Overview

Dataset statistics

Number of variables10
Number of observations539
Missing cells1744
Missing cells (%)32.4%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory42.8 KiB
Average record size in memory81.2 B

Variable types

Numeric1
Text7
Categorical2

Dataset

Description충청남도 지방하천코드입니다. 하천코드, 하천명, 본류, 제1지류, 제2지류, 제3지류, 제4지류, 제5지류, 제6지류, 하천등급, 수계 등의 데이터로 구성되어 있습니다.
URLhttps://www.data.go.kr/data/15121928/fileData.do

Alerts

하천코드 is highly overall correlated with 수계High correlation
수계 is highly overall correlated with 하천코드High correlation
하천등급 is highly imbalanced (89.7%)Imbalance
제1지류 has 61 (11.3%) missing valuesMissing
제2지류 has 207 (38.4%) missing valuesMissing
제3지류 has 422 (78.3%) missing valuesMissing
제4지류 has 517 (95.9%) missing valuesMissing
제5지류 has 537 (99.6%) missing valuesMissing
하천코드 has unique valuesUnique

Reproduction

Analysis started2023-12-12 20:58:45.201662
Analysis finished2023-12-12 20:58:46.518314
Duration1.32 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

하천코드
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct539
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean3067306
Minimum1120310
Maximum3421530
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size4.9 KiB
2023-12-13T05:58:46.614049image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1120310
5-th percentile3013960
Q13022745
median3024120
Q33420185
95-th percentile3421261
Maximum3421530
Range2301220
Interquartile range (IQR)397440

Descriptive statistics

Standard deviation425802.06
Coefficient of variation (CV)0.13881956
Kurtosis14.348149
Mean3067306
Median Absolute Deviation (MAD)3350
Skewness-3.5975716
Sum1.6532779 × 109
Variance1.8130739 × 1011
MonotonicityNot monotonic
2023-12-13T05:58:46.796394image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
3023930 1
 
0.2%
1120940 1
 
0.2%
3020830 1
 
0.2%
3020820 1
 
0.2%
3020810 1
 
0.2%
3020790 1
 
0.2%
3020780 1
 
0.2%
3020770 1
 
0.2%
3020760 1
 
0.2%
3020750 1
 
0.2%
Other values (529) 529
98.1%
ValueCountFrequency (%)
1120310 1
0.2%
1120320 1
0.2%
1120330 1
0.2%
1120340 1
0.2%
1120350 1
0.2%
1120360 1
0.2%
1120370 1
0.2%
1120380 1
0.2%
1120390 1
0.2%
1120400 1
0.2%
ValueCountFrequency (%)
3421530 1
0.2%
3421520 1
0.2%
3421510 1
0.2%
3421500 1
0.2%
3421490 1
0.2%
3421480 1
0.2%
3421470 1
0.2%
3421460 1
0.2%
3421450 1
0.2%
3421440 1
0.2%

하천명
Text

Distinct480
Distinct (%)89.1%
Missing0
Missing (%)0.0%
Memory size4.3 KiB
2023-12-13T05:58:47.155261image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length4
Median length3
Mean length2.9573284
Min length2

Characters and Unicode

Total characters1594
Distinct characters207
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique429 ?
Unique (%)79.6%

Sample

1st row응평천
2nd row증산천
3rd row정각천
4th row현내천
5th row오산천
ValueCountFrequency (%)
용두천 4
 
0.7%
금천 4
 
0.7%
갈산천 3
 
0.6%
구룡천 3
 
0.6%
화산천 3
 
0.6%
읍내천 3
 
0.6%
태봉천 2
 
0.4%
길산천 2
 
0.4%
마정천 2
 
0.4%
마산천 2
 
0.4%
Other values (470) 511
94.8%
2023-12-13T05:58:47.687127image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
천 559
35.1%
산 46
 
2.9%
곡 34
 
2.1%
성 28
 
1.8%
대 25
 
1.6%
암 22
 
1.4%
신 21
 
1.3%
정 20
 
1.3%
봉 18
 
1.1%
장 18
 
1.1%
Other values (197) 803
50.4%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1594
100.0%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
천 559
35.1%
산 46
 
2.9%
곡 34
 
2.1%
성 28
 
1.8%
대 25
 
1.6%
암 22
 
1.4%
신 21
 
1.3%
정 20
 
1.3%
봉 18
 
1.1%
장 18
 
1.1%
Other values (197) 803
50.4%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1594
100.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
천 559
35.1%
산 46
 
2.9%
곡 34
 
2.1%
성 28
 
1.8%
대 25
 
1.6%
암 22
 
1.4%
신 21
 
1.3%
정 20
 
1.3%
봉 18
 
1.1%
장 18
 
1.1%
Other values (197) 803
50.4%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1594
100.0%

Most frequent character per block

Hangul
ValueCountFrequency (%)
천 559
35.1%
산 46
 
2.9%
곡 34
 
2.1%
성 28
 
1.8%
대 25
 
1.6%
암 22
 
1.4%
신 21
 
1.3%
정 20
 
1.3%
봉 18
 
1.1%
장 18
 
1.1%
Other values (197) 803
50.4%

본류
Text

Distinct60
Distinct (%)11.1%
Missing0
Missing (%)0.0%
Memory size4.3 KiB
2023-12-13T05:58:48.206571image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length3
Median length2
Mean length2.4508349
Min length2

Characters and Unicode

Total characters1321
Distinct characters79
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique41 ?
Unique (%)7.6%

Sample

1st row금강
2nd row금강
3rd row금강
4th row금강
5th row금강
ValueCountFrequency (%)
금강 284
52.7%
삽교천 97
 
18.0%
안성천 21
 
3.9%
웅천천 19
 
3.5%
도당천 13
 
2.4%
역천 12
 
2.2%
와룡천 9
 
1.7%
대천천 9
 
1.7%
청지천 5
 
0.9%
판교천 5
 
0.9%
Other values (50) 65
 
12.1%
2023-12-13T05:58:48.512239image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
천 294
22.3%
금 287
21.7%
강 284
21.5%
교 104
 
7.9%
삽 97
 
7.3%
성 26
 
2.0%
안 22
 
1.7%
웅 19
 
1.4%
당 18
 
1.4%
도 14
 
1.1%
Other values (69) 156
11.8%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1321
100.0%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
천 294
22.3%
금 287
21.7%
강 284
21.5%
교 104
 
7.9%
삽 97
 
7.3%
성 26
 
2.0%
안 22
 
1.7%
웅 19
 
1.4%
당 18
 
1.4%
도 14
 
1.1%
Other values (69) 156
11.8%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1321
100.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
천 294
22.3%
금 287
21.7%
강 284
21.5%
교 104
 
7.9%
삽 97
 
7.3%
성 26
 
2.0%
안 22
 
1.7%
웅 19
 
1.4%
당 18
 
1.4%
도 14
 
1.1%
Other values (69) 156
11.8%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1321
100.0%

Most frequent character per block

Hangul
ValueCountFrequency (%)
천 294
22.3%
금 287
21.7%
강 284
21.5%
교 104
 
7.9%
삽 97
 
7.3%
성 26
 
2.0%
안 22
 
1.7%
웅 19
 
1.4%
당 18
 
1.4%
도 14
 
1.1%
Other values (69) 156
11.8%

제1지류
Text

MISSING 

Distinct143
Distinct (%)29.9%
Missing61
Missing (%)11.3%
Memory size4.3 KiB
2023-12-13T05:58:48.845820image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length4
Median length3
Mean length2.8933054
Min length2

Characters and Unicode

Total characters1383
Distinct characters123
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique87 ?
Unique (%)18.2%

Sample

1st row석성천
2nd row석성천
3rd row석성천
4th row석성천
5th row논산천
ValueCountFrequency (%)
곡교천 35
 
7.3%
무한천 33
 
6.9%
논산천 30
 
6.3%
미호천 26
 
5.4%
지천 26
 
5.4%
유구천 18
 
3.8%
봉황천 17
 
3.6%
정안천 14
 
2.9%
대교천 12
 
2.5%
석성천 11
 
2.3%
Other values (133) 256
53.6%
2023-12-13T05:58:49.287122image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
천 484
35.0%
산 62
 
4.5%
교 51
 
3.7%
곡 43
 
3.1%
성 40
 
2.9%
무 34
 
2.5%
한 33
 
2.4%
논 30
 
2.2%
지 30
 
2.2%
미 29
 
2.1%
Other values (113) 547
39.6%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1383
100.0%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
천 484
35.0%
산 62
 
4.5%
교 51
 
3.7%
곡 43
 
3.1%
성 40
 
2.9%
무 34
 
2.5%
한 33
 
2.4%
논 30
 
2.2%
지 30
 
2.2%
미 29
 
2.1%
Other values (113) 547
39.6%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1383
100.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
천 484
35.0%
산 62
 
4.5%
교 51
 
3.7%
곡 43
 
3.1%
성 40
 
2.9%
무 34
 
2.5%
한 33
 
2.4%
논 30
 
2.2%
지 30
 
2.2%
미 29
 
2.1%
Other values (113) 547
39.6%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1383
100.0%

Most frequent character per block

Hangul
ValueCountFrequency (%)
천 484
35.0%
산 62
 
4.5%
교 51
 
3.7%
곡 43
 
3.1%
성 40
 
2.9%
무 34
 
2.5%
한 33
 
2.4%
논 30
 
2.2%
지 30
 
2.2%
미 29
 
2.1%
Other values (113) 547
39.6%

제2지류
Text

MISSING 

Distinct200
Distinct (%)60.2%
Missing207
Missing (%)38.4%
Memory size4.3 KiB
2023-12-13T05:58:49.614094image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length4
Median length3
Mean length2.9156627
Min length1

Characters and Unicode

Total characters968
Distinct characters152
Distinct categories2 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique150 ?
Unique (%)45.2%

Sample

1st row응평천
2nd row증산천
3rd row증산천
4th row현내천
5th row오산천
ValueCountFrequency (%)
신양천 14
 
4.3%
노성천 13
 
4.0%
구룡천 9
 
2.7%
병천천 9
 
2.7%
조천 8
 
2.4%
온양천 6
 
1.8%
강경천 6
 
1.8%
천안천 5
 
1.5%
기사천 5
 
1.5%
유등천 5
 
1.5%
Other values (189) 248
75.6%
2023-12-13T05:58:50.104338image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
천 345
35.6%
신 26
 
2.7%
양 23
 
2.4%
성 20
 
2.1%
산 19
 
2.0%
곡 18
 
1.9%
노 16
 
1.7%
룡 16
 
1.7%
정 14
 
1.4%
봉 13
 
1.3%
Other values (142) 458
47.3%

Most occurring categories

ValueCountFrequency (%)
Other Letter 964
99.6%
Space Separator 4
 
0.4%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
천 345
35.8%
신 26
 
2.7%
양 23
 
2.4%
성 20
 
2.1%
산 19
 
2.0%
곡 18
 
1.9%
노 16
 
1.7%
룡 16
 
1.7%
정 14
 
1.5%
봉 13
 
1.3%
Other values (141) 454
47.1%
Space Separator
ValueCountFrequency (%)
4
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 964
99.6%
Common 4
 
0.4%

Most frequent character per script

Hangul
ValueCountFrequency (%)
천 345
35.8%
신 26
 
2.7%
양 23
 
2.4%
성 20
 
2.1%
산 19
 
2.0%
곡 18
 
1.9%
노 16
 
1.7%
룡 16
 
1.7%
정 14
 
1.5%
봉 13
 
1.3%
Other values (141) 454
47.1%
Common
ValueCountFrequency (%)
4
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 964
99.6%
ASCII 4
 
0.4%

Most frequent character per block

Hangul
ValueCountFrequency (%)
천 345
35.8%
신 26
 
2.7%
양 23
 
2.4%
성 20
 
2.1%
산 19
 
2.0%
곡 18
 
1.9%
노 16
 
1.7%
룡 16
 
1.7%
정 14
 
1.5%
봉 13
 
1.3%
Other values (141) 454
47.1%
ASCII
ValueCountFrequency (%)
4
100.0%

제3지류
Text

MISSING 

Distinct92
Distinct (%)78.6%
Missing422
Missing (%)78.3%
Memory size4.3 KiB
2023-12-13T05:58:50.384072image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length3
Median length3
Mean length2.9316239
Min length1

Characters and Unicode

Total characters343
Distinct characters95
Distinct categories2 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique78 ?
Unique (%)66.7%

Sample

1st row정각천
2nd row하대천
3rd row월암천
4th row용두천
5th row월산천
ValueCountFrequency (%)
화산천 7
 
6.1%
연산천 4
 
3.5%
마산천 4
 
3.5%
주천 3
 
2.6%
승천천 3
 
2.6%
국촌천 2
 
1.7%
아산천 2
 
1.7%
외부천 2
 
1.7%
율지천 2
 
1.7%
수목천 2
 
1.7%
Other values (81) 84
73.0%
2023-12-13T05:58:50.758939image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
천 120
35.0%
산 25
 
7.3%
화 7
 
2.0%
곡 7
 
2.0%
마 6
 
1.7%
성 6
 
1.7%
장 5
 
1.5%
암 5
 
1.5%
주 4
 
1.2%
금 4
 
1.2%
Other values (85) 154
44.9%

Most occurring categories

ValueCountFrequency (%)
Other Letter 341
99.4%
Space Separator 2
 
0.6%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
천 120
35.2%
산 25
 
7.3%
화 7
 
2.1%
곡 7
 
2.1%
마 6
 
1.8%
성 6
 
1.8%
장 5
 
1.5%
암 5
 
1.5%
주 4
 
1.2%
금 4
 
1.2%
Other values (84) 152
44.6%
Space Separator
ValueCountFrequency (%)
2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 341
99.4%
Common 2
 
0.6%

Most frequent character per script

Hangul
ValueCountFrequency (%)
천 120
35.2%
산 25
 
7.3%
화 7
 
2.1%
곡 7
 
2.1%
마 6
 
1.8%
성 6
 
1.8%
장 5
 
1.5%
암 5
 
1.5%
주 4
 
1.2%
금 4
 
1.2%
Other values (84) 152
44.6%
Common
ValueCountFrequency (%)
2
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 341
99.4%
ASCII 2
 
0.6%

Most frequent character per block

Hangul
ValueCountFrequency (%)
천 120
35.2%
산 25
 
7.3%
화 7
 
2.1%
곡 7
 
2.1%
마 6
 
1.8%
성 6
 
1.8%
장 5
 
1.5%
암 5
 
1.5%
주 4
 
1.2%
금 4
 
1.2%
Other values (84) 152
44.6%
ASCII
ValueCountFrequency (%)
2
100.0%

제4지류
Text

MISSING 

Distinct21
Distinct (%)95.5%
Missing517
Missing (%)95.9%
Memory size4.3 KiB
2023-12-13T05:58:50.984951image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length3
Median length3
Mean length2.9545455
Min length2

Characters and Unicode

Total characters65
Distinct characters32
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique20 ?
Unique (%)90.9%

Sample

1st row대명천
2nd row대촌천
3rd row도곡천
4th row신암천
5th row왕덕천
ValueCountFrequency (%)
황화천 2
 
9.1%
산동천 1
 
4.5%
하천천 1
 
4.5%
은곡천 1
 
4.5%
용마천 1
 
4.5%
지압천 1
 
4.5%
조양천 1
 
4.5%
서원천 1
 
4.5%
대암천 1
 
4.5%
행화천 1
 
4.5%
Other values (11) 11
50.0%
2023-12-13T05:58:51.275306image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
천 23
35.4%
곡 4
 
6.2%
대 4
 
6.2%
화 3
 
4.6%
황 2
 
3.1%
암 2
 
3.1%
왕 2
 
3.1%
은 1
 
1.5%
하 1
 
1.5%
행 1
 
1.5%
Other values (22) 22
33.8%

Most occurring categories

ValueCountFrequency (%)
Other Letter 65
100.0%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
천 23
35.4%
곡 4
 
6.2%
대 4
 
6.2%
화 3
 
4.6%
황 2
 
3.1%
암 2
 
3.1%
왕 2
 
3.1%
은 1
 
1.5%
하 1
 
1.5%
행 1
 
1.5%
Other values (22) 22
33.8%

Most occurring scripts

ValueCountFrequency (%)
Hangul 65
100.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
천 23
35.4%
곡 4
 
6.2%
대 4
 
6.2%
화 3
 
4.6%
황 2
 
3.1%
암 2
 
3.1%
왕 2
 
3.1%
은 1
 
1.5%
하 1
 
1.5%
행 1
 
1.5%
Other values (22) 22
33.8%

Most occurring blocks

ValueCountFrequency (%)
Hangul 65
100.0%

Most frequent character per block

Hangul
ValueCountFrequency (%)
천 23
35.4%
곡 4
 
6.2%
대 4
 
6.2%
화 3
 
4.6%
황 2
 
3.1%
암 2
 
3.1%
왕 2
 
3.1%
은 1
 
1.5%
하 1
 
1.5%
행 1
 
1.5%
Other values (22) 22
33.8%

제5지류
Text

MISSING 

Distinct2
Distinct (%)100.0%
Missing537
Missing (%)99.6%
Memory size4.3 KiB
2023-12-13T05:58:51.385329image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length3
Median length2
Mean length2
Min length1

Characters and Unicode

Total characters4
Distinct characters4
Distinct categories2 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique2 ?
Unique (%)100.0%

Sample

1st row
2nd row수철천
ValueCountFrequency (%)
수철천 1
100.0%
2023-12-13T05:58:51.652741image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1
25.0%
수 1
25.0%
철 1
25.0%
천 1
25.0%

Most occurring categories

ValueCountFrequency (%)
Other Letter 3
75.0%
Space Separator 1
 
25.0%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
수 1
33.3%
철 1
33.3%
천 1
33.3%
Space Separator
ValueCountFrequency (%)
1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 3
75.0%
Common 1
 
25.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
수 1
33.3%
철 1
33.3%
천 1
33.3%
Common
ValueCountFrequency (%)
1
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 3
75.0%
ASCII 1
 
25.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1
100.0%
Hangul
ValueCountFrequency (%)
수 1
33.3%
철 1
33.3%
천 1
33.3%

하천등급
Categorical

IMBALANCE 

Distinct3
Distinct (%)0.6%
Missing0
Missing (%)0.0%
Memory size4.3 KiB
지방2급
527 
지방1급
 
11
국가하천
 
1

Length

Max length4
Median length4
Mean length4
Min length4

Unique

Unique1 ?
Unique (%)0.2%

Sample

1st row지방2급
2nd row지방2급
3rd row지방2급
4th row지방2급
5th row지방2급

Common Values

ValueCountFrequency (%)
지방2급 527
97.8%
지방1급 11
 
2.0%
국가하천 1
 
0.2%

Length

2023-12-13T05:58:51.794684image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T05:58:51.883711image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
지방2급 527
97.8%
지방1급 11
 
2.0%
국가하천 1
 
0.2%

수계
Categorical

HIGH CORRELATION 

Distinct4
Distinct (%)0.7%
Missing0
Missing (%)0.0%
Memory size4.3 KiB
금강
284 
기타
137 
삽교천
97 
안성천
 
21

Length

Max length3
Median length2
Mean length2.2189239
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
금강 284
52.7%
기타 137
25.4%
삽교천 97
 
18.0%
안성천 21
 
3.9%

Length

2023-12-13T05:58:51.987066image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T05:58:52.102584image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
금강 284
52.7%
기타 137
25.4%
삽교천 97
 
18.0%
안성천 21
 
3.9%

Interactions

2023-12-13T05:58:45.902623image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-13T05:58:52.177305image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
하천코드본류제3지류제4지류제5지류하천등급수계
하천코드1.0001.0000.939NaNNaN0.1051.000
본류1.0001.0000.9421.000NaN0.0001.000
제3지류0.9390.9421.0001.000NaN0.0000.980
제4지류NaN1.0001.0001.000NaNNaN1.000
제5지류NaNNaNNaNNaN1.000NaNNaN
하천등급0.1050.0000.000NaNNaN1.0000.005
수계1.0001.0000.9801.000NaN0.0051.000
2023-12-13T05:58:52.305254image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
하천등급수계
하천등급1.0000.003
수계0.0031.000
2023-12-13T05:58:52.408003image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
하천코드하천등급수계
하천코드1.0000.0320.999
하천등급0.0321.0000.003
수계0.9990.0031.000

Missing values

2023-12-13T05:58:46.059020image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-13T05:58:46.255272image/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.
2023-12-13T05:58:46.429218image/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

하천코드하천명본류제1지류제2지류제3지류제4지류제5지류하천등급수계
03023930응평천금강석성천응평천<NA><NA><NA>지방2급금강
13023940증산천금강석성천증산천<NA><NA><NA>지방2급금강
23023950정각천금강석성천증산천정각천<NA><NA>지방2급금강
33023960현내천금강석성천현내천<NA><NA><NA>지방2급금강
43024010오산천금강논산천오산천<NA><NA><NA>지방2급금강
53024020양촌천금강논산천양촌천<NA><NA><NA>지방2급금강
63024030입촌천금강논산천입촌천<NA><NA><NA>지방2급금강
73024040장성천금강논산천장성천<NA><NA><NA>지방2급금강
83024050웅천금강논산천웅천<NA><NA><NA>지방2급금강
93024060명암천금강논산천명암천<NA><NA><NA>지방2급금강
하천코드하천명본류제1지류제2지류제3지류제4지류제5지류하천등급수계
5293023830봉두천금강봉두천<NA><NA><NA><NA>지방2급금강
5303023840하황천금강하황천<NA><NA><NA><NA>지방2급금강
5313023850상황천금강하황천상황천<NA><NA><NA>지방2급금강
5323023860화수천금강화수천<NA><NA><NA><NA>지방2급금강
5333023880광명천금강석성천광명천<NA><NA><NA>지방2급금강
5343023890신영천금강석성천신영천<NA><NA><NA>지방2급금강
5353023900노티천금강석성천노티천<NA><NA><NA>지방2급금강
5363023910덕포천금강석성천덕포천<NA><NA><NA>지방2급금강
5373023920하관천금강석성천하관천<NA><NA><NA>지방2급금강
5383004080노성천금강<NA><NA><NA><NA><NA>국가하천금강