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

측정항목 is highly overall correlated with 평균값High correlation
평균값 is highly overall correlated with 측정항목High correlation
국가 기준초과 구분 is highly overall correlated with 지자체 기준초과 구분High correlation
지자체 기준초과 구분 is highly overall correlated with 국가 기준초과 구분High correlation
국가 기준초과 구분 is highly imbalanced (99.5%)Imbalance
지자체 기준초과 구분 is highly imbalanced (99.5%)Imbalance
평균값 is highly skewed (γ1 = -34.2708403)Skewed
측정기 상태 has 9808 (98.1%) zerosZeros

Reproduction

Analysis started2024-04-27 12:05:17.134911
Analysis finished2024-04-27 12:05:26.209765
Duration9.07 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

측정일시
Real number (ℝ)

Distinct435
Distinct (%)4.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2.009011 × 109
Minimum2.0090101 × 109
Maximum2.0090119 × 109
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-04-27T12:05:26.416745image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum2.0090101 × 109
5-th percentile2.0090101 × 109
Q12.0090105 × 109
median2.009011 × 109
Q32.0090114 × 109
95-th percentile2.0090118 × 109
Maximum2.0090119 × 109
Range1802
Interquartile range (IQR)901

Descriptive statistics

Standard deviation524.47485
Coefficient of variation (CV)2.6106122 × 10-7
Kurtosis-1.2058591
Mean2.009011 × 109
Median Absolute Deviation (MAD)479.5
Skewness0.0076469006
Sum2.009011 × 1013
Variance275073.87
MonotonicityNot monotonic
2024-04-27T12:05:26.862820image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
2009010108 35
 
0.4%
2009011802 34
 
0.3%
2009010507 34
 
0.3%
2009010518 34
 
0.3%
2009011821 34
 
0.3%
2009011313 33
 
0.3%
2009011805 32
 
0.3%
2009010617 32
 
0.3%
2009010905 32
 
0.3%
2009011522 32
 
0.3%
Other values (425) 9668
96.7%
ValueCountFrequency (%)
2009010100 15
0.1%
2009010101 22
0.2%
2009010102 22
0.2%
2009010103 27
0.3%
2009010104 21
0.2%
2009010105 29
0.3%
2009010106 23
0.2%
2009010107 22
0.2%
2009010108 35
0.4%
2009010109 24
0.2%
ValueCountFrequency (%)
2009011902 22
0.2%
2009011901 24
0.2%
2009011900 22
0.2%
2009011823 24
0.2%
2009011822 30
0.3%
2009011821 34
0.3%
2009011820 25
0.2%
2009011819 25
0.2%
2009011818 26
0.3%
2009011817 14
0.1%

측정소 코드
Real number (ℝ)

Distinct25
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean112.9829
Minimum101
Maximum125
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-04-27T12:05:27.310571image/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 deviation7.2568777
Coefficient of variation (CV)0.064229876
Kurtosis-1.2075917
Mean112.9829
Median Absolute Deviation (MAD)6
Skewness0.0044423865
Sum1129829
Variance52.662274
MonotonicityNot monotonic
2024-04-27T12:05:27.668525image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=25)
ValueCountFrequency (%)
125 430
 
4.3%
101 427
 
4.3%
107 420
 
4.2%
102 416
 
4.2%
109 412
 
4.1%
124 411
 
4.1%
115 410
 
4.1%
118 410
 
4.1%
113 408
 
4.1%
119 407
 
4.1%
Other values (15) 5849
58.5%
ValueCountFrequency (%)
101 427
4.3%
102 416
4.2%
103 382
3.8%
104 396
4.0%
105 405
4.0%
106 388
3.9%
107 420
4.2%
108 394
3.9%
109 412
4.1%
110 371
3.7%
ValueCountFrequency (%)
125 430
4.3%
124 411
4.1%
123 389
3.9%
122 386
3.9%
121 382
3.8%
120 405
4.0%
119 407
4.1%
118 410
4.1%
117 374
3.7%
116 403
4.0%

측정항목
Real number (ℝ)

HIGH CORRELATION 

Distinct6
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean5.3248
Minimum1
Maximum9
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-04-27T12:05:28.023929image/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 deviation2.7675749
Coefficient of variation (CV)0.5197519
Kurtosis-1.2256539
Mean5.3248
Median Absolute Deviation (MAD)3
Skewness-0.2042916
Sum53248
Variance7.6594709
MonotonicityNot monotonic
2024-04-27T12:05:28.309197image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=6)
ValueCountFrequency (%)
1 1713
17.1%
9 1686
16.9%
8 1665
16.7%
6 1665
16.7%
3 1652
16.5%
5 1619
16.2%
ValueCountFrequency (%)
1 1713
17.1%
3 1652
16.5%
5 1619
16.2%
6 1665
16.7%
8 1665
16.7%
9 1686
16.9%
ValueCountFrequency (%)
9 1686
16.9%
8 1665
16.7%
6 1665
16.7%
5 1619
16.2%
3 1652
16.5%
1 1713
17.1%

평균값
Real number (ℝ)

HIGH CORRELATION  SKEWED 

Distinct294
Distinct (%)2.9%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean7.8392487
Minimum-9999
Maximum2310
Zeros24
Zeros (%)0.2%
Negative17
Negative (%)0.2%
Memory size166.0 KiB
2024-04-27T12:05:28.573401image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum-9999
5-th percentile0.003
Q10.011
median0.078
Q324
95-th percentile76
Maximum2310
Range12309
Interquartile range (IQR)23.989

Descriptive statistics

Standard deviation285.88855
Coefficient of variation (CV)36.468871
Kurtosis1199.149
Mean7.8392487
Median Absolute Deviation (MAD)0.077
Skewness-34.27084
Sum78392.487
Variance81732.264
MonotonicityNot monotonic
2024-04-27T12:05:29.032908image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.006 324
 
3.2%
0.005 287
 
2.9%
0.002 281
 
2.8%
0.007 279
 
2.8%
0.003 267
 
2.7%
0.004 250
 
2.5%
0.008 228
 
2.3%
0.009 198
 
2.0%
0.4 185
 
1.8%
0.5 185
 
1.8%
Other values (284) 7516
75.2%
ValueCountFrequency (%)
-9999.0 8
 
0.1%
-999.9 2
 
< 0.1%
-9.999 7
 
0.1%
0.0 24
 
0.2%
0.001 132
1.3%
0.002 281
2.8%
0.003 267
2.7%
0.004 250
2.5%
0.005 287
2.9%
0.006 324
3.2%
ValueCountFrequency (%)
2310.0 1
< 0.1%
475.0 1
< 0.1%
379.0 1
< 0.1%
322.0 1
< 0.1%
238.0 1
< 0.1%
181.0 1
< 0.1%
178.0 1
< 0.1%
177.0 1
< 0.1%
173.0 1
< 0.1%
171.0 1
< 0.1%

측정기 상태
Real number (ℝ)

ZEROS 

Distinct6
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.0863
Minimum0
Maximum9
Zeros9808
Zeros (%)98.1%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-04-27T12:05:29.255282image/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 deviation0.79618823
Coefficient of variation (CV)9.2258196
Kurtosis109.32434
Mean0.0863
Median Absolute Deviation (MAD)0
Skewness10.398174
Sum863
Variance0.6339157
MonotonicityNot monotonic
2024-04-27T12:05:29.440711image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=6)
ValueCountFrequency (%)
0 9808
98.1%
1 74
 
0.7%
9 55
 
0.5%
2 31
 
0.3%
8 26
 
0.3%
4 6
 
0.1%
ValueCountFrequency (%)
0 9808
98.1%
1 74
 
0.7%
2 31
 
0.3%
4 6
 
0.1%
8 26
 
0.3%
9 55
 
0.5%
ValueCountFrequency (%)
9 55
 
0.5%
8 26
 
0.3%
4 6
 
0.1%
2 31
 
0.3%
1 74
 
0.7%
0 9808
98.1%

국가 기준초과 구분
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
0
9996 
1
 
4

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 9996
> 99.9%
1 4
 
< 0.1%

Length

2024-04-27T12:05:29.650121image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-27T12:05:29.855096image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 9996
> 99.9%
1 4
 
< 0.1%

지자체 기준초과 구분
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
0
9996 
1
 
4

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 9996
> 99.9%
1 4
 
< 0.1%

Length

2024-04-27T12:05:30.142785image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-27T12:05:30.340728image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 9996
> 99.9%
1 4
 
< 0.1%

Interactions

2024-04-27T12:05:23.800499image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-27T12:05:18.453939image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-27T12:05:19.901669image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-27T12:05:21.127056image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-27T12:05:22.395252image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-27T12:05:24.315701image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-27T12:05:18.797459image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-27T12:05:20.174483image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-27T12:05:21.336179image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-27T12:05:22.723399image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-27T12:05:24.578657image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-27T12:05:19.067796image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-27T12:05:20.433252image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-27T12:05:21.569129image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-27T12:05:22.990982image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-27T12:05:24.867345image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-27T12:05:19.354800image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-27T12:05:20.712510image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-27T12:05:21.836129image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-27T12:05:23.274054image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-27T12:05:25.161344image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-27T12:05:19.630982image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-27T12:05:20.950444image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-27T12:05:22.097579image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-27T12:05:23.542862image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-04-27T12:05:30.457969image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
측정일시측정소 코드측정항목평균값측정기 상태국가 기준초과 구분지자체 기준초과 구분
측정일시1.0000.0000.0000.0000.1050.0450.045
측정소 코드0.0001.0000.0000.0330.1590.0380.038
측정항목0.0000.0001.0000.0400.1350.0540.054
평균값0.0000.0330.0401.0000.5760.0000.000
측정기 상태0.1050.1590.1350.5761.0000.0000.000
국가 기준초과 구분0.0450.0380.0540.0000.0001.0000.981
지자체 기준초과 구분0.0450.0380.0540.0000.0000.9811.000
2024-04-27T12:05:30.651513image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
지자체 기준초과 구분국가 기준초과 구분
지자체 기준초과 구분1.0000.875
국가 기준초과 구분0.8751.000
2024-04-27T12:05:30.816528image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
측정일시측정소 코드측정항목평균값측정기 상태국가 기준초과 구분지자체 기준초과 구분
측정일시1.0000.0040.0040.0210.0300.0340.034
측정소 코드0.0041.000-0.0070.0010.0050.0290.029
측정항목0.004-0.0071.0000.6830.0720.0390.039
평균값0.0210.0010.6831.0000.0600.0000.000
측정기 상태0.0300.0050.0720.0601.0000.0000.000
국가 기준초과 구분0.0340.0290.0390.0000.0001.0000.875
지자체 기준초과 구분0.0340.0290.0390.0000.0000.8751.000

Missing values

2024-04-27T12:05:25.506862image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-04-27T12:05:25.927477image/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
57084200901162011510.011000
22351200901070510130.056000
205200901010111030.024000
187482009010604125874.0000
11934200901040711510.008000
24398200901071811750.9000
46629200901132212260.001000
62421200901180810460.011000
443622009011307119838.0000
185872009010603123947.0000
측정일시측정소 코드측정항목평균값측정기 상태국가 기준초과 구분지자체 기준초과 구분
4818200901020810410.006000
32709200901100210260.024000
26424200901080810510.006000
504162009011500103868.0000
57247200901162111730.081000
151312009010504122931.0000
25908200901080411910.006000
22338200901070412410.017000
18511200901060311130.049000
45360200901131411110.006000