Overview

Dataset statistics

Number of variables8
Number of observations229
Missing cells99
Missing cells (%)5.4%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory15.8 KiB
Average record size in memory70.6 B

Variable types

DateTime1
Numeric6
Categorical1

Dataset

Description전라북도 무주군의 강우량 데이터로써 연월일, 무주읍, 무풍면, 설천면, 적상면, 안성면, 부남면, 데이터기준일자 컬럼으로 구성
URLhttps://www.data.go.kr/data/3040165/fileData.do

Alerts

데이터기준일자 has constant value ""Constant
무주읍 is highly overall correlated with 무풍면 and 4 other fieldsHigh correlation
무풍면 is highly overall correlated with 무주읍 and 4 other fieldsHigh correlation
설천면 is highly overall correlated with 무주읍 and 4 other fieldsHigh correlation
적상면 is highly overall correlated with 무주읍 and 4 other fieldsHigh correlation
안성면 is highly overall correlated with 무주읍 and 4 other fieldsHigh correlation
부남면 is highly overall correlated with 무주읍 and 4 other fieldsHigh correlation
무주읍 has 96 (41.9%) missing valuesMissing
연월일 has unique valuesUnique

Reproduction

Analysis started2023-12-11 23:15:59.885541
Analysis finished2023-12-11 23:16:03.755636
Duration3.87 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

연월일
Date

UNIQUE 

Distinct229
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size1.9 KiB
Minimum2004-01-01 00:00:00
Maximum2023-01-01 00:00:00
2023-12-12T08:16:03.854393image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:16:04.022788image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

무주읍
Real number (ℝ)

HIGH CORRELATION  MISSING 

Distinct97
Distinct (%)72.9%
Missing96
Missing (%)41.9%
Infinite0
Infinite (%)0.0%
Mean86.981203
Minimum1
Maximum441
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size2.1 KiB
2023-12-12T08:16:04.208429image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile3.6
Q126
median55
Q3110
95-th percentile290.6
Maximum441
Range440
Interquartile range (IQR)84

Descriptive statistics

Standard deviation90.695908
Coefficient of variation (CV)1.042707
Kurtosis3.5282248
Mean86.981203
Median Absolute Deviation (MAD)33
Skewness1.8716069
Sum11568.5
Variance8225.7478
MonotonicityNot monotonic
2023-12-12T08:16:04.377771image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
23.0 5
 
2.2%
65.0 4
 
1.7%
2.0 4
 
1.7%
47.0 3
 
1.3%
62.0 3
 
1.3%
26.0 3
 
1.3%
36.0 3
 
1.3%
51.0 3
 
1.3%
22.0 3
 
1.3%
94.0 3
 
1.3%
Other values (87) 99
43.2%
(Missing) 96
41.9%
ValueCountFrequency (%)
1.0 2
0.9%
2.0 4
1.7%
3.0 1
 
0.4%
4.0 1
 
0.4%
4.5 1
 
0.4%
5.0 1
 
0.4%
6.0 1
 
0.4%
9.0 2
0.9%
9.5 1
 
0.4%
12.0 2
0.9%
ValueCountFrequency (%)
441.0 1
0.4%
425.5 1
0.4%
402.0 1
0.4%
339.0 1
0.4%
306.0 2
0.9%
293.0 1
0.4%
289.0 1
0.4%
262.0 1
0.4%
261.5 1
0.4%
232.5 1
0.4%

무풍면
Real number (ℝ)

HIGH CORRELATION 

Distinct145
Distinct (%)63.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean88.759825
Minimum0
Maximum635
Zeros1
Zeros (%)0.4%
Negative0
Negative (%)0.0%
Memory size2.1 KiB
2023-12-12T08:16:04.527224image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile5
Q124
median54.5
Q3116
95-th percentile327.6
Maximum635
Range635
Interquartile range (IQR)92

Descriptive statistics

Standard deviation105.93496
Coefficient of variation (CV)1.1935012
Kurtosis7.2346692
Mean88.759825
Median Absolute Deviation (MAD)37.5
Skewness2.4615296
Sum20326
Variance11222.216
MonotonicityNot monotonic
2023-12-12T08:16:04.666600image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
28.0 6
 
2.6%
23.0 6
 
2.6%
5.0 6
 
2.6%
24.0 5
 
2.2%
60.0 5
 
2.2%
38.0 4
 
1.7%
55.0 4
 
1.7%
6.0 3
 
1.3%
49.0 3
 
1.3%
7.0 3
 
1.3%
Other values (135) 184
80.3%
ValueCountFrequency (%)
0.0 1
 
0.4%
1.0 2
 
0.9%
1.5 2
 
0.9%
2.0 2
 
0.9%
3.0 2
 
0.9%
4.0 1
 
0.4%
5.0 6
2.6%
6.0 3
1.3%
6.5 1
 
0.4%
7.0 3
1.3%
ValueCountFrequency (%)
635.0 1
0.4%
617.0 1
0.4%
491.5 1
0.4%
439.0 1
0.4%
429.0 1
0.4%
421.0 1
0.4%
405.0 1
0.4%
386.0 1
0.4%
382.0 1
0.4%
365.0 1
0.4%

설천면
Real number (ℝ)

HIGH CORRELATION 

Distinct151
Distinct (%)66.5%
Missing2
Missing (%)0.9%
Infinite0
Infinite (%)0.0%
Mean92.42467
Minimum0.5
Maximum612
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size2.1 KiB
2023-12-12T08:16:04.803376image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0.5
5-th percentile4
Q124.5
median59
Q3124.5
95-th percentile348.1
Maximum612
Range611.5
Interquartile range (IQR)100

Descriptive statistics

Standard deviation105.3027
Coefficient of variation (CV)1.1393354
Kurtosis4.5511954
Mean92.42467
Median Absolute Deviation (MAD)39
Skewness2.0604489
Sum20980.4
Variance11088.658
MonotonicityNot monotonic
2023-12-12T08:16:04.991824image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
2.0 5
 
2.2%
21.0 5
 
2.2%
32.0 5
 
2.2%
22.0 4
 
1.7%
28.0 4
 
1.7%
26.0 4
 
1.7%
14.0 4
 
1.7%
18.0 3
 
1.3%
35.0 3
 
1.3%
29.0 3
 
1.3%
Other values (141) 187
81.7%
ValueCountFrequency (%)
0.5 1
 
0.4%
1.0 3
1.3%
2.0 5
2.2%
3.0 2
 
0.9%
4.0 2
 
0.9%
4.5 1
 
0.4%
5.0 2
 
0.9%
6.0 1
 
0.4%
7.0 3
1.3%
7.5 1
 
0.4%
ValueCountFrequency (%)
612.0 1
0.4%
485.0 1
0.4%
447.0 1
0.4%
431.0 1
0.4%
418.5 1
0.4%
408.0 1
0.4%
397.0 1
0.4%
385.0 1
0.4%
376.0 1
0.4%
373.0 1
0.4%

적상면
Real number (ℝ)

HIGH CORRELATION 

Distinct147
Distinct (%)64.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean98.406114
Minimum1
Maximum623
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size2.1 KiB
2023-12-12T08:16:05.135840image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile5
Q127
median60
Q3119
95-th percentile327.6
Maximum623
Range622
Interquartile range (IQR)92

Descriptive statistics

Standard deviation113.64339
Coefficient of variation (CV)1.1548407
Kurtosis5.2596038
Mean98.406114
Median Absolute Deviation (MAD)39
Skewness2.1815541
Sum22535
Variance12914.819
MonotonicityNot monotonic
2023-12-12T08:16:05.260223image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
27.0 5
 
2.2%
30.0 5
 
2.2%
38.0 5
 
2.2%
29.0 4
 
1.7%
26.0 4
 
1.7%
17.0 4
 
1.7%
2.0 4
 
1.7%
18.0 3
 
1.3%
80.0 3
 
1.3%
12.0 3
 
1.3%
Other values (137) 189
82.5%
ValueCountFrequency (%)
1.0 2
0.9%
1.5 1
 
0.4%
2.0 4
1.7%
3.0 1
 
0.4%
4.0 2
0.9%
5.0 3
1.3%
6.0 2
0.9%
6.5 1
 
0.4%
7.0 1
 
0.4%
8.0 3
1.3%
ValueCountFrequency (%)
623.0 1
0.4%
620.0 1
0.4%
527.0 1
0.4%
504.0 1
0.4%
461.0 1
0.4%
455.0 1
0.4%
437.0 1
0.4%
395.0 1
0.4%
381.0 1
0.4%
371.0 1
0.4%

안성면
Real number (ℝ)

HIGH CORRELATION 

Distinct146
Distinct (%)63.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean93.89083
Minimum0
Maximum595
Zeros1
Zeros (%)0.4%
Negative0
Negative (%)0.0%
Memory size2.1 KiB
2023-12-12T08:16:05.683883image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile6
Q126
median59
Q3111
95-th percentile363.2
Maximum595
Range595
Interquartile range (IQR)85

Descriptive statistics

Standard deviation108.08765
Coefficient of variation (CV)1.1512056
Kurtosis5.1469663
Mean93.89083
Median Absolute Deviation (MAD)37
Skewness2.2148196
Sum21501
Variance11682.94
MonotonicityNot monotonic
2023-12-12T08:16:05.838966image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
27.0 5
 
2.2%
22.0 5
 
2.2%
35.0 4
 
1.7%
59.0 4
 
1.7%
113.0 4
 
1.7%
26.0 4
 
1.7%
17.0 4
 
1.7%
32.0 3
 
1.3%
23.0 3
 
1.3%
81.0 3
 
1.3%
Other values (136) 190
83.0%
ValueCountFrequency (%)
0.0 1
 
0.4%
1.0 3
1.3%
2.0 2
0.9%
2.5 1
 
0.4%
4.0 2
0.9%
5.0 1
 
0.4%
5.5 1
 
0.4%
6.0 3
1.3%
7.0 2
0.9%
8.0 3
1.3%
ValueCountFrequency (%)
595.0 1
0.4%
549.0 1
0.4%
490.0 1
0.4%
471.0 1
0.4%
457.0 1
0.4%
456.0 1
0.4%
394.0 1
0.4%
385.0 1
0.4%
380.0 1
0.4%
378.0 1
0.4%

부남면
Real number (ℝ)

HIGH CORRELATION 

Distinct141
Distinct (%)61.8%
Missing1
Missing (%)0.4%
Infinite0
Infinite (%)0.0%
Mean94.635965
Minimum0
Maximum659
Zeros2
Zeros (%)0.9%
Negative0
Negative (%)0.0%
Memory size2.1 KiB
2023-12-12T08:16:05.995810image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile4
Q126.75
median58.75
Q3124.25
95-th percentile304.6
Maximum659
Range659
Interquartile range (IQR)97.5

Descriptive statistics

Standard deviation105.50886
Coefficient of variation (CV)1.1148918
Kurtosis5.3076853
Mean94.635965
Median Absolute Deviation (MAD)36.75
Skewness2.1261587
Sum21577
Variance11132.12
MonotonicityNot monotonic
2023-12-12T08:16:06.119083image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
33.0 8
 
3.5%
3.0 5
 
2.2%
83.0 4
 
1.7%
18.0 4
 
1.7%
19.0 4
 
1.7%
43.0 4
 
1.7%
22.0 4
 
1.7%
37.0 4
 
1.7%
23.0 4
 
1.7%
71.0 4
 
1.7%
Other values (131) 183
79.9%
ValueCountFrequency (%)
0.0 2
 
0.9%
1.0 3
1.3%
2.0 1
 
0.4%
3.0 5
2.2%
4.0 2
 
0.9%
5.0 3
1.3%
7.0 1
 
0.4%
8.0 1
 
0.4%
9.0 3
1.3%
10.0 1
 
0.4%
ValueCountFrequency (%)
659.0 1
0.4%
483.0 1
0.4%
478.0 1
0.4%
426.0 1
0.4%
416.0 1
0.4%
407.0 1
0.4%
393.0 1
0.4%
392.0 1
0.4%
381.0 1
0.4%
344.0 1
0.4%

데이터기준일자
Categorical

CONSTANT 

Distinct1
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size1.9 KiB
2023-03-07
229 

Length

Max length10
Median length10
Mean length10
Min length10

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2023-03-07
2nd row2023-03-07
3rd row2023-03-07
4th row2023-03-07
5th row2023-03-07

Common Values

ValueCountFrequency (%)
2023-03-07 229
100.0%

Length

2023-12-12T08:16:06.227025image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T08:16:06.301466image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2023-03-07 229
100.0%

Interactions

2023-12-12T08:16:02.766685image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:16:00.109579image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:16:00.542984image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:16:01.026102image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:16:01.580029image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:16:02.174623image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:16:02.853364image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:16:00.180968image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:16:00.607008image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:16:01.102297image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:16:01.662287image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:16:02.255265image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:16:02.943116image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:16:00.269550image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:16:00.680265image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:16:01.181020image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:16:01.750220image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:16:02.348696image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:16:03.028441image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:16:00.336166image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:16:00.769434image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:16:01.285376image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:16:01.830788image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:16:02.443612image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:16:03.172601image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:16:00.406344image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:16:00.862654image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:16:01.368037image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:16:01.940873image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:16:02.558337image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:16:03.258685image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:16:00.480540image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:16:00.939161image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:16:01.449029image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:16:02.074939image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:16:02.659015image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-12T08:16:06.353940image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
무주읍무풍면설천면적상면안성면부남면
무주읍1.0000.8460.8790.9120.8750.880
무풍면0.8461.0000.9530.8800.8760.943
설천면0.8790.9531.0000.8860.8950.968
적상면0.9120.8800.8861.0000.9730.892
안성면0.8750.8760.8950.9731.0000.889
부남면0.8800.9430.9680.8920.8891.000
2023-12-12T08:16:06.443348image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
무주읍무풍면설천면적상면안성면부남면
무주읍1.0000.8930.9480.9660.9490.968
무풍면0.8931.0000.9370.9220.9350.924
설천면0.9480.9371.0000.9520.9570.956
적상면0.9660.9220.9521.0000.9700.962
안성면0.9490.9350.9570.9701.0000.955
부남면0.9680.9240.9560.9620.9551.000

Missing values

2023-12-12T08:16:03.372920image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-12T08:16:03.501791image/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.
2023-12-12T08:16:03.668482image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
The correlation heatmap measures nullity correlation: how strongly the presence or absence of one variable affects the presence of another.

Sample

연월일무주읍무풍면설천면적상면안성면부남면데이터기준일자
02004-01-01<NA>3.02.06.06.05.02023-03-07
12004-02-01<NA>25.028.030.036.018.02023-03-07
22004-03-01<NA>15.015.019.024.019.02023-03-07
32004-04-01<NA>67.071.076.059.069.02023-03-07
42004-05-01<NA>86.0103.098.0108.087.02023-03-07
52004-06-01<NA>186.0239.0223.0193.0260.02023-03-07
62004-07-01<NA>206.0258.0230.0296.0240.02023-03-07
72004-08-01<NA>386.0408.0323.0359.0287.02023-03-07
82004-09-01<NA>175.0168.0145.0161.0137.02023-03-07
92004-10-01<NA>5.04.03.02.00.02023-03-07
연월일무주읍무풍면설천면적상면안성면부남면데이터기준일자
2192022-04-0165.560.065.065.063.072.02023-03-07
2202022-05-014.56.56.04.05.03.02023-03-07
2212022-06-01124.5123.0119.0143.0135.5139.02023-03-07
2222022-07-01134.5159.0177.5130.5133.0143.52023-03-07
2232022-08-01261.5222.0296.0286.5170.5267.52023-03-07
2242022-09-0173.0136.5114.580.074.063.02023-03-07
2252022-10-0137.548.543.554.053.541.52023-03-07
2262022-11-0165.055.067.560.562.558.02023-03-07
2272022-12-019.010.010.06.513.010.02023-03-07
2282023-01-0122.016.519.520.020.024.52023-03-07