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 평균값 and 1 other fieldsHigh correlation
평균값 is highly overall correlated with 측정항목 and 1 other fieldsHigh correlation
측정기 상태 is highly overall correlated with 측정항목 and 1 other fieldsHigh correlation
평균값 has 579 (5.8%) zerosZeros
측정기 상태 has 5195 (51.9%) zerosZeros

Reproduction

Analysis started2024-04-27 12:07:45.379635
Analysis finished2024-04-27 12:07:53.438008
Duration8.06 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

측정일시
Real number (ℝ)

Distinct2068
Distinct (%)20.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1.988021 × 109
Minimum1.9880101 × 109
Maximum1.9880327 × 109
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-04-27T12:07:53.697015image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1.9880101 × 109
5-th percentile1.9880105 × 109
Q11.9880123 × 109
median1.9880213 × 109
Q31.9880305 × 109
95-th percentile1.9880323 × 109
Maximum1.9880327 × 109
Range22619
Interquartile range (IQR)18216

Descriptive statistics

Standard deviation8070.7092
Coefficient of variation (CV)4.05967 × 10-6
Kurtosis-1.4474015
Mean1.988021 × 109
Median Absolute Deviation (MAD)9119
Skewness0.094048095
Sum1.988021 × 1013
Variance65136347
MonotonicityNot monotonic
2024-04-27T12:07:54.143774image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1988012905 13
 
0.1%
1988021702 12
 
0.1%
1988012213 12
 
0.1%
1988032618 12
 
0.1%
1988010300 12
 
0.1%
1988012306 12
 
0.1%
1988021509 11
 
0.1%
1988010911 11
 
0.1%
1988012503 11
 
0.1%
1988011721 11
 
0.1%
Other values (2058) 9883
98.8%
ValueCountFrequency (%)
1988010100 9
0.1%
1988010101 7
0.1%
1988010102 2
 
< 0.1%
1988010103 8
0.1%
1988010104 11
0.1%
1988010105 3
 
< 0.1%
1988010106 3
 
< 0.1%
1988010107 3
 
< 0.1%
1988010108 4
 
< 0.1%
1988010109 3
 
< 0.1%
ValueCountFrequency (%)
1988032719 2
 
< 0.1%
1988032718 5
0.1%
1988032717 5
0.1%
1988032716 1
 
< 0.1%
1988032715 5
0.1%
1988032714 7
0.1%
1988032713 5
0.1%
1988032712 6
0.1%
1988032711 6
0.1%
1988032710 1
 
< 0.1%

측정소 코드
Real number (ℝ)

Distinct8
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean112.4556
Minimum103
Maximum124
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-04-27T12:07:54.677699image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum103
5-th percentile103
Q1105
median113
Q3122
95-th percentile124
Maximum124
Range21
Interquartile range (IQR)17

Descriptive statistics

Standard deviation7.4668872
Coefficient of variation (CV)0.066398536
Kurtosis-1.4071086
Mean112.4556
Median Absolute Deviation (MAD)8
Skewness0.30909746
Sum1124556
Variance55.754404
MonotonicityNot monotonic
2024-04-27T12:07:55.041511image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=8)
ValueCountFrequency (%)
103 1296
13.0%
122 1286
12.9%
124 1272
12.7%
117 1271
12.7%
107 1232
12.3%
113 1229
12.3%
105 1224
12.2%
108 1190
11.9%
ValueCountFrequency (%)
103 1296
13.0%
105 1224
12.2%
107 1232
12.3%
108 1190
11.9%
113 1229
12.3%
117 1271
12.7%
122 1286
12.9%
124 1272
12.7%
ValueCountFrequency (%)
124 1272
12.7%
122 1286
12.9%
117 1271
12.7%
113 1229
12.3%
108 1190
11.9%
107 1232
12.3%
105 1224
12.2%
103 1296
13.0%

측정항목
Real number (ℝ)

HIGH CORRELATION 

Distinct6
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean5.3683
Minimum1
Maximum9
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-04-27T12:07:55.356899image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q13
median6
Q38
95-th percentile9
Maximum9
Range8
Interquartile range (IQR)5

Descriptive statistics

Standard deviation2.7419349
Coefficient of variation (CV)0.51076409
Kurtosis-1.1943571
Mean5.3683
Median Absolute Deviation (MAD)2
Skewness-0.22822385
Sum53683
Variance7.5182069
MonotonicityNot monotonic
2024-04-27T12:07:55.760767image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=6)
ValueCountFrequency (%)
6 1717
17.2%
8 1710
17.1%
9 1666
16.7%
1 1639
16.4%
3 1636
16.4%
5 1632
16.3%
ValueCountFrequency (%)
1 1639
16.4%
3 1636
16.4%
5 1632
16.3%
6 1717
17.2%
8 1710
17.1%
9 1666
16.7%
ValueCountFrequency (%)
9 1666
16.7%
8 1710
17.1%
6 1717
17.2%
5 1632
16.3%
3 1636
16.4%
1 1639
16.4%

평균값
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct491
Distinct (%)4.9%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean-3397.4494
Minimum-9999
Maximum43.7
Zeros579
Zeros (%)5.8%
Negative4699
Negative (%)47.0%
Memory size166.0 KiB
2024-04-27T12:07:56.201681image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum-9999
5-th percentile-9999
Q1-9999
median0
Q30.048
95-th percentile4.1
Maximum43.7
Range10042.7
Interquartile range (IQR)9999.048

Descriptive statistics

Standard deviation4715.3071
Coefficient of variation (CV)-1.3878962
Kurtosis-1.5287987
Mean-3397.4494
Median Absolute Deviation (MAD)5.9
Skewness-0.68418734
Sum-33974494
Variance22234121
MonotonicityNot monotonic
2024-04-27T12:07:56.673748image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
-9999.0 3376
33.8%
-9.999 1110
 
11.1%
0.0 579
 
5.8%
-999.9 213
 
2.1%
0.001 80
 
0.8%
0.003 77
 
0.8%
0.007 67
 
0.7%
0.02 66
 
0.7%
0.006 66
 
0.7%
0.01 64
 
0.6%
Other values (481) 4302
43.0%
ValueCountFrequency (%)
-9999.0 3376
33.8%
-999.9 213
 
2.1%
-9.999 1110
 
11.1%
0.0 579
 
5.8%
0.001 80
 
0.8%
0.002 59
 
0.6%
0.003 77
 
0.8%
0.004 59
 
0.6%
0.005 45
 
0.4%
0.006 66
 
0.7%
ValueCountFrequency (%)
43.7 1
< 0.1%
41.5 1
< 0.1%
31.1 1
< 0.1%
30.4 1
< 0.1%
29.9 1
< 0.1%
29.1 1
< 0.1%
28.8 1
< 0.1%
25.3 1
< 0.1%
25.0 1
< 0.1%
24.9 1
< 0.1%

측정기 상태
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct6
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1.8379
Minimum0
Maximum9
Zeros5195
Zeros (%)51.9%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-04-27T12:07:57.046135image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q34
95-th percentile4
Maximum9
Range9
Interquartile range (IQR)4

Descriptive statistics

Standard deviation2.1256706
Coefficient of variation (CV)1.1565758
Kurtosis0.047253686
Mean1.8379
Median Absolute Deviation (MAD)0
Skewness0.79232934
Sum18379
Variance4.5184754
MonotonicityNot monotonic
2024-04-27T12:07:57.268570image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=6)
ValueCountFrequency (%)
0 5195
51.9%
4 3605
36.0%
2 940
 
9.4%
8 133
 
1.3%
9 111
 
1.1%
1 16
 
0.2%
ValueCountFrequency (%)
0 5195
51.9%
1 16
 
0.2%
2 940
 
9.4%
4 3605
36.0%
8 133
 
1.3%
9 111
 
1.1%
ValueCountFrequency (%)
9 111
 
1.1%
8 133
 
1.3%
4 3605
36.0%
2 940
 
9.4%
1 16
 
0.2%
0 5195
51.9%

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

2024-04-27T12:07:57.569478image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-27T12:07:57.797994image/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

2024-04-27T12:07:57.996702image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-27T12:07:58.217155image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 10000
100.0%

Interactions

2024-04-27T12:07:51.270867image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-27T12:07:46.637217image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-27T12:07:47.548862image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-27T12:07:48.983009image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-27T12:07:50.006915image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-27T12:07:51.592659image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-27T12:07:46.804558image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-27T12:07:47.812860image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-27T12:07:49.159877image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-27T12:07:50.266136image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-27T12:07:51.847365image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-27T12:07:46.967596image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-27T12:07:48.061272image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-27T12:07:49.337846image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-27T12:07:50.519876image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-27T12:07:52.194419image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-27T12:07:47.175409image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-27T12:07:48.510849image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-27T12:07:49.543266image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-27T12:07:50.751168image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-27T12:07:52.472650image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-27T12:07:47.367821image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-27T12:07:48.773379image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-27T12:07:49.737380image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-27T12:07:51.009964image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-04-27T12:07:58.350753image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
측정일시측정소 코드측정항목평균값측정기 상태
측정일시1.0000.0000.0260.0740.271
측정소 코드0.0001.0000.0000.1880.315
측정항목0.0260.0001.0000.4710.822
평균값0.0740.1880.4711.0000.521
측정기 상태0.2710.3150.8220.5211.000
2024-04-27T12:07:58.567405image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
측정일시측정소 코드측정항목평균값측정기 상태
측정일시1.0000.0020.0170.017-0.045
측정소 코드0.0021.0000.0070.015-0.058
측정항목0.0170.0071.000-0.7200.633
평균값0.0170.015-0.7201.000-0.886
측정기 상태-0.045-0.0580.633-0.8861.000

Missing values

2024-04-27T12:07:52.852164image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-04-27T12:07:53.264894image/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
212001988011909117511.6000
3657419880201171248-9999.0400
40813198802051010730.045000
51201198802141011760.012000
5226519880215081229-9999.0400
1339019880112141248-9999.0400
2259319880120141176-9.999200
6852519880229111139-9999.0400
42056198802061210551.8000
26426198801232211352.1000
측정일시측정소 코드측정항목평균값측정기 상태국가 기준초과 구분지자체 기준초과 구분
2147219880119151078-9999.0400
9760719880325171089-9999.0400
80564198803102210856.1000
97440198803251410310.068000
61911198802231712260.002000
7301319880304091039-9999.0400
32522198801290511352.4000
39757198802041210730.056000
6584319880227031179-9999.0400
83480198803131110554.7000