Overview

Dataset statistics

Number of variables7
Number of observations10000
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory693.4 KiB
Average record size in memory71.0 B

Variable types

Numeric5
Categorical2

Dataset

Description파일 다운로드
Author서울특별시
URLhttps://data.seoul.go.kr/dataList/OA-15526/S/1/datasetView.do

Alerts

국가 기준초과 구분 has constant value ""Constant
지자체 기준초과 구분 has constant value ""Constant
측정항목 is highly overall correlated with 평균값High correlation
평균값 is highly overall correlated with 측정항목High correlation
측정기 상태 has 9802 (98.0%) zerosZeros

Reproduction

Analysis started2024-05-04 03:58:04.621863
Analysis finished2024-05-04 03:58:16.926423
Duration12.3 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

측정일시
Real number (ℝ)

Distinct446
Distinct (%)4.5%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2.011011 × 109
Minimum2.0110101 × 109
Maximum2.0110119 × 109
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-05-04T03:58:17.271024image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum2.0110101 × 109
5-th percentile2.0110101 × 109
Q12.0110105 × 109
median2.011011 × 109
Q32.0110114 × 109
95-th percentile2.0110118 × 109
Maximum2.0110119 × 109
Range1813
Interquartile range (IQR)907.25

Descriptive statistics

Standard deviation534.4345
Coefficient of variation (CV)2.6575414 × 10-7
Kurtosis-1.2025629
Mean2.011011 × 109
Median Absolute Deviation (MAD)492
Skewness-0.0050054639
Sum2.011011 × 1013
Variance285620.23
MonotonicityNot monotonic
2024-05-04T03:58:17.860607image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
2011010414 34
 
0.3%
2011011022 34
 
0.3%
2011011005 34
 
0.3%
2011010500 34
 
0.3%
2011011305 34
 
0.3%
2011010513 34
 
0.3%
2011011211 33
 
0.3%
2011011615 32
 
0.3%
2011010822 32
 
0.3%
2011011909 32
 
0.3%
Other values (436) 9667
96.7%
ValueCountFrequency (%)
2011010100 24
0.2%
2011010101 23
0.2%
2011010102 18
0.2%
2011010103 22
0.2%
2011010104 27
0.3%
2011010105 27
0.3%
2011010106 25
0.2%
2011010107 23
0.2%
2011010108 31
0.3%
2011010109 19
0.2%
ValueCountFrequency (%)
2011011913 14
0.1%
2011011912 21
0.2%
2011011911 25
0.2%
2011011910 15
0.1%
2011011909 32
0.3%
2011011908 19
0.2%
2011011907 23
0.2%
2011011906 21
0.2%
2011011905 22
0.2%
2011011904 27
0.3%

측정소 코드
Real number (ℝ)

Distinct25
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean113.0572
Minimum101
Maximum125
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-05-04T03:58:18.370459image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum101
5-th percentile102
Q1107
median113
Q3119
95-th percentile124
Maximum125
Range24
Interquartile range (IQR)12

Descriptive statistics

Standard deviation7.1562315
Coefficient of variation (CV)0.063297441
Kurtosis-1.1801404
Mean113.0572
Median Absolute Deviation (MAD)6
Skewness-0.012683888
Sum1130572
Variance51.211649
MonotonicityNot monotonic
2024-05-04T03:58:18.792217image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=25)
ValueCountFrequency (%)
114 434
 
4.3%
116 434
 
4.3%
109 427
 
4.3%
110 426
 
4.3%
108 414
 
4.1%
117 412
 
4.1%
101 410
 
4.1%
123 409
 
4.1%
113 409
 
4.1%
121 405
 
4.0%
Other values (15) 5820
58.2%
ValueCountFrequency (%)
101 410
4.1%
102 367
3.7%
103 383
3.8%
104 398
4.0%
105 370
3.7%
106 400
4.0%
107 374
3.7%
108 414
4.1%
109 427
4.3%
110 426
4.3%
ValueCountFrequency (%)
125 386
3.9%
124 399
4.0%
123 409
4.1%
122 394
3.9%
121 405
4.0%
120 400
4.0%
119 381
3.8%
118 401
4.0%
117 412
4.1%
116 434
4.3%

측정항목
Real number (ℝ)

HIGH CORRELATION 

Distinct6
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean5.3246
Minimum1
Maximum9
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-05-04T03:58:19.289233image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q13
median5
Q38
95-th percentile9
Maximum9
Range8
Interquartile range (IQR)5

Descriptive statistics

Standard deviation2.7376604
Coefficient of variation (CV)0.51415325
Kurtosis-1.1973041
Mean5.3246
Median Absolute Deviation (MAD)2
Skewness-0.20007258
Sum53246
Variance7.4947843
MonotonicityNot monotonic
2024-05-04T03:58:19.798070image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=6)
ValueCountFrequency (%)
5 1729
17.3%
3 1665
16.7%
8 1661
16.6%
1 1655
16.6%
6 1649
16.5%
9 1641
16.4%
ValueCountFrequency (%)
1 1655
16.6%
3 1665
16.7%
5 1729
17.3%
6 1649
16.5%
8 1661
16.6%
9 1641
16.4%
ValueCountFrequency (%)
9 1641
16.4%
8 1661
16.6%
6 1649
16.5%
5 1729
17.3%
3 1665
16.7%
1 1655
16.6%

평균값
Real number (ℝ)

HIGH CORRELATION 

Distinct230
Distinct (%)2.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean-19.17761
Minimum-9999
Maximum1068
Zeros13
Zeros (%)0.1%
Negative101
Negative (%)1.0%
Memory size166.0 KiB
2024-05-04T03:58:20.348483image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum-9999
5-th percentile0.003
Q10.01
median0.0735
Q321
95-th percentile55
Maximum1068
Range11067
Interquartile range (IQR)20.99

Descriptive statistics

Standard deviation540.95238
Coefficient of variation (CV)-28.207497
Kurtosis333.19472
Mean-19.17761
Median Absolute Deviation (MAD)0.2265
Skewness-18.22665
Sum-191776.1
Variance292629.48
MonotonicityNot monotonic
2024-05-04T03:58:20.871280image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.005 403
 
4.0%
0.006 361
 
3.6%
0.004 322
 
3.2%
0.007 274
 
2.7%
0.5 250
 
2.5%
0.4 247
 
2.5%
0.003 233
 
2.3%
0.008 218
 
2.2%
0.6 198
 
2.0%
0.002 196
 
2.0%
Other values (220) 7298
73.0%
ValueCountFrequency (%)
-9999.0 29
 
0.3%
-999.9 23
 
0.2%
-9.999 49
 
0.5%
0.0 13
 
0.1%
0.001 127
 
1.3%
0.002 196
2.0%
0.003 233
2.3%
0.004 322
3.2%
0.005 403
4.0%
0.006 361
3.6%
ValueCountFrequency (%)
1068.0 1
< 0.1%
774.0 1
< 0.1%
247.0 1
< 0.1%
140.0 1
< 0.1%
135.0 1
< 0.1%
128.0 1
< 0.1%
123.0 1
< 0.1%
117.0 1
< 0.1%
116.0 1
< 0.1%
115.0 1
< 0.1%

측정기 상태
Real number (ℝ)

ZEROS 

Distinct6
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.0732
Minimum0
Maximum9
Zeros9802
Zeros (%)98.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-05-04T03:58:21.218734image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile0
Maximum9
Range9
Interquartile range (IQR)0

Descriptive statistics

Standard deviation0.63299434
Coefficient of variation (CV)8.6474636
Kurtosis128.40949
Mean0.0732
Median Absolute Deviation (MAD)0
Skewness10.71186
Sum732
Variance0.40068183
MonotonicityNot monotonic
2024-05-04T03:58:21.555025image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=6)
ValueCountFrequency (%)
0 9802
98.0%
4 92
 
0.9%
1 66
 
0.7%
9 26
 
0.3%
2 8
 
0.1%
8 6
 
0.1%
ValueCountFrequency (%)
0 9802
98.0%
1 66
 
0.7%
2 8
 
0.1%
4 92
 
0.9%
8 6
 
0.1%
9 26
 
0.3%
ValueCountFrequency (%)
9 26
 
0.3%
8 6
 
0.1%
4 92
 
0.9%
2 8
 
0.1%
1 66
 
0.7%
0 9802
98.0%

국가 기준초과 구분
Categorical

CONSTANT 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
0
10000 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 10000
100.0%

Length

2024-05-04T03:58:21.928095image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-04T03:58:22.237097image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 10000
100.0%

지자체 기준초과 구분
Categorical

CONSTANT 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
0
10000 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 10000
100.0%

Length

2024-05-04T03:58:22.543584image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-04T03:58:22.886831image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 10000
100.0%

Interactions

2024-05-04T03:58:14.453916image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-04T03:58:06.821321image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-04T03:58:08.275406image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-04T03:58:10.271689image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-04T03:58:12.442285image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-04T03:58:14.752582image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-04T03:58:07.142975image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-04T03:58:08.887483image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-04T03:58:10.762278image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-04T03:58:12.850396image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-04T03:58:15.024665image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-04T03:58:07.445378image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-04T03:58:09.191351image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-04T03:58:11.247519image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-04T03:58:13.306961image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-04T03:58:15.347004image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-04T03:58:07.726107image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-04T03:58:09.499408image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-04T03:58:11.643227image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-04T03:58:13.685147image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-04T03:58:15.654531image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-04T03:58:07.999301image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-04T03:58:09.877359image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-04T03:58:12.030849image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-04T03:58:14.072086image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-05-04T03:58:23.063253image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
측정일시측정소 코드측정항목평균값측정기 상태
측정일시1.0000.0270.0000.0640.145
측정소 코드0.0271.0000.0000.1260.210
측정항목0.0000.0001.0000.1430.112
평균값0.0640.1260.1431.0000.686
측정기 상태0.1450.2100.1120.6861.000
2024-05-04T03:58:23.335289image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
측정일시측정소 코드측정항목평균값측정기 상태
측정일시1.000-0.023-0.013-0.0680.081
측정소 코드-0.0231.000-0.0100.014-0.083
측정항목-0.013-0.0101.0000.7040.031
평균값-0.0680.0140.7041.000-0.097
측정기 상태0.081-0.0830.031-0.0971.000

Missing values

2024-05-04T03:58:16.139737image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-05-04T03:58:16.687936image/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

측정일시측정소 코드측정항목평균값측정기 상태국가 기준초과 구분지자체 기준초과 구분
31661201101091910298.0000
54816201101160511210.003000
488802011011413122893.0100
28692201101082310810.013000
663232011011910104927.0000
63182201101181310650.5000
182992011010601125920.0000
36518201101110311251.0000
180942011010600116837.0000
26204201101080611851.2000
측정일시측정소 코드측정항목평균값측정기 상태국가 기준초과 구분지자체 기준초과 구분
566512011011617117931.0000
58710201101170711110.005000
11487201101040411560.012000
4065201101020310360.002000
342112011011012102910.0000
27318201101081410410.009000
32930201101100311450.5000
55615201101161012030.019000
23520201101071212110.005000
605452011011719116913.0000