Overview

Dataset statistics

Number of variables14
Number of observations4010
Missing cells5689
Missing cells (%)10.1%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory489.6 KiB
Average record size in memory125.0 B

Variable types

DateTime1
Numeric13

Dataset

Description2013년 이후, 하동군의 읍면별 강우량을 일자별로 제공.
Author경상남도 하동군
URLhttps://bigdata.gyeongnam.go.kr/index.gn?menuCd=DOM_000000114002001000&publicdatapk=15112856

Alerts

하동읍 is highly overall correlated with 화개면 and 11 other fieldsHigh correlation
화개면 is highly overall correlated with 하동읍 and 11 other fieldsHigh correlation
악양면 is highly overall correlated with 하동읍 and 11 other fieldsHigh correlation
적량면 is highly overall correlated with 하동읍 and 11 other fieldsHigh correlation
횡천면 is highly overall correlated with 하동읍 and 11 other fieldsHigh correlation
고전면 is highly overall correlated with 하동읍 and 11 other fieldsHigh correlation
금남면 is highly overall correlated with 하동읍 and 11 other fieldsHigh correlation
금성면 is highly overall correlated with 하동읍 and 11 other fieldsHigh correlation
진교면 is highly overall correlated with 하동읍 and 11 other fieldsHigh correlation
양보면 is highly overall correlated with 하동읍 and 11 other fieldsHigh correlation
북천면 is highly overall correlated with 하동읍 and 11 other fieldsHigh correlation
청암면 is highly overall correlated with 하동읍 and 11 other fieldsHigh correlation
옥종면 is highly overall correlated with 하동읍 and 11 other fieldsHigh correlation
화개면 has 1287 (32.1%) missing valuesMissing
악양면 has 516 (12.9%) missing valuesMissing
적량면 has 1344 (33.5%) missing valuesMissing
횡천면 has 802 (20.0%) missing valuesMissing
금남면 has 375 (9.4%) missing valuesMissing
청암면 has 1262 (31.5%) missing valuesMissing
날짜 has unique valuesUnique
하동읍 has 3040 (75.8%) zerosZeros
화개면 has 2007 (50.0%) zerosZeros
악양면 has 2563 (63.9%) zerosZeros
적량면 has 1991 (49.7%) zerosZeros
횡천면 has 2349 (58.6%) zerosZeros
고전면 has 2977 (74.2%) zerosZeros
금남면 has 2786 (69.5%) zerosZeros
금성면 has 3020 (75.3%) zerosZeros
진교면 has 3040 (75.8%) zerosZeros
양보면 has 2946 (73.5%) zerosZeros
북천면 has 2953 (73.6%) zerosZeros
청암면 has 2043 (50.9%) zerosZeros
옥종면 has 2940 (73.3%) zerosZeros

Reproduction

Analysis started2023-12-10 22:59:00.673477
Analysis finished2023-12-10 22:59:18.965327
Duration18.29 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

날짜
Date

UNIQUE 

Distinct4010
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size31.5 KiB
Minimum2012-01-01 00:00:00
Maximum2022-12-31 00:00:00
2023-12-11T07:59:19.026826image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:59:19.150018image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

하동읍
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct119
Distinct (%)3.0%
Missing35
Missing (%)0.9%
Infinite0
Infinite (%)0.0%
Mean4.4728805
Minimum0
Maximum201
Zeros3040
Zeros (%)75.8%
Negative0
Negative (%)0.0%
Memory size35.4 KiB
2023-12-11T07:59:19.278373image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile28
Maximum201
Range201
Interquartile range (IQR)0

Descriptive statistics

Standard deviation15.683087
Coefficient of variation (CV)3.5062611
Kurtosis46.561271
Mean4.4728805
Median Absolute Deviation (MAD)0
Skewness5.9657529
Sum17779.7
Variance245.95921
MonotonicityNot monotonic
2023-12-11T07:59:19.431271image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.0 3040
75.8%
1.0 142
 
3.5%
2.0 98
 
2.4%
3.0 54
 
1.3%
4.0 53
 
1.3%
5.0 44
 
1.1%
6.0 37
 
0.9%
7.0 32
 
0.8%
10.0 25
 
0.6%
9.0 23
 
0.6%
Other values (109) 427
 
10.6%
(Missing) 35
 
0.9%
ValueCountFrequency (%)
0.0 3040
75.8%
0.5 4
 
0.1%
1.0 142
 
3.5%
1.5 3
 
0.1%
2.0 98
 
2.4%
3.0 54
 
1.3%
4.0 53
 
1.3%
5.0 44
 
1.1%
6.0 37
 
0.9%
6.5 1
 
< 0.1%
ValueCountFrequency (%)
201.0 1
< 0.1%
195.0 1
< 0.1%
193.0 1
< 0.1%
191.0 1
< 0.1%
169.0 1
< 0.1%
157.0 1
< 0.1%
150.0 1
< 0.1%
149.0 1
< 0.1%
148.0 1
< 0.1%
140.0 1
< 0.1%

화개면
Real number (ℝ)

HIGH CORRELATION  MISSING  ZEROS 

Distinct138
Distinct (%)5.1%
Missing1287
Missing (%)32.1%
Infinite0
Infinite (%)0.0%
Mean4.3296915
Minimum0
Maximum284.5
Zeros2007
Zeros (%)50.0%
Negative0
Negative (%)0.0%
Memory size35.4 KiB
2023-12-11T07:59:19.576170image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30.5
95-th percentile25.45
Maximum284.5
Range284.5
Interquartile range (IQR)0.5

Descriptive statistics

Standard deviation16.405854
Coefficient of variation (CV)3.7891507
Kurtosis89.919226
Mean4.3296915
Median Absolute Deviation (MAD)0
Skewness7.9326578
Sum11789.75
Variance269.15203
MonotonicityNot monotonic
2023-12-11T07:59:19.690604image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.0 2007
50.0%
0.5 100
 
2.5%
1.0 58
 
1.4%
1.5 40
 
1.0%
2.0 28
 
0.7%
2.5 28
 
0.7%
3.5 23
 
0.6%
4.0 20
 
0.5%
4.5 19
 
0.5%
3.0 18
 
0.4%
Other values (128) 382
 
9.5%
(Missing) 1287
32.1%
ValueCountFrequency (%)
0.0 2007
50.0%
0.5 100
 
2.5%
1.0 58
 
1.4%
1.5 40
 
1.0%
2.0 28
 
0.7%
2.5 28
 
0.7%
3.0 18
 
0.4%
3.5 23
 
0.6%
4.0 20
 
0.5%
4.5 19
 
0.5%
ValueCountFrequency (%)
284.5 1
< 0.1%
257.0 1
< 0.1%
219.0 1
< 0.1%
191.0 1
< 0.1%
179.5 1
< 0.1%
173.0 1
< 0.1%
165.5 1
< 0.1%
144.5 1
< 0.1%
132.0 1
< 0.1%
123.5 1
< 0.1%

악양면
Real number (ℝ)

HIGH CORRELATION  MISSING  ZEROS 

Distinct157
Distinct (%)4.5%
Missing516
Missing (%)12.9%
Infinite0
Infinite (%)0.0%
Mean4.7271895
Minimum0
Maximum249
Zeros2563
Zeros (%)63.9%
Negative0
Negative (%)0.0%
Memory size35.4 KiB
2023-12-11T07:59:19.822421image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30.5
95-th percentile29.175
Maximum249
Range249
Interquartile range (IQR)0.5

Descriptive statistics

Standard deviation16.950741
Coefficient of variation (CV)3.5857969
Kurtosis62.944938
Mean4.7271895
Median Absolute Deviation (MAD)0
Skewness6.7679076
Sum16516.8
Variance287.32763
MonotonicityNot monotonic
2023-12-11T07:59:19.953376image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.0 2563
63.9%
0.5 137
 
3.4%
1.0 59
 
1.5%
1.5 49
 
1.2%
2.0 43
 
1.1%
2.5 42
 
1.0%
3.0 30
 
0.7%
4.0 20
 
0.5%
3.5 20
 
0.5%
5.5 19
 
0.5%
Other values (147) 512
 
12.8%
(Missing) 516
 
12.9%
ValueCountFrequency (%)
0.0 2563
63.9%
0.5 137
 
3.4%
1.0 59
 
1.5%
1.5 49
 
1.2%
2.0 43
 
1.1%
2.5 42
 
1.0%
3.0 30
 
0.7%
3.5 20
 
0.5%
4.0 20
 
0.5%
4.5 16
 
0.4%
ValueCountFrequency (%)
249.0 1
< 0.1%
243.0 1
< 0.1%
222.5 1
< 0.1%
209.5 1
< 0.1%
202.0 1
< 0.1%
183.0 1
< 0.1%
157.0 1
< 0.1%
155.0 1
< 0.1%
148.5 1
< 0.1%
146.5 1
< 0.1%

적량면
Real number (ℝ)

HIGH CORRELATION  MISSING  ZEROS 

Distinct143
Distinct (%)5.4%
Missing1344
Missing (%)33.5%
Infinite0
Infinite (%)0.0%
Mean4.3938485
Minimum0
Maximum181
Zeros1991
Zeros (%)49.7%
Negative0
Negative (%)0.0%
Memory size35.4 KiB
2023-12-11T07:59:20.085378image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30.5
95-th percentile27.875
Maximum181
Range181
Interquartile range (IQR)0.5

Descriptive statistics

Standard deviation15.317557
Coefficient of variation (CV)3.4861369
Kurtosis40.331559
Mean4.3938485
Median Absolute Deviation (MAD)0
Skewness5.6470582
Sum11714
Variance234.62756
MonotonicityNot monotonic
2023-12-11T07:59:20.243782image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.0 1991
49.7%
0.5 101
 
2.5%
1.0 52
 
1.3%
1.5 36
 
0.9%
2.0 34
 
0.8%
3.0 23
 
0.6%
4.0 20
 
0.5%
4.5 17
 
0.4%
5.0 16
 
0.4%
6.5 15
 
0.4%
Other values (133) 361
 
9.0%
(Missing) 1344
33.5%
ValueCountFrequency (%)
0.0 1991
49.7%
0.5 101
 
2.5%
1.0 52
 
1.3%
1.5 36
 
0.9%
2.0 34
 
0.8%
2.5 11
 
0.3%
3.0 23
 
0.6%
3.5 14
 
0.3%
4.0 20
 
0.5%
4.5 17
 
0.4%
ValueCountFrequency (%)
181.0 1
< 0.1%
160.0 1
< 0.1%
157.5 1
< 0.1%
157.0 1
< 0.1%
154.0 1
< 0.1%
151.0 1
< 0.1%
146.5 1
< 0.1%
138.5 1
< 0.1%
120.5 1
< 0.1%
115.0 1
< 0.1%

횡천면
Real number (ℝ)

HIGH CORRELATION  MISSING  ZEROS 

Distinct159
Distinct (%)5.0%
Missing802
Missing (%)20.0%
Infinite0
Infinite (%)0.0%
Mean4.6502494
Minimum0
Maximum203.5
Zeros2349
Zeros (%)58.6%
Negative0
Negative (%)0.0%
Memory size35.4 KiB
2023-12-11T07:59:20.737313image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30.5
95-th percentile28.5
Maximum203.5
Range203.5
Interquartile range (IQR)0.5

Descriptive statistics

Standard deviation16.380851
Coefficient of variation (CV)3.5225747
Kurtosis47.179049
Mean4.6502494
Median Absolute Deviation (MAD)0
Skewness6.0606121
Sum14918
Variance268.33227
MonotonicityNot monotonic
2023-12-11T07:59:20.887681image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.0 2349
58.6%
0.5 135
 
3.4%
1.0 60
 
1.5%
1.5 43
 
1.1%
2.0 39
 
1.0%
2.5 28
 
0.7%
3.5 24
 
0.6%
3.0 22
 
0.5%
4.0 21
 
0.5%
6.5 17
 
0.4%
Other values (149) 470
 
11.7%
(Missing) 802
 
20.0%
ValueCountFrequency (%)
0.0 2349
58.6%
0.5 135
 
3.4%
1.0 60
 
1.5%
1.5 43
 
1.1%
2.0 39
 
1.0%
2.5 28
 
0.7%
3.0 22
 
0.5%
3.5 24
 
0.6%
4.0 21
 
0.5%
4.5 14
 
0.3%
ValueCountFrequency (%)
203.5 1
< 0.1%
192.0 1
< 0.1%
187.0 1
< 0.1%
184.0 1
< 0.1%
178.0 1
< 0.1%
170.5 1
< 0.1%
169.0 1
< 0.1%
149.0 1
< 0.1%
140.0 1
< 0.1%
136.5 1
< 0.1%

고전면
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct183
Distinct (%)4.6%
Missing14
Missing (%)0.3%
Infinite0
Infinite (%)0.0%
Mean4.8762513
Minimum0
Maximum275
Zeros2977
Zeros (%)74.2%
Negative0
Negative (%)0.0%
Memory size35.4 KiB
2023-12-11T07:59:21.008920image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30.5
95-th percentile30.625
Maximum275
Range275
Interquartile range (IQR)0.5

Descriptive statistics

Standard deviation17.326949
Coefficient of variation (CV)3.553334
Kurtosis56.904637
Mean4.8762513
Median Absolute Deviation (MAD)0
Skewness6.3793527
Sum19485.5
Variance300.22317
MonotonicityNot monotonic
2023-12-11T07:59:21.137401image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.0 2977
74.2%
0.5 142
 
3.5%
1.0 61
 
1.5%
1.5 45
 
1.1%
2.0 45
 
1.1%
2.5 31
 
0.8%
3.0 30
 
0.7%
5.0 29
 
0.7%
3.5 27
 
0.7%
6.0 23
 
0.6%
Other values (173) 586
 
14.6%
ValueCountFrequency (%)
0.0 2977
74.2%
0.5 142
 
3.5%
1.0 61
 
1.5%
1.5 45
 
1.1%
2.0 45
 
1.1%
2.5 31
 
0.8%
3.0 30
 
0.7%
3.5 27
 
0.7%
4.0 21
 
0.5%
4.5 21
 
0.5%
ValueCountFrequency (%)
275.0 1
< 0.1%
255.0 1
< 0.1%
216.5 1
< 0.1%
205.5 1
< 0.1%
177.0 1
< 0.1%
165.0 1
< 0.1%
164.5 1
< 0.1%
152.5 1
< 0.1%
147.5 1
< 0.1%
146.0 1
< 0.1%

금남면
Real number (ℝ)

HIGH CORRELATION  MISSING  ZEROS 

Distinct153
Distinct (%)4.2%
Missing375
Missing (%)9.4%
Infinite0
Infinite (%)0.0%
Mean4.1295736
Minimum0
Maximum244.5
Zeros2786
Zeros (%)69.5%
Negative0
Negative (%)0.0%
Memory size35.4 KiB
2023-12-11T07:59:21.284486image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile25.15
Maximum244.5
Range244.5
Interquartile range (IQR)0

Descriptive statistics

Standard deviation15.598842
Coefficient of variation (CV)3.7773494
Kurtosis66.360539
Mean4.1295736
Median Absolute Deviation (MAD)0
Skewness6.9887617
Sum15011
Variance243.32388
MonotonicityNot monotonic
2023-12-11T07:59:21.427622image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.0 2786
69.5%
0.5 115
 
2.9%
1.0 49
 
1.2%
2.5 47
 
1.2%
1.5 39
 
1.0%
2.0 32
 
0.8%
3.0 29
 
0.7%
3.5 22
 
0.5%
5.0 22
 
0.5%
4.5 20
 
0.5%
Other values (143) 474
 
11.8%
(Missing) 375
 
9.4%
ValueCountFrequency (%)
0.0 2786
69.5%
0.5 115
 
2.9%
1.0 49
 
1.2%
1.5 39
 
1.0%
2.0 32
 
0.8%
2.5 47
 
1.2%
3.0 29
 
0.7%
3.5 22
 
0.5%
4.0 17
 
0.4%
4.5 20
 
0.5%
ValueCountFrequency (%)
244.5 1
< 0.1%
228.5 1
< 0.1%
212.5 1
< 0.1%
173.5 1
< 0.1%
169.0 1
< 0.1%
160.0 1
< 0.1%
155.5 1
< 0.1%
142.5 1
< 0.1%
139.0 1
< 0.1%
135.0 1
< 0.1%

금성면
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct149
Distinct (%)3.7%
Missing7
Missing (%)0.2%
Infinite0
Infinite (%)0.0%
Mean3.9502873
Minimum0
Maximum225
Zeros3020
Zeros (%)75.3%
Negative0
Negative (%)0.0%
Memory size35.4 KiB
2023-12-11T07:59:21.551560image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile24
Maximum225
Range225
Interquartile range (IQR)0

Descriptive statistics

Standard deviation14.569416
Coefficient of variation (CV)3.6881916
Kurtosis62.429086
Mean3.9502873
Median Absolute Deviation (MAD)0
Skewness6.7788052
Sum15813
Variance212.26789
MonotonicityNot monotonic
2023-12-11T07:59:21.678220image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.0 3020
75.3%
0.5 139
 
3.5%
1.0 80
 
2.0%
2.5 42
 
1.0%
1.5 41
 
1.0%
2.0 41
 
1.0%
3.0 28
 
0.7%
4.5 27
 
0.7%
5.0 26
 
0.6%
3.5 25
 
0.6%
Other values (139) 534
 
13.3%
ValueCountFrequency (%)
0.0 3020
75.3%
0.5 139
 
3.5%
1.0 80
 
2.0%
1.5 41
 
1.0%
2.0 41
 
1.0%
2.5 42
 
1.0%
3.0 28
 
0.7%
3.5 25
 
0.6%
4.0 20
 
0.5%
4.5 27
 
0.7%
ValueCountFrequency (%)
225.0 1
< 0.1%
207.0 1
< 0.1%
193.0 1
< 0.1%
180.0 1
< 0.1%
162.5 1
< 0.1%
153.5 1
< 0.1%
150.0 1
< 0.1%
147.5 1
< 0.1%
145.0 1
< 0.1%
137.0 1
< 0.1%

진교면
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct169
Distinct (%)4.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean4.4157107
Minimum0
Maximum233
Zeros3040
Zeros (%)75.8%
Negative0
Negative (%)0.0%
Memory size35.4 KiB
2023-12-11T07:59:21.795919image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile28
Maximum233
Range233
Interquartile range (IQR)0

Descriptive statistics

Standard deviation15.883831
Coefficient of variation (CV)3.5971176
Kurtosis49.382213
Mean4.4157107
Median Absolute Deviation (MAD)0
Skewness6.0932952
Sum17707
Variance252.29609
MonotonicityNot monotonic
2023-12-11T07:59:21.926723image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.0 3040
75.8%
0.5 135
 
3.4%
1.0 61
 
1.5%
2.0 50
 
1.2%
1.5 38
 
0.9%
2.5 32
 
0.8%
3.0 31
 
0.8%
3.5 28
 
0.7%
6.0 23
 
0.6%
4.5 23
 
0.6%
Other values (159) 549
 
13.7%
ValueCountFrequency (%)
0.0 3040
75.8%
0.5 135
 
3.4%
1.0 61
 
1.5%
1.5 38
 
0.9%
2.0 50
 
1.2%
2.5 32
 
0.8%
3.0 31
 
0.8%
3.5 28
 
0.7%
4.0 20
 
0.5%
4.5 23
 
0.6%
ValueCountFrequency (%)
233.0 1
< 0.1%
217.5 1
< 0.1%
187.0 1
< 0.1%
179.5 1
< 0.1%
155.0 1
< 0.1%
151.0 1
< 0.1%
148.5 1
< 0.1%
145.5 1
< 0.1%
134.0 1
< 0.1%
131.5 1
< 0.1%

양보면
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct172
Distinct (%)4.3%
Missing31
Missing (%)0.8%
Infinite0
Infinite (%)0.0%
Mean4.6540588
Minimum0
Maximum236
Zeros2946
Zeros (%)73.5%
Negative0
Negative (%)0.0%
Memory size35.4 KiB
2023-12-11T07:59:22.066535image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30.5
95-th percentile30
Maximum236
Range236
Interquartile range (IQR)0.5

Descriptive statistics

Standard deviation16.613649
Coefficient of variation (CV)3.5697119
Kurtosis50.29897
Mean4.6540588
Median Absolute Deviation (MAD)0
Skewness6.1612284
Sum18518.5
Variance276.01334
MonotonicityNot monotonic
2023-12-11T07:59:22.208689image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.0 2946
73.5%
0.5 165
 
4.1%
1.0 62
 
1.5%
2.0 56
 
1.4%
1.5 55
 
1.4%
3.0 30
 
0.7%
4.0 28
 
0.7%
5.0 26
 
0.6%
2.5 24
 
0.6%
4.5 22
 
0.5%
Other values (162) 565
 
14.1%
(Missing) 31
 
0.8%
ValueCountFrequency (%)
0.0 2946
73.5%
0.5 165
 
4.1%
1.0 62
 
1.5%
1.5 55
 
1.4%
2.0 56
 
1.4%
2.5 24
 
0.6%
3.0 30
 
0.7%
3.5 22
 
0.5%
4.0 28
 
0.7%
4.5 22
 
0.5%
ValueCountFrequency (%)
236.0 1
< 0.1%
225.5 1
< 0.1%
203.5 1
< 0.1%
186.0 1
< 0.1%
175.5 1
< 0.1%
165.0 1
< 0.1%
158.5 1
< 0.1%
153.5 1
< 0.1%
142.0 2
< 0.1%
140.5 1
< 0.1%

북천면
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct174
Distinct (%)4.3%
Missing9
Missing (%)0.2%
Infinite0
Infinite (%)0.0%
Mean4.6892027
Minimum0
Maximum285.5
Zeros2953
Zeros (%)73.6%
Negative0
Negative (%)0.0%
Memory size35.4 KiB
2023-12-11T07:59:22.350027image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30.5
95-th percentile29
Maximum285.5
Range285.5
Interquartile range (IQR)0.5

Descriptive statistics

Standard deviation16.70661
Coefficient of variation (CV)3.5627827
Kurtosis62.23609
Mean4.6892027
Median Absolute Deviation (MAD)0
Skewness6.5703202
Sum18761.5
Variance279.11082
MonotonicityNot monotonic
2023-12-11T07:59:22.466263image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.0 2953
73.6%
0.5 169
 
4.2%
1.0 69
 
1.7%
1.5 44
 
1.1%
2.0 39
 
1.0%
2.5 38
 
0.9%
3.5 37
 
0.9%
3.0 27
 
0.7%
4.5 25
 
0.6%
4.0 21
 
0.5%
Other values (164) 579
 
14.4%
ValueCountFrequency (%)
0.0 2953
73.6%
0.5 169
 
4.2%
1.0 69
 
1.7%
1.5 44
 
1.1%
2.0 39
 
1.0%
2.5 38
 
0.9%
3.0 27
 
0.7%
3.5 37
 
0.9%
4.0 21
 
0.5%
4.5 25
 
0.6%
ValueCountFrequency (%)
285.5 1
< 0.1%
258.5 1
< 0.1%
187.0 1
< 0.1%
185.5 1
< 0.1%
178.0 1
< 0.1%
168.5 1
< 0.1%
163.5 1
< 0.1%
145.0 1
< 0.1%
141.0 1
< 0.1%
137.5 1
< 0.1%

청암면
Real number (ℝ)

HIGH CORRELATION  MISSING  ZEROS 

Distinct144
Distinct (%)5.2%
Missing1262
Missing (%)31.5%
Infinite0
Infinite (%)0.0%
Mean4.6052948
Minimum0
Maximum212
Zeros2043
Zeros (%)50.9%
Negative0
Negative (%)0.0%
Memory size35.4 KiB
2023-12-11T07:59:22.613151image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30.5
95-th percentile29
Maximum212
Range212
Interquartile range (IQR)0.5

Descriptive statistics

Standard deviation16.262279
Coefficient of variation (CV)3.5312134
Kurtosis48.958793
Mean4.6052948
Median Absolute Deviation (MAD)0
Skewness6.1114666
Sum12655.35
Variance264.46171
MonotonicityNot monotonic
2023-12-11T07:59:22.745417image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.0 2043
50.9%
0.5 91
 
2.3%
1.0 51
 
1.3%
1.5 39
 
1.0%
2.0 33
 
0.8%
2.5 30
 
0.7%
4.0 20
 
0.5%
3.5 17
 
0.4%
5.0 17
 
0.4%
3.0 16
 
0.4%
Other values (134) 391
 
9.8%
(Missing) 1262
31.5%
ValueCountFrequency (%)
0.0 2043
50.9%
0.5 91
 
2.3%
1.0 51
 
1.3%
1.5 39
 
1.0%
2.0 33
 
0.8%
2.5 30
 
0.7%
3.0 16
 
0.4%
3.5 17
 
0.4%
4.0 20
 
0.5%
4.5 14
 
0.3%
ValueCountFrequency (%)
212.0 1
< 0.1%
203.5 1
< 0.1%
196.5 1
< 0.1%
166.5 1
< 0.1%
158.0 1
< 0.1%
153.5 1
< 0.1%
143.5 1
< 0.1%
141.0 1
< 0.1%
131.0 1
< 0.1%
122.5 1
< 0.1%

옥종면
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct166
Distinct (%)4.1%
Missing7
Missing (%)0.2%
Infinite0
Infinite (%)0.0%
Mean4.6393955
Minimum0
Maximum268
Zeros2940
Zeros (%)73.3%
Negative0
Negative (%)0.0%
Memory size35.4 KiB
2023-12-11T07:59:22.865996image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30.5
95-th percentile28
Maximum268
Range268
Interquartile range (IQR)0.5

Descriptive statistics

Standard deviation16.720785
Coefficient of variation (CV)3.6040869
Kurtosis59.50582
Mean4.6393955
Median Absolute Deviation (MAD)0
Skewness6.5882322
Sum18571.5
Variance279.58464
MonotonicityNot monotonic
2023-12-11T07:59:23.006492image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.0 2940
73.3%
0.5 159
 
4.0%
1.0 89
 
2.2%
2.0 48
 
1.2%
1.5 47
 
1.2%
2.5 42
 
1.0%
3.0 34
 
0.8%
4.0 26
 
0.6%
3.5 25
 
0.6%
5.0 23
 
0.6%
Other values (156) 570
 
14.2%
ValueCountFrequency (%)
0.0 2940
73.3%
0.5 159
 
4.0%
1.0 89
 
2.2%
1.5 47
 
1.2%
2.0 48
 
1.2%
2.5 42
 
1.0%
3.0 34
 
0.8%
3.5 25
 
0.6%
4.0 26
 
0.6%
4.5 22
 
0.5%
ValueCountFrequency (%)
268.0 1
< 0.1%
217.5 1
< 0.1%
210.5 1
< 0.1%
207.0 1
< 0.1%
202.5 1
< 0.1%
171.0 1
< 0.1%
164.5 2
< 0.1%
156.0 1
< 0.1%
153.5 1
< 0.1%
147.0 1
< 0.1%

Interactions

2023-12-11T07:59:17.389663image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:59:02.178609image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:59:03.430495image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:59:04.976830image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:59:06.317816image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:59:07.539668image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:59:08.701316image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:59:10.088844image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:59:11.316788image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:59:12.414793image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:59:13.561669image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:59:14.758718image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:59:16.021614image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:59:17.479006image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:59:02.267609image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:59:03.540438image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:59:05.098618image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:59:06.429116image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:59:07.630889image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:59:08.792889image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:59:10.181721image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:59:11.405920image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:59:12.541165image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:59:13.674568image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:59:14.856785image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:59:16.130419image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:59:17.554523image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:59:02.353793image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:59:03.658537image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:59:05.196758image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:59:06.526593image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:59:07.718971image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:59:08.871549image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:59:10.265027image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:59:11.486550image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:59:12.624645image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:59:13.780638image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:59:14.948211image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:59:16.496854image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:59:17.632254image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:59:02.432859image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:59:03.738703image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:59:05.299902image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:59:06.635394image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:59:07.802563image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:59:08.967920image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:59:10.348355image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:59:11.580850image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:59:12.705281image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:59:13.892220image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:59:15.039326image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:59:16.572689image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:59:17.727423image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:59:02.522146image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:59:04.100786image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:59:05.383566image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:59:06.747822image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:59:07.908500image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:59:09.052397image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:59:10.438939image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:59:11.682506image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:59:12.794283image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:59:14.006137image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:59:15.145166image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:59:16.657060image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:59:17.815575image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:59:02.612021image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:59:04.198946image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:59:05.475832image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:59:06.844301image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:59:07.998436image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:59:09.139628image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:59:10.537961image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:59:11.774714image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:59:12.888788image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:59:14.100314image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:59:15.240095image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:59:16.742136image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:59:17.889664image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:59:02.695636image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:59:04.294294image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:59:05.604414image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:59:06.956695image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:59:08.085749image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:59:09.219210image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:59:10.628953image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:59:11.864784image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:59:12.968103image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:59:14.189962image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:59:15.328925image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:59:16.825528image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:59:17.971189image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:59:02.791677image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:59:04.400297image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:59:05.705898image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:59:07.040146image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:59:08.167641image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:59:09.297889image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:59:10.722292image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:59:11.948501image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:59:13.046439image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:59:14.274334image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:59:15.431870image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:59:16.901695image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:59:18.045599image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:59:02.878435image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:59:04.489228image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:59:05.809472image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:59:07.128698image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:59:08.248248image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:59:09.376748image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:59:10.806761image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:59:12.026791image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:59:13.131230image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:59:14.347636image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:59:15.516248image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:59:16.977895image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:59:18.122591image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:59:02.962821image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:59:04.570956image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:59:05.908355image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:59:07.217037image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:59:08.325686image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:59:09.448018image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:59:10.895155image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:59:12.104610image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:59:13.210045image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:59:14.428527image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:59:15.597032image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:59:17.060785image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:59:18.195878image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:59:03.071403image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:59:04.653786image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:59:06.031704image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:59:07.296716image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:59:08.414856image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:59:09.523034image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:59:11.005864image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:59:12.178381image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:59:13.295506image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:59:14.507768image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:59:15.719653image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:59:17.131021image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:59:18.269269image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:59:03.180278image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:59:04.760114image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:59:06.123595image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:59:07.377774image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:59:08.513666image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:59:09.613136image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:59:11.100221image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:59:12.263399image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:59:13.396317image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:59:14.589192image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:59:15.815052image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:59:17.208177image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:59:18.348535image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:59:03.319250image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:59:04.866615image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:59:06.210716image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:59:07.455104image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:59:08.609496image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:59:09.697957image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:59:11.184738image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:59:12.338574image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:59:13.476642image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:59:14.675363image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:59:15.912827image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:59:17.295454image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-11T07:59:23.112599image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
하동읍화개면악양면적량면횡천면고전면금남면금성면진교면양보면북천면청암면옥종면
하동읍1.0000.9150.8330.9080.9200.8560.8260.9270.9180.9480.8370.9430.919
화개면0.9151.0000.8610.8120.8270.7600.7450.8880.8170.8980.7960.9070.921
악양면0.8330.8611.0000.8940.9370.8600.9040.9280.9310.9210.8540.8860.957
적량면0.9080.8120.8941.0000.9670.8880.9270.8850.9620.8840.8610.8960.874
횡천면0.9200.8270.9370.9671.0000.8450.9030.9130.9260.9320.8820.9010.954
고전면0.8560.7600.8600.8880.8451.0000.8700.8700.9000.9060.8430.8010.832
금남면0.8260.7450.9040.9270.9030.8701.0000.9480.9390.9550.8490.7790.904
금성면0.9270.8880.9280.8850.9130.8700.9481.0000.9670.9640.8150.8920.927
진교면0.9180.8170.9310.9620.9260.9000.9390.9671.0000.9580.8510.8130.908
양보면0.9480.8980.9210.8840.9320.9060.9550.9640.9581.0000.8620.9160.949
북천면0.8370.7960.8540.8610.8820.8430.8490.8150.8510.8621.0000.8650.890
청암면0.9430.9070.8860.8960.9010.8010.7790.8920.8130.9160.8651.0000.955
옥종면0.9190.9210.9570.8740.9540.8320.9040.9270.9080.9490.8900.9551.000
2023-12-11T07:59:23.250672image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
하동읍화개면악양면적량면횡천면고전면금남면금성면진교면양보면북천면청암면옥종면
하동읍1.0000.8500.8790.9180.9080.9010.8880.8950.9000.9040.8940.8900.876
화개면0.8501.0000.9130.8630.8580.8290.8270.8210.8410.8300.8460.8800.844
악양면0.8790.9131.0000.8980.8940.8710.8550.8520.8620.8670.8780.9150.883
적량면0.9180.8630.8981.0000.9340.8970.8770.8810.8980.9010.9100.9210.905
횡천면0.9080.8580.8940.9341.0000.9060.8780.8850.9050.9100.9310.9160.901
고전면0.9010.8290.8710.8970.9061.0000.9090.9090.9270.9350.9070.8800.875
금남면0.8880.8270.8550.8770.8780.9091.0000.9270.9260.9110.8800.8710.866
금성면0.8950.8210.8520.8810.8850.9090.9271.0000.9120.9130.8820.8700.859
진교면0.9000.8410.8620.8980.9050.9270.9260.9121.0000.9250.9120.8920.887
양보면0.9040.8300.8670.9010.9100.9350.9110.9130.9251.0000.9120.8840.880
북천면0.8940.8460.8780.9100.9310.9070.8800.8820.9120.9121.0000.9080.904
청암면0.8900.8800.9150.9210.9160.8800.8710.8700.8920.8840.9081.0000.911
옥종면0.8760.8440.8830.9050.9010.8750.8660.8590.8870.8800.9040.9111.000

Missing values

2023-12-11T07:59:18.505163image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-11T07:59:18.692360image/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.
2023-12-11T07:59:18.851753image/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

날짜하동읍화개면악양면적량면횡천면고전면금남면금성면진교면양보면북천면청암면옥종면
02012-01-010.0<NA><NA><NA><NA>0.0<NA>0.00.00.00.0<NA>0.0
12012-01-020.0<NA><NA><NA><NA>0.0<NA>0.00.00.00.0<NA>0.0
22012-01-030.0<NA><NA><NA><NA>0.0<NA>0.00.00.00.0<NA>0.0
32012-01-040.0<NA><NA><NA><NA>0.0<NA>0.00.00.00.0<NA>0.0
42012-01-050.0<NA><NA><NA><NA>0.0<NA>0.00.00.00.0<NA>0.0
52012-01-060.0<NA><NA><NA><NA>0.0<NA>0.00.00.00.0<NA>0.0
62012-01-070.0<NA><NA><NA><NA>0.0<NA>0.00.00.00.0<NA>0.0
72012-01-080.0<NA><NA><NA><NA>0.0<NA>0.00.00.00.0<NA>0.0
82012-01-090.0<NA><NA><NA><NA>0.0<NA>0.00.00.00.0<NA>0.0
92012-01-100.0<NA><NA><NA><NA>0.0<NA>0.00.00.00.0<NA>0.0
날짜하동읍화개면악양면적량면횡천면고전면금남면금성면진교면양보면북천면청암면옥종면
40002022-12-220.00.00.00.00.00.00.00.00.00.00.00.00.0
40012022-12-230.00.00.00.00.00.00.00.00.00.00.00.00.0
40022022-12-240.00.00.00.00.00.00.00.00.00.00.00.00.0
40032022-12-250.00.00.00.00.00.00.00.00.00.00.00.00.0
40042022-12-260.00.00.00.00.00.00.00.00.00.00.00.00.0
40052022-12-270.00.00.00.00.00.00.00.00.00.00.00.00.0
40062022-12-280.00.00.00.00.00.00.00.00.00.00.00.00.0
40072022-12-290.00.00.00.00.00.00.00.00.00.00.00.00.0
40082022-12-300.00.00.00.00.00.00.00.00.00.00.00.00.0
40092022-12-310.00.00.00.00.00.00.00.00.00.00.00.00.0