0.8%
1091 1
 
0.8%
204 1
 
0.8%
Other values (106) 106
87.6%
ValueCountFrequency (%)
17 1
0.8%
85 1
0.8%
125 1
0.8%
144 1
0.8%
168 1
0.8%
194 1
0.8%
199 1
0.8%
204 1
0.8%
225 1
0.8%
231 1
0.8%
ValueCountFrequency (%)
3880 1
0.8%
2495 1
0.8%
2127 1
0.8%
2106 1
0.8%
2004 1
0.8%
1970 1
0.8%
1929 1
0.8%
1903 1
0.8%
1896 1
0.8%
1808 1
0.8%

Interactions

2024-05-04T08:03:51.133283image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-04T08:03:44.361346image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-04T08:03:46.009718image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-04T08:03:47.606893image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-04T08:03:49.668908image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-04T08:03:51.461355image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-04T08:03:44.762790image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-04T08:03:46.285082image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-04T08:03:48.152360image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-04T08:03:49.934873image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-04T08:03:51.932640image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-04T08:03:45.120013image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-04T08:03:46.691805image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-04T08:03:48.759670image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-04T08:03:50.197110image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-04T08:03:52.321106image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-04T08:03:45.402936image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-04T08:03:46.987902image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-04T08:03:49.009100image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-04T08:03:50.474467image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-04T08:03:52.694002image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-04T08:03:45.654902image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-04T08:03:47.272811image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-04T08:03:49.290784image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-04T08:03:50.719481image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-05-04T08:04:01.751520image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
전체(R1) 독립관앞(R2) 산책로(R3) 방문자센터앞(R4) CU편의점
전체1.0000.9650.7530.7670.870
(R1) 독립관앞0.9651.0000.8130.7590.810
(R2) 산책로0.7530.8131.0000.7280.593
(R3) 방문자센터앞0.7670.7590.7281.0000.871
(R4) CU편의점0.8700.8100.5930.8711.000
2024-05-04T08:04:02.155266image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
전체(R1) 독립관앞(R2) 산책로(R3) 방문자센터앞(R4) CU편의점
전체1.0000.9770.8420.7850.962
(R1) 독립관앞0.9771.0000.8610.8000.892
(R2) 산책로0.8420.8611.0000.7460.757
(R3) 방문자센터앞0.7850.8000.7461.0000.700
(R4) CU편의점0.9620.8920.7570.7001.000

Missing values

2024-05-04T08:03:53.389449image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-05-04T08:03:54.242443image/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

날짜전체(R1) 독립관앞(R2) 산책로(R3) 방문자센터앞(R4) CU편의점
02024-01-011041633132114347
12024-01-02105470010068318
22024-01-031080638114112371
32024-01-041395843128113481
42024-01-05111868712699347
52024-01-0620331242150128802
62024-01-07123372264101512
72024-01-088616415570194
82024-01-098916207972225
92024-01-10110075610383317
날짜전체(R1) 독립관앞(R2) 산책로(R3) 방문자센터앞(R4) CU편의점
1112024-04-21337017661921681679
1122024-04-2220651336177167682
1132024-04-2320441219178151759
1142024-04-24230611921471281067
1152024-04-2523301359176149914
1162024-04-26267415951921431036
1172024-04-27408619983021662106
1182024-04-28321516001941011679
1192024-04-2918651171221155578
1202024-04-3023251348201112848