Overview

Dataset statistics

Number of variables16
Number of observations60
Missing cells196
Missing cells (%)20.4%
Duplicate rows1
Duplicate rows (%)1.7%
Total size in memory8.4 KiB
Average record size in memory144.2 B

Variable types

Categorical2
Numeric13
DateTime1

Dataset

Description경기도 포천시 자동기상현황관측시스템에서 제공하는 수위현황 입니다.
Author경기도 포천시
URLhttps://www.data.go.kr/data/15061912/fileData.do

Alerts

데이터기준일자 has constant value ""Constant
Dataset has 1 (1.7%) duplicate rowsDuplicates
1월 is highly overall correlated with 2월 and 3 other fieldsHigh correlation
2월 is highly overall correlated with 1월 and 9 other fieldsHigh correlation
3월 is highly overall correlated with 1월 and 11 other fieldsHigh correlation
4월 is highly overall correlated with 2월 and 10 other fieldsHigh correlation
5월 is highly overall correlated with 1월 and 11 other fieldsHigh correlation
6월 is highly overall correlated with 3월 and 9 other fieldsHigh correlation
7월 is highly overall correlated with 2월 and 10 other fieldsHigh correlation
8월 is highly overall correlated with 2월 and 10 other fieldsHigh correlation
9월 is highly overall correlated with 2월 and 10 other fieldsHigh correlation
10월 is highly overall correlated with 2월 and 10 other fieldsHigh correlation
11월 is highly overall correlated with 3월 and 9 other fieldsHigh correlation
12월 is highly overall correlated with 2월 and 10 other fieldsHigh correlation
누계 is highly overall correlated with 1월 and 11 other fieldsHigh correlation
1월 has 14 (23.3%) missing valuesMissing
2월 has 14 (23.3%) missing valuesMissing
3월 has 14 (23.3%) missing valuesMissing
4월 has 14 (23.3%) missing valuesMissing
5월 has 14 (23.3%) missing valuesMissing
6월 has 14 (23.3%) missing valuesMissing
7월 has 14 (23.3%) missing valuesMissing
8월 has 14 (23.3%) missing valuesMissing
9월 has 14 (23.3%) missing valuesMissing
10월 has 14 (23.3%) missing valuesMissing
11월 has 14 (23.3%) missing valuesMissing
12월 has 14 (23.3%) missing valuesMissing
누계 has 14 (23.3%) missing valuesMissing
데이터기준일자 has 14 (23.3%) missing valuesMissing
1월 has 1 (1.7%) zerosZeros
2월 has 1 (1.7%) zerosZeros
3월 has 1 (1.7%) zerosZeros
4월 has 1 (1.7%) zerosZeros
5월 has 1 (1.7%) zerosZeros
9월 has 1 (1.7%) zerosZeros
10월 has 1 (1.7%) zerosZeros
11월 has 2 (3.3%) zerosZeros
12월 has 2 (3.3%) zerosZeros

Reproduction

Analysis started2023-12-12 17:41:41.386991
Analysis finished2023-12-12 17:41:59.909203
Duration18.52 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

연도
Categorical

Distinct6
Distinct (%)10.0%
Missing0
Missing (%)0.0%
Memory size612.0 B
<NA>
14 
2019
10 
2015
2016
2017

Length

Max length4
Median length4
Mean length4
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2015
2nd row2015
3rd row2015
4th row2015
5th row2015

Common Values

ValueCountFrequency (%)
<NA> 14
23.3%
2019 10
16.7%
2015 9
15.0%
2016 9
15.0%
2017 9
15.0%
2018 9
15.0%

Length

2023-12-13T02:41:59.970681image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T02:42:00.089167image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 14
23.3%
2019 10
16.7%
2015 9
15.0%
2016 9
15.0%
2017 9
15.0%
2018 9
15.0%

구분
Categorical

Distinct11
Distinct (%)18.3%
Missing0
Missing (%)0.0%
Memory size612.0 B
<NA>
14 
백의교
가산교
포천대교
낭유대교
Other values (6)
26 

Length

Max length6
Median length5
Mean length4.15
Min length3

Unique

Unique1 ?
Unique (%)1.7%

Sample

1st row백의교
2nd row가산교
3rd row포천대교
4th row낭유대교
5th row영중교

Common Values

ValueCountFrequency (%)
<NA> 14
23.3%
백의교 5
 
8.3%
가산교 5
 
8.3%
포천대교 5
 
8.3%
낭유대교 5
 
8.3%
영중교 5
 
8.3%
고소성(한) 5
 
8.3%
관인(한) 5
 
8.3%
은현(한) 5
 
8.3%
영중(한) 5
 
8.3%

Length

2023-12-13T02:42:00.219710image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
na 14
23.3%
백의교 5
 
8.3%
가산교 5
 
8.3%
포천대교 5
 
8.3%
낭유대교 5
 
8.3%
영중교 5
 
8.3%
고소성(한 5
 
8.3%
관인(한 5
 
8.3%
은현(한 5
 
8.3%
영중(한 5
 
8.3%

1월
Real number (ℝ)

HIGH CORRELATION  MISSING  ZEROS 

Distinct41
Distinct (%)89.1%
Missing14
Missing (%)23.3%
Infinite0
Infinite (%)0.0%
Mean0.9473913
Minimum0
Maximum3.9
Zeros1
Zeros (%)1.7%
Negative0
Negative (%)0.0%
Memory size672.0 B
2023-12-13T02:42:00.378632image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0.16
Q10.5525
median0.695
Q31.0025
95-th percentile2.755
Maximum3.9
Range3.9
Interquartile range (IQR)0.45

Descriptive statistics

Standard deviation0.81217523
Coefficient of variation (CV)0.85727537
Kurtosis4.6771424
Mean0.9473913
Median Absolute Deviation (MAD)0.235
Skewness2.1564647
Sum43.58
Variance0.6596286
MonotonicityNot monotonic
2023-12-13T02:42:00.536200image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=41)
ValueCountFrequency (%)
0.66 3
 
5.0%
0.63 2
 
3.3%
1.01 2
 
3.3%
0.86 2
 
3.3%
0.65 1
 
1.7%
0.55 1
 
1.7%
3.9 1
 
1.7%
0.8 1
 
1.7%
0.0 1
 
1.7%
0.37 1
 
1.7%
Other values (31) 31
51.7%
(Missing) 14
23.3%
ValueCountFrequency (%)
0.0 1
1.7%
0.09 1
1.7%
0.14 1
1.7%
0.22 1
1.7%
0.31 1
1.7%
0.33 1
1.7%
0.37 1
1.7%
0.4 1
1.7%
0.49 1
1.7%
0.52 1
1.7%
ValueCountFrequency (%)
3.9 1
1.7%
3.32 1
1.7%
2.77 1
1.7%
2.71 1
1.7%
2.34 1
1.7%
1.58 1
1.7%
1.37 1
1.7%
1.22 1
1.7%
1.1 1
1.7%
1.03 1
1.7%

2월
Real number (ℝ)

HIGH CORRELATION  MISSING  ZEROS 

Distinct32
Distinct (%)69.6%
Missing14
Missing (%)23.3%
Infinite0
Infinite (%)0.0%
Mean0.86891304
Minimum0
Maximum7.76
Zeros1
Zeros (%)1.7%
Negative0
Negative (%)0.0%
Memory size672.0 B
2023-12-13T02:42:00.696978image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0.1025
Q10.52
median0.64
Q30.94
95-th percentile1.57
Maximum7.76
Range7.76
Interquartile range (IQR)0.42

Descriptive statistics

Standard deviation1.1105899
Coefficient of variation (CV)1.278137
Kurtosis34.509541
Mean0.86891304
Median Absolute Deviation (MAD)0.22
Skewness5.541664
Sum39.97
Variance1.2334099
MonotonicityNot monotonic
2023-12-13T02:42:00.865207image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=32)
ValueCountFrequency (%)
0.63 4
 
6.7%
0.52 2
 
3.3%
0.64 2
 
3.3%
0.68 2
 
3.3%
1.13 2
 
3.3%
0.37 2
 
3.3%
0.1 2
 
3.3%
1.09 2
 
3.3%
1.57 2
 
3.3%
0.58 2
 
3.3%
Other values (22) 24
40.0%
(Missing) 14
23.3%
ValueCountFrequency (%)
0.0 1
1.7%
0.1 2
3.3%
0.11 1
1.7%
0.31 1
1.7%
0.37 2
3.3%
0.4 1
1.7%
0.41 1
1.7%
0.48 1
1.7%
0.51 1
1.7%
0.52 2
3.3%
ValueCountFrequency (%)
7.76 1
1.7%
2.09 1
1.7%
1.57 2
3.3%
1.13 2
3.3%
1.09 2
3.3%
1.03 1
1.7%
1.0 1
1.7%
0.97 1
1.7%
0.95 1
1.7%
0.91 1
1.7%

3월
Real number (ℝ)

HIGH CORRELATION  MISSING  ZEROS 

Distinct35
Distinct (%)76.1%
Missing14
Missing (%)23.3%
Infinite0
Infinite (%)0.0%
Mean0.90565217
Minimum0
Maximum6.82
Zeros1
Zeros (%)1.7%
Negative0
Negative (%)0.0%
Memory size672.0 B
2023-12-13T02:42:01.009658image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0.09
Q10.4825
median0.665
Q30.89
95-th percentile2.825
Maximum6.82
Range6.82
Interquartile range (IQR)0.4075

Descriptive statistics

Standard deviation1.0914428
Coefficient of variation (CV)1.2051457
Kurtosis19.860627
Mean0.90565217
Median Absolute Deviation (MAD)0.225
Skewness4.1018387
Sum41.66
Variance1.1912473
MonotonicityNot monotonic
2023-12-13T02:42:01.195849image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=35)
ValueCountFrequency (%)
0.69 3
 
5.0%
0.52 2
 
3.3%
0.54 2
 
3.3%
0.4 2
 
3.3%
0.64 2
 
3.3%
1.23 2
 
3.3%
0.09 2
 
3.3%
0.62 2
 
3.3%
0.84 2
 
3.3%
0.89 2
 
3.3%
Other values (25) 25
41.7%
(Missing) 14
23.3%
ValueCountFrequency (%)
0.0 1
1.7%
0.07 1
1.7%
0.09 2
3.3%
0.24 1
1.7%
0.27 1
1.7%
0.35 1
1.7%
0.37 1
1.7%
0.4 2
3.3%
0.41 1
1.7%
0.47 1
1.7%
ValueCountFrequency (%)
6.82 1
1.7%
3.3 1
1.7%
3.24 1
1.7%
1.58 1
1.7%
1.23 2
3.3%
1.2 1
1.7%
1.08 1
1.7%
1.03 1
1.7%
0.98 1
1.7%
0.97 1
1.7%

4월
Real number (ℝ)

HIGH CORRELATION  MISSING  ZEROS 

Distinct36
Distinct (%)78.3%
Missing14
Missing (%)23.3%
Infinite0
Infinite (%)0.0%
Mean0.75130435
Minimum0
Maximum3.22
Zeros1
Zeros (%)1.7%
Negative0
Negative (%)0.0%
Memory size672.0 B
2023-12-13T02:42:01.357825image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0.07
Q10.505
median0.695
Q30.99
95-th percentile1.305
Maximum3.22
Range3.22
Interquartile range (IQR)0.485

Descriptive statistics

Standard deviation0.524407
Coefficient of variation (CV)0.69799543
Kurtosis10.000925
Mean0.75130435
Median Absolute Deviation (MAD)0.295
Skewness2.2647904
Sum34.56
Variance0.27500271
MonotonicityNot monotonic
2023-12-13T02:42:01.555187image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=36)
ValueCountFrequency (%)
0.53 2
 
3.3%
0.79 2
 
3.3%
0.99 2
 
3.3%
0.63 2
 
3.3%
0.67 2
 
3.3%
1.14 2
 
3.3%
0.06 2
 
3.3%
0.85 2
 
3.3%
0.81 2
 
3.3%
1.01 2
 
3.3%
Other values (26) 26
43.3%
(Missing) 14
23.3%
ValueCountFrequency (%)
0.0 1
1.7%
0.06 2
3.3%
0.1 1
1.7%
0.18 1
1.7%
0.19 1
1.7%
0.23 1
1.7%
0.26 1
1.7%
0.29 1
1.7%
0.33 1
1.7%
0.39 1
1.7%
ValueCountFrequency (%)
3.22 1
1.7%
1.59 1
1.7%
1.32 1
1.7%
1.26 1
1.7%
1.19 1
1.7%
1.17 1
1.7%
1.14 2
3.3%
1.06 1
1.7%
1.01 2
3.3%
0.99 2
3.3%

5월
Real number (ℝ)

HIGH CORRELATION  MISSING  ZEROS 

Distinct38
Distinct (%)82.6%
Missing14
Missing (%)23.3%
Infinite0
Infinite (%)0.0%
Mean0.74934783
Minimum0
Maximum1.6
Zeros1
Zeros (%)1.7%
Negative0
Negative (%)0.0%
Memory size672.0 B
2023-12-13T02:42:01.708264image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0.125
Q10.52
median0.71
Q30.99
95-th percentile1.4025
Maximum1.6
Range1.6
Interquartile range (IQR)0.47

Descriptive statistics

Standard deviation0.39968544
Coefficient of variation (CV)0.53337773
Kurtosis-0.50348053
Mean0.74934783
Median Absolute Deviation (MAD)0.245
Skewness0.23946531
Sum34.47
Variance0.15974845
MonotonicityNot monotonic
2023-12-13T02:42:01.890074image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=38)
ValueCountFrequency (%)
0.8 3
 
5.0%
1.27 2
 
3.3%
0.59 2
 
3.3%
0.72 2
 
3.3%
0.43 2
 
3.3%
0.52 2
 
3.3%
0.6 2
 
3.3%
1.55 1
 
1.7%
0.23 1
 
1.7%
0.58 1
 
1.7%
Other values (28) 28
46.7%
(Missing) 14
23.3%
ValueCountFrequency (%)
0.0 1
1.7%
0.06 1
1.7%
0.11 1
1.7%
0.17 1
1.7%
0.23 1
1.7%
0.26 1
1.7%
0.27 1
1.7%
0.35 1
1.7%
0.43 2
3.3%
0.47 1
1.7%
ValueCountFrequency (%)
1.6 1
1.7%
1.55 1
1.7%
1.42 1
1.7%
1.35 1
1.7%
1.32 1
1.7%
1.27 2
3.3%
1.26 1
1.7%
1.14 1
1.7%
1.13 1
1.7%
1.09 1
1.7%

6월
Real number (ℝ)

HIGH CORRELATION  MISSING 

Distinct39
Distinct (%)84.8%
Missing14
Missing (%)23.3%
Infinite0
Infinite (%)0.0%
Mean0.71413043
Minimum0.05
Maximum2.41
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size672.0 B
2023-12-13T02:42:02.075845image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0.05
5-th percentile0.13
Q10.49
median0.635
Q30.94
95-th percentile1.3725
Maximum2.41
Range2.36
Interquartile range (IQR)0.45

Descriptive statistics

Standard deviation0.43971999
Coefficient of variation (CV)0.61574185
Kurtosis3.7213676
Mean0.71413043
Median Absolute Deviation (MAD)0.225
Skewness1.3776223
Sum32.85
Variance0.19335367
MonotonicityNot monotonic
2023-12-13T02:42:02.250408image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=39)
ValueCountFrequency (%)
0.56 3
 
5.0%
0.61 2
 
3.3%
0.49 2
 
3.3%
1.17 2
 
3.3%
0.94 2
 
3.3%
0.64 2
 
3.3%
0.21 1
 
1.7%
0.74 1
 
1.7%
0.24 1
 
1.7%
1.43 1
 
1.7%
Other values (29) 29
48.3%
(Missing) 14
23.3%
ValueCountFrequency (%)
0.05 1
1.7%
0.09 1
1.7%
0.11 1
1.7%
0.19 1
1.7%
0.21 1
1.7%
0.24 1
1.7%
0.25 1
1.7%
0.26 1
1.7%
0.32 1
1.7%
0.37 1
1.7%
ValueCountFrequency (%)
2.41 1
1.7%
1.59 1
1.7%
1.43 1
1.7%
1.2 1
1.7%
1.18 1
1.7%
1.17 2
3.3%
1.15 1
1.7%
1.11 1
1.7%
1.02 1
1.7%
1.01 1
1.7%

7월
Real number (ℝ)

HIGH CORRELATION  MISSING 

Distinct38
Distinct (%)82.6%
Missing14
Missing (%)23.3%
Infinite0
Infinite (%)0.0%
Mean0.95608696
Minimum0.22
Maximum2.18
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size672.0 B
2023-12-13T02:42:02.415279image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0.22
5-th percentile0.24
Q10.66
median0.925
Q31.315
95-th percentile1.6825
Maximum2.18
Range1.96
Interquartile range (IQR)0.655

Descriptive statistics

Standard deviation0.45478434
Coefficient of variation (CV)0.47567257
Kurtosis-0.16100967
Mean0.95608696
Median Absolute Deviation (MAD)0.285
Skewness0.31887761
Sum43.98
Variance0.20682879
MonotonicityNot monotonic
2023-12-13T02:42:02.588787image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=38)
ValueCountFrequency (%)
1.35 3
 
5.0%
0.64 2
 
3.3%
0.23 2
 
3.3%
1.47 2
 
3.3%
1.0 2
 
3.3%
0.7 2
 
3.3%
0.92 2
 
3.3%
0.8 1
 
1.7%
1.02 1
 
1.7%
0.76 1
 
1.7%
Other values (28) 28
46.7%
(Missing) 14
23.3%
ValueCountFrequency (%)
0.22 1
1.7%
0.23 2
3.3%
0.27 1
1.7%
0.32 1
1.7%
0.34 1
1.7%
0.35 1
1.7%
0.49 1
1.7%
0.51 1
1.7%
0.64 2
3.3%
0.65 1
1.7%
ValueCountFrequency (%)
2.18 1
 
1.7%
1.71 1
 
1.7%
1.7 1
 
1.7%
1.63 1
 
1.7%
1.53 1
 
1.7%
1.47 2
3.3%
1.44 1
 
1.7%
1.35 3
5.0%
1.33 1
 
1.7%
1.27 1
 
1.7%

8월
Real number (ℝ)

HIGH CORRELATION  MISSING 

Distinct37
Distinct (%)80.4%
Missing14
Missing (%)23.3%
Infinite0
Infinite (%)0.0%
Mean0.94
Minimum0.02
Maximum2.11
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size672.0 B
2023-12-13T02:42:02.772484image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0.02
5-th percentile0.25
Q10.72
median0.88
Q31.28
95-th percentile1.6775
Maximum2.11
Range2.09
Interquartile range (IQR)0.56

Descriptive statistics

Standard deviation0.46367613
Coefficient of variation (CV)0.49327248
Kurtosis-0.2057808
Mean0.94
Median Absolute Deviation (MAD)0.315
Skewness0.23815808
Sum43.24
Variance0.21499556
MonotonicityNot monotonic
2023-12-13T02:42:02.945880image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=37)
ValueCountFrequency (%)
0.84 3
 
5.0%
0.76 3
 
5.0%
0.25 2
 
3.3%
1.04 2
 
3.3%
0.3 2
 
3.3%
1.28 2
 
3.3%
0.77 2
 
3.3%
1.0 1
 
1.7%
0.99 1
 
1.7%
1.68 1
 
1.7%
Other values (27) 27
45.0%
(Missing) 14
23.3%
ValueCountFrequency (%)
0.02 1
1.7%
0.19 1
1.7%
0.25 2
3.3%
0.3 2
3.3%
0.4 1
1.7%
0.45 1
1.7%
0.46 1
1.7%
0.53 1
1.7%
0.69 1
1.7%
0.71 1
1.7%
ValueCountFrequency (%)
2.11 1
1.7%
1.71 1
1.7%
1.68 1
1.7%
1.67 1
1.7%
1.66 1
1.7%
1.51 1
1.7%
1.5 1
1.7%
1.39 1
1.7%
1.32 1
1.7%
1.31 1
1.7%

9월
Real number (ℝ)

HIGH CORRELATION  MISSING  ZEROS 

Distinct38
Distinct (%)82.6%
Missing14
Missing (%)23.3%
Infinite0
Infinite (%)0.0%
Mean0.8173913
Minimum0
Maximum3.13
Zeros1
Zeros (%)1.7%
Negative0
Negative (%)0.0%
Memory size672.0 B
2023-12-13T02:42:03.094030image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0.0625
Q10.525
median0.74
Q31.1075
95-th percentile1.6025
Maximum3.13
Range3.13
Interquartile range (IQR)0.5825

Descriptive statistics

Standard deviation0.54182996
Coefficient of variation (CV)0.66287708
Kurtosis6.218627
Mean0.8173913
Median Absolute Deviation (MAD)0.275
Skewness1.6726349
Sum37.6
Variance0.29357971
MonotonicityNot monotonic
2023-12-13T02:42:03.254197image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=38)
ValueCountFrequency (%)
1.22 3
 
5.0%
0.92 2
 
3.3%
0.56 2
 
3.3%
0.52 2
 
3.3%
0.99 2
 
3.3%
0.72 2
 
3.3%
1.23 2
 
3.3%
1.66 1
 
1.7%
0.75 1
 
1.7%
0.59 1
 
1.7%
Other values (28) 28
46.7%
(Missing) 14
23.3%
ValueCountFrequency (%)
0.0 1
1.7%
0.01 1
1.7%
0.05 1
1.7%
0.1 1
1.7%
0.16 1
1.7%
0.19 1
1.7%
0.33 1
1.7%
0.39 1
1.7%
0.4 1
1.7%
0.41 1
1.7%
ValueCountFrequency (%)
3.13 1
 
1.7%
1.67 1
 
1.7%
1.66 1
 
1.7%
1.43 1
 
1.7%
1.27 1
 
1.7%
1.23 2
3.3%
1.22 3
5.0%
1.21 1
 
1.7%
1.13 1
 
1.7%
1.04 1
 
1.7%

10월
Real number (ℝ)

HIGH CORRELATION  MISSING  ZEROS 

Distinct38
Distinct (%)82.6%
Missing14
Missing (%)23.3%
Infinite0
Infinite (%)0.0%
Mean0.75934783
Minimum0
Maximum4.06
Zeros1
Zeros (%)1.7%
Negative0
Negative (%)0.0%
Memory size672.0 B
2023-12-13T02:42:03.402752image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0.0725
Q10.415
median0.68
Q30.9875
95-th percentile1.455
Maximum4.06
Range4.06
Interquartile range (IQR)0.5725

Descriptive statistics

Standard deviation0.63398704
Coefficient of variation (CV)0.83490993
Kurtosis15.886826
Mean0.75934783
Median Absolute Deviation (MAD)0.285
Skewness3.1943963
Sum34.93
Variance0.40193957
MonotonicityNot monotonic
2023-12-13T02:42:03.557543image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=38)
ValueCountFrequency (%)
0.68 3
 
5.0%
0.74 3
 
5.0%
0.63 2
 
3.3%
0.16 2
 
3.3%
1.03 2
 
3.3%
0.7 2
 
3.3%
0.64 1
 
1.7%
1.05 1
 
1.7%
1.0 1
 
1.7%
0.38 1
 
1.7%
Other values (28) 28
46.7%
(Missing) 14
23.3%
ValueCountFrequency (%)
0.0 1
1.7%
0.03 1
1.7%
0.06 1
1.7%
0.11 1
1.7%
0.13 1
1.7%
0.16 2
3.3%
0.25 1
1.7%
0.27 1
1.7%
0.38 1
1.7%
0.39 1
1.7%
ValueCountFrequency (%)
4.06 1
1.7%
1.64 1
1.7%
1.49 1
1.7%
1.35 1
1.7%
1.22 1
1.7%
1.21 1
1.7%
1.2 1
1.7%
1.08 1
1.7%
1.05 1
1.7%
1.03 2
3.3%

11월
Real number (ℝ)

HIGH CORRELATION  MISSING  ZEROS 

Distinct36
Distinct (%)78.3%
Missing14
Missing (%)23.3%
Infinite0
Infinite (%)0.0%
Mean0.76543478
Minimum0
Maximum4.36
Zeros2
Zeros (%)3.3%
Negative0
Negative (%)0.0%
Memory size672.0 B
2023-12-13T02:42:03.698772image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0.055
Q10.4125
median0.69
Q31.005
95-th percentile1.2275
Maximum4.36
Range4.36
Interquartile range (IQR)0.5925

Descriptive statistics

Standard deviation0.6613478
Coefficient of variation (CV)0.86401588
Kurtosis19.295038
Mean0.76543478
Median Absolute Deviation (MAD)0.305
Skewness3.6168526
Sum35.21
Variance0.43738092
MonotonicityNot monotonic
2023-12-13T02:42:03.863259image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=36)
ValueCountFrequency (%)
0.69 3
 
5.0%
0.38 2
 
3.3%
0.0 2
 
3.3%
0.91 2
 
3.3%
0.73 2
 
3.3%
0.6 2
 
3.3%
0.67 2
 
3.3%
1.01 2
 
3.3%
0.14 2
 
3.3%
0.77 1
 
1.7%
Other values (26) 26
43.3%
(Missing) 14
23.3%
ValueCountFrequency (%)
0.0 2
3.3%
0.03 1
1.7%
0.13 1
1.7%
0.14 2
3.3%
0.2 1
1.7%
0.27 1
1.7%
0.28 1
1.7%
0.38 2
3.3%
0.4 1
1.7%
0.45 1
1.7%
ValueCountFrequency (%)
4.36 1
1.7%
1.65 1
1.7%
1.23 1
1.7%
1.22 1
1.7%
1.21 1
1.7%
1.2 1
1.7%
1.19 1
1.7%
1.14 1
1.7%
1.07 1
1.7%
1.03 1
1.7%

12월
Real number (ℝ)

HIGH CORRELATION  MISSING  ZEROS 

Distinct35
Distinct (%)76.1%
Missing14
Missing (%)23.3%
Infinite0
Infinite (%)0.0%
Mean0.68456522
Minimum0
Maximum1.62
Zeros2
Zeros (%)3.3%
Negative0
Negative (%)0.0%
Memory size672.0 B
2023-12-13T02:42:04.032070image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0.1125
Q10.5125
median0.68
Q30.945
95-th percentile1.1675
Maximum1.62
Range1.62
Interquartile range (IQR)0.4325

Descriptive statistics

Standard deviation0.35551969
Coefficient of variation (CV)0.51933648
Kurtosis-0.057285174
Mean0.68456522
Median Absolute Deviation (MAD)0.25
Skewness0.028845873
Sum31.49
Variance0.12639425
MonotonicityNot monotonic
2023-12-13T02:42:04.206630image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=35)
ValueCountFrequency (%)
0.69 3
 
5.0%
0.93 2
 
3.3%
0.17 2
 
3.3%
0.68 2
 
3.3%
0.65 2
 
3.3%
0.37 2
 
3.3%
0.52 2
 
3.3%
1.05 2
 
3.3%
0.0 2
 
3.3%
0.72 2
 
3.3%
Other values (25) 25
41.7%
(Missing) 14
23.3%
ValueCountFrequency (%)
0.0 2
3.3%
0.11 1
1.7%
0.12 1
1.7%
0.17 2
3.3%
0.22 1
1.7%
0.29 1
1.7%
0.37 2
3.3%
0.44 1
1.7%
0.51 1
1.7%
0.52 2
3.3%
ValueCountFrequency (%)
1.62 1
1.7%
1.22 1
1.7%
1.17 1
1.7%
1.16 1
1.7%
1.13 1
1.7%
1.06 1
1.7%
1.05 2
3.3%
1.03 1
1.7%
1.0 1
1.7%
0.99 1
1.7%

누계
Real number (ℝ)

HIGH CORRELATION  MISSING 

Distinct40
Distinct (%)87.0%
Missing14
Missing (%)23.3%
Infinite0
Infinite (%)0.0%
Mean0.83521739
Minimum0.11
Maximum1.94
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size672.0 B
2023-12-13T02:42:04.662499image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0.11
5-th percentile0.3175
Q10.6425
median0.73
Q31.08
95-th percentile1.3825
Maximum1.94
Range1.83
Interquartile range (IQR)0.4375

Descriptive statistics

Standard deviation0.37094318
Coefficient of variation (CV)0.4441277
Kurtosis0.5397809
Mean0.83521739
Median Absolute Deviation (MAD)0.26
Skewness0.52807986
Sum38.42
Variance0.13759884
MonotonicityNot monotonic
2023-12-13T02:42:04.797030image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=40)
ValueCountFrequency (%)
0.73 3
 
5.0%
0.67 2
 
3.3%
0.68 2
 
3.3%
0.71 2
 
3.3%
1.04 2
 
3.3%
0.46 1
 
1.7%
0.52 1
 
1.7%
1.94 1
 
1.7%
1.36 1
 
1.7%
0.64 1
 
1.7%
Other values (30) 30
50.0%
(Missing) 14
23.3%
ValueCountFrequency (%)
0.11 1
1.7%
0.16 1
1.7%
0.3 1
1.7%
0.37 1
1.7%
0.41 1
1.7%
0.44 1
1.7%
0.46 1
1.7%
0.48 1
1.7%
0.51 1
1.7%
0.52 1
1.7%
ValueCountFrequency (%)
1.94 1
1.7%
1.52 1
1.7%
1.39 1
1.7%
1.36 1
1.7%
1.29 1
1.7%
1.27 1
1.7%
1.24 1
1.7%
1.22 1
1.7%
1.2 1
1.7%
1.19 1
1.7%

데이터기준일자
Date

CONSTANT  MISSING 

Distinct1
Distinct (%)2.2%
Missing14
Missing (%)23.3%
Memory size612.0 B
Minimum2020-06-30 00:00:00
Maximum2020-06-30 00:00:00
2023-12-13T02:42:04.918802image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T02:42:05.023656image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=1)

Interactions

2023-12-13T02:41:57.820787image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T02:41:41.893915image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T02:41:43.305146image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T02:41:44.475535image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T02:41:45.943585image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T02:41:47.166547image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T02:41:48.873004image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T02:41:50.172974image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T02:41:51.392775image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T02:41:52.488550image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T02:41:54.082647image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T02:41:55.436688image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T02:41:56.579090image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T02:41:57.925985image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T02:41:41.979947image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T02:41:43.400028image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T02:41:44.571519image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T02:41:46.035729image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T02:41:47.283826image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T02:41:49.015691image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T02:41:50.296998image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T02:41:51.483082image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T02:41:52.579799image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T02:41:54.202691image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T02:41:55.549473image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T02:41:56.676365image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T02:41:58.031801image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T02:41:42.066100image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T02:41:43.482362image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T02:41:44.745427image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T02:41:46.116215image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T02:41:47.404068image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T02:41:49.116054image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T02:41:50.421655image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T02:41:51.573407image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T02:41:52.681493image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T02:41:54.323520image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T02:41:55.629032image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T02:41:56.774665image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T02:41:58.123957image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T02:41:42.153826image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T02:41:43.573277image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T02:41:44.852546image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T02:41:46.205533image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T02:41:47.529116image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T02:41:49.203244image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T02:41:50.513573image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T02:41:51.647921image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T02:41:52.823815image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T02:41:54.417943image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T02:41:55.717515image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T02:41:56.883502image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T02:41:58.224266image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T02:41:42.244067image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T02:41:43.659665image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T02:41:44.945645image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T02:41:46.296035image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T02:41:47.641165image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T02:41:49.294834image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T02:41:50.594127image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T02:41:51.725725image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T02:41:52.913368image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T02:41:54.521494image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T02:41:55.801520image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T02:41:56.984980image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T02:41:58.342590image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T02:41:42.348397image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T02:41:43.753732image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T02:41:45.074416image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T02:41:46.395412image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T02:41:47.796765image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T02:41:49.394743image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T02:41:50.680603image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T02:41:51.802167image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T02:41:53.000428image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T02:41:54.620976image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T02:41:55.898093image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T02:41:57.084305image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T02:41:58.439189image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T02:41:42.447176image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T02:41:43.839136image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T02:41:45.166426image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T02:41:46.481723image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T02:41:47.947977image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T02:41:49.480926image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T02:41:50.764954image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T02:41:51.871999image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T02:41:53.072334image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T02:41:54.722232image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T02:41:55.972634image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T02:41:57.169935image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T02:41:58.562713image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T02:41:42.550473image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T02:41:43.937782image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T02:41:45.278077image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T02:41:46.570015image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T02:41:48.045524image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T02:41:49.577351image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T02:41:50.856389image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T02:41:51.970821image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T02:41:53.161716image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T02:41:54.814555image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T02:41:56.065141image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T02:41:57.278416image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T02:41:58.649800image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T02:41:42.882907image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T02:41:44.024454image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T02:41:45.419563image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T02:41:46.648417image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T02:41:48.119966image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T02:41:49.658169image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T02:41:50.933484image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T02:41:52.040621image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T02:41:53.239757image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T02:41:54.907802image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T02:41:56.146529image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T02:41:57.379696image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T02:41:58.732924image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T02:41:42.960100image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T02:41:44.122907image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T02:41:45.549654image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T02:41:46.767707image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T02:41:48.485090image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T02:41:49.742162image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T02:41:51.035368image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T02:41:52.127914image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T02:41:53.364738image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T02:41:55.004337image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T02:41:56.235452image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T02:41:57.476238image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T02:41:58.822238image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T02:41:43.047814image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T02:41:44.210372image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T02:41:45.672936image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T02:41:46.867291image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T02:41:48.572428image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T02:41:49.848422image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T02:41:51.126427image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T02:41:52.217809image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T02:41:53.470179image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T02:41:55.128796image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T02:41:56.322230image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T02:41:57.571196image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T02:41:58.903977image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T02:41:43.128045image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T02:41:44.296850image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T02:41:45.770067image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T02:41:46.973157image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T02:41:48.658568image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T02:41:49.927780image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T02:41:51.202228image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T02:41:52.297141image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T02:41:53.553215image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T02:41:55.218722image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T02:41:56.400728image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T02:41:57.648332image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T02:41:59.004853image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T02:41:43.217328image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T02:41:44.386750image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T02:41:45.860993image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T02:41:47.070922image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T02:41:48.767594image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T02:41:50.066674image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T02:41:51.299689image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T02:41:52.402853image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T02:41:53.644689image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T02:41:55.323230image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T02:41:56.489946image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T02:41:57.729743image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-13T02:42:05.115588image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연도구분1월2월3월4월5월6월7월8월9월10월11월12월누계
연도1.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.000
구분0.0001.0000.5040.6210.6000.6940.7910.7170.6960.7330.6710.7020.8510.7230.565
1월0.0000.5041.0000.9220.8700.7540.6780.7110.7810.6810.6060.6050.5360.8210.918
2월0.0000.6210.9221.0000.8040.7260.7700.8870.6100.7830.7130.6620.5450.7070.869
3월0.0000.6000.8700.8041.0000.7290.8640.7480.5590.8010.6800.5220.6680.6580.912
4월0.0000.6940.7540.7260.7291.0000.7940.7610.7910.8240.8010.7740.5750.6890.785
5월0.0000.7910.6780.7700.8640.7941.0000.8010.7510.7280.6190.6370.7750.6450.756
6월0.0000.7170.7110.8870.7480.7610.8011.0000.6030.5180.7560.8250.8190.7920.771
7월0.0000.6960.7810.6100.5590.7910.7510.6031.0000.8150.7100.8020.7490.8460.805
8월0.0000.7330.6810.7830.8010.8240.7280.5180.8151.0000.8460.6990.8590.6270.766
9월0.0000.6710.6060.7130.6800.8010.6190.7560.7100.8461.0000.7240.7350.7070.687
10월0.0000.7020.6050.6620.5220.7740.6370.8250.8020.6990.7241.0001.0000.9620.730
11월0.0000.8510.5360.5450.6680.5750.7750.8190.7490.8590.7351.0001.0000.9000.683
12월0.0000.7230.8210.7070.6580.6890.6450.7920.8460.6270.7070.9620.9001.0000.884
누계0.0000.5650.9180.8690.9120.7850.7560.7710.8050.7660.6870.7300.6830.8841.000
2023-12-13T02:42:05.263307image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연도구분
연도1.0000.000
구분0.0001.000
2023-12-13T02:42:05.361775image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
1월2월3월4월5월6월7월8월9월10월11월12월누계연도구분
1월1.0000.6770.6020.3930.6120.4380.4870.4240.3160.3750.3350.3810.6000.0000.232
2월0.6771.0000.8710.6890.6900.4980.5140.7040.6740.5070.4830.5310.7750.0000.387
3월0.6020.8711.0000.8120.8230.6450.6090.7640.7480.5920.5560.6100.8630.0000.265
4월0.3930.6890.8121.0000.8050.7660.6720.8720.8410.6720.6400.6870.7350.0000.430
5월0.6120.6900.8230.8051.0000.7770.6780.6760.6730.6720.6220.6520.7760.0000.357
6월0.4380.4980.6450.7660.7771.0000.6870.6530.6630.6820.6650.6850.5770.0000.431
7월0.4870.5140.6090.6720.6780.6871.0000.7330.6390.8210.7920.7210.7540.0000.374
8월0.4240.7040.7640.8720.6760.6530.7331.0000.8980.6570.6130.6980.7770.0000.298
9월0.3160.6740.7480.8410.6730.6630.6390.8981.0000.7690.7290.7400.7660.0000.400
10월0.3750.5070.5920.6720.6720.6820.8210.6570.7691.0000.9710.8590.7290.0000.438
11월0.3350.4830.5560.6400.6220.6650.7920.6130.7290.9711.0000.8700.7010.0000.480
12월0.3810.5310.6100.6870.6520.6850.7210.6980.7400.8590.8701.0000.5990.0000.425
누계0.6000.7750.8630.7350.7760.5770.7540.7770.7660.7290.7010.5991.0000.0000.287
연도0.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0001.0000.000
구분0.2320.3870.2650.4300.3570.4310.3740.2980.4000.4380.4800.4250.2870.0001.000

Missing values

2023-12-13T02:41:59.392763image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-13T02:41:59.576262image/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.
2023-12-13T02:41:59.745172image/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

연도구분1월2월3월4월5월6월7월8월9월10월11월12월누계데이터기준일자
02015백의교1.011.00.981.060.960.941.21.160.930.941.031.031.022020-06-30
12015가산교0.520.480.40.290.260.251.440.530.524.064.360.521.142020-06-30
22015포천대교0.140.110.070.10.060.050.220.190.050.060.140.170.112020-06-30
32015낭유대교0.860.840.841.011.141.111.271.31.221.21.211.061.092020-06-30
42015영중교0.630.630.720.70.520.760.870.780.560.540.690.680.672020-06-30
52015고소성(한)0.590.580.770.810.660.640.920.770.560.560.640.650.682020-06-30
62015관인(한)0.490.40.410.330.170.210.740.840.330.160.270.950.442020-06-30
72015은현(한)0.640.630.620.660.620.610.80.840.730.740.790.790.712020-06-30
82015영중(한)1.371.570.350.190.110.090.350.30.10.110.20.220.412020-06-30
92016백의교0.970.971.031.011.130.941.331.040.991.030.991.051.042020-06-30
연도구분1월2월3월4월5월6월7월8월9월10월11월12월누계데이터기준일자
50<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
51<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
52<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
53<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
54<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
55<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
56<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
57<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
58<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
59<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>

Duplicate rows

Most frequently occurring

연도구분1월2월3월4월5월6월7월8월9월10월11월12월누계데이터기준일자# duplicates
0<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>14