Overview

Dataset statistics

Number of variables9
Number of observations222
Missing cells8
Missing cells (%)0.4%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory16.6 KiB
Average record size in memory76.6 B

Variable types

Numeric3
Text4
Categorical2

Dataset

Description지적재조사를 실행하는 한국국토정보공사(LX)의 기관정보에 관한 목록파일입니다.기관정보는 본사, 본부, 지사, 처로 이루어져있고, 한국국토정보공사 홈페이지에서도 담당자와 연락처를 보실 수 있습니다.
Author국토교통부
URLhttps://www.data.go.kr/data/15118425/fileData.do

Alerts

지적공사기관구분코드 is highly overall correlated with 상위지적공사기관코드 and 2 other fieldsHigh correlation
지적공사기관구분명 is highly overall correlated with 상위지적공사기관코드 and 2 other fieldsHigh correlation
상위지적공사기관코드 is highly overall correlated with 지적공사기관코드 and 2 other fieldsHigh correlation
지적공사기관코드 is highly overall correlated with 상위지적공사기관코드 and 3 other fieldsHigh correlation
전화번호 is highly overall correlated with 지적공사기관코드High correlation
지적공사기관구분코드 is highly imbalanced (50.2%)Imbalance
지적공사기관구분명 is highly imbalanced (50.2%)Imbalance
상위지적공사기관코드 has 6 (2.7%) missing valuesMissing
지적공사기관코드 has unique valuesUnique

Reproduction

Analysis started2024-04-20 21:31:50.080798
Analysis finished2024-04-20 21:31:52.963176
Duration2.88 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

상위지적공사기관코드
Real number (ℝ)

HIGH CORRELATION  MISSING 

Distinct14
Distinct (%)6.5%
Missing6
Missing (%)2.7%
Infinite0
Infinite (%)0.0%
Mean815787.04
Minimum100000
Maximum940000
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size2.1 KiB
2024-04-21T06:31:53.352243image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum100000
5-th percentile100000
Q1830000
median860000
Q3920000
95-th percentile940000
Maximum940000
Range840000
Interquartile range (IQR)90000

Descriptive statistics

Standard deviation190900.76
Coefficient of variation (CV)0.23400808
Kurtosis9.2932812
Mean815787.04
Median Absolute Deviation (MAD)40000
Skewness-3.1668982
Sum1.7621 × 108
Variance3.6443099 × 1010
MonotonicityNot monotonic
2024-04-21T06:31:53.546048image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=14)
ValueCountFrequency (%)
870000 27
12.2%
860000 24
10.8%
920000 22
9.9%
840000 20
9.0%
930000 20
9.0%
820000 17
7.7%
850000 15
6.8%
100000 13
5.9%
830000 13
5.9%
940000 13
5.9%
Other values (4) 32
14.4%
ValueCountFrequency (%)
100000 13
5.9%
700000 12
5.4%
730000 6
 
2.7%
820000 17
7.7%
830000 13
5.9%
840000 20
9.0%
850000 15
6.8%
860000 24
10.8%
870000 27
12.2%
890000 4
 
1.8%
ValueCountFrequency (%)
940000 13
5.9%
930000 20
9.0%
920000 22
9.9%
910000 10
 
4.5%
890000 4
 
1.8%
870000 27
12.2%
860000 24
10.8%
850000 15
6.8%
840000 20
9.0%
830000 13
5.9%

상위지적공사기관명
Text

Distinct210
Distinct (%)94.6%
Missing0
Missing (%)0.0%
Memory size1.9 KiB
2024-04-21T06:31:54.257677image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length14
Median length4
Mean length5.2792793
Min length2

Characters and Unicode

Total characters1172
Distinct characters126
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

Unique209 ?
Unique (%)94.1%

Sample

1st row본사
2nd row서울지역본부
3rd row서울사업처
4th row강동송파지사
5th row강서양천지사
ValueCountFrequency (%)
공간정보사업처 13
 
5.9%
강원지적재조사추진단 1
 
0.5%
대구동부지사 1
 
0.5%
장흥강진지사 1
 
0.5%
서울북부지사 1
 
0.5%
서귀포지사 1
 
0.5%
울산지사 1
 
0.5%
임실순창지사 1
 
0.5%
영주봉화지사 1
 
0.5%
진안장수지사 1
 
0.5%
Other values (200) 200
90.1%
2024-04-21T06:31:55.216848image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
사 210
 
17.9%
지 195
 
16.6%
부 54
 
4.6%
주 29
 
2.5%
업 27
 
2.3%
처 27
 
2.3%
천 27
 
2.3%
산 24
 
2.0%
남 23
 
2.0%
서 19
 
1.6%
Other values (116) 537
45.8%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1172
100.0%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
사 210
 
17.9%
지 195
 
16.6%
부 54
 
4.6%
주 29
 
2.5%
업 27
 
2.3%
처 27
 
2.3%
천 27
 
2.3%
산 24
 
2.0%
남 23
 
2.0%
서 19
 
1.6%
Other values (116) 537
45.8%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1172
100.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
사 210
 
17.9%
지 195
 
16.6%
부 54
 
4.6%
주 29
 
2.5%
업 27
 
2.3%
처 27
 
2.3%
천 27
 
2.3%
산 24
 
2.0%
남 23
 
2.0%
서 19
 
1.6%
Other values (116) 537
45.8%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1172
100.0%

Most frequent character per block

Hangul
ValueCountFrequency (%)
사 210
 
17.9%
지 195
 
16.6%
부 54
 
4.6%
주 29
 
2.5%
업 27
 
2.3%
처 27
 
2.3%
천 27
 
2.3%
산 24
 
2.0%
남 23
 
2.0%
서 19
 
1.6%
Other values (116) 537
45.8%

지적공사기관코드
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct222
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean856736.66
Minimum100000
Maximum940150
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size2.1 KiB
2024-04-21T06:31:55.618392image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum100000
5-th percentile700430.5
Q1830282.5
median860335
Q3920088.5
95-th percentile940039.05
Maximum940150
Range840150
Interquartile range (IQR)89806

Descriptive statistics

Standard deviation79567.624
Coefficient of variation (CV)0.092872907
Kurtosis36.320067
Mean856736.66
Median Absolute Deviation (MAD)40008.5
Skewness-4.3038322
Sum1.9019554 × 108
Variance6.3310069 × 109
MonotonicityNot monotonic
2024-04-21T06:31:56.020765image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
100000 1
 
0.5%
910120 1
 
0.5%
860400 1
 
0.5%
700430 1
 
0.5%
860390 1
 
0.5%
810730 1
 
0.5%
700420 1
 
0.5%
920120 1
 
0.5%
920160 1
 
0.5%
920230 1
 
0.5%
Other values (212) 212
95.5%
ValueCountFrequency (%)
100000 1
0.5%
700000 1
0.5%
700021 1
0.5%
700190 1
0.5%
700265 1
0.5%
700320 1
0.5%
700370 1
0.5%
700390 1
0.5%
700400 1
0.5%
700410 1
0.5%
ValueCountFrequency (%)
940150 1
0.5%
940140 1
0.5%
940130 1
0.5%
940120 1
0.5%
940110 1
0.5%
940100 1
0.5%
940090 1
0.5%
940080 1
0.5%
940070 1
0.5%
940060 1
0.5%

지적공사기관명
Text

Distinct210
Distinct (%)94.6%
Missing0
Missing (%)0.0%
Memory size1.9 KiB
2024-04-21T06:31:56.848708image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length14
Median length4
Mean length5.2792793
Min length2

Characters and Unicode

Total characters1172
Distinct characters126
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

Unique209 ?
Unique (%)94.1%

Sample

1st row본사
2nd row서울지역본부
3rd row서울사업처
4th row강동송파지사
5th row강서양천지사
ValueCountFrequency (%)
공간정보사업처 13
 
5.9%
강원지적재조사추진단 1
 
0.5%
대구동부지사 1
 
0.5%
장흥강진지사 1
 
0.5%
서울북부지사 1
 
0.5%
서귀포지사 1
 
0.5%
울산지사 1
 
0.5%
임실순창지사 1
 
0.5%
영주봉화지사 1
 
0.5%
진안장수지사 1
 
0.5%
Other values (200) 200
90.1%
2024-04-21T06:31:58.155889image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
사 210
 
17.9%
지 195
 
16.6%
부 54
 
4.6%
주 29
 
2.5%
업 27
 
2.3%
처 27
 
2.3%
천 27
 
2.3%
산 24
 
2.0%
남 23
 
2.0%
서 19
 
1.6%
Other values (116) 537
45.8%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1172
100.0%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
사 210
 
17.9%
지 195
 
16.6%
부 54
 
4.6%
주 29
 
2.5%
업 27
 
2.3%
처 27
 
2.3%
천 27
 
2.3%
산 24
 
2.0%
남 23
 
2.0%
서 19
 
1.6%
Other values (116) 537
45.8%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1172
100.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
사 210
 
17.9%
지 195
 
16.6%
부 54
 
4.6%
주 29
 
2.5%
업 27
 
2.3%
처 27
 
2.3%
천 27
 
2.3%
산 24
 
2.0%
남 23
 
2.0%
서 19
 
1.6%
Other values (116) 537
45.8%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1172
100.0%

Most frequent character per block

Hangul
ValueCountFrequency (%)
사 210
 
17.9%
지 195
 
16.6%
부 54
 
4.6%
주 29
 
2.5%
업 27
 
2.3%
처 27
 
2.3%
천 27
 
2.3%
산 24
 
2.0%
남 23
 
2.0%
서 19
 
1.6%
Other values (116) 537
45.8%

지적공사기관약어
Text

Distinct213
Distinct (%)95.9%
Missing0
Missing (%)0.0%
Memory size1.9 KiB
2024-04-21T06:31:59.118249image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length12
Median length3
Mean length4.2432432
Min length2

Characters and Unicode

Total characters942
Distinct characters132
Distinct categories2 ?
Distinct scripts2 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique209 ?
Unique (%)94.1%

Sample

1st row본사
2nd row서울본부
3rd row서울사업처
4th row강동송파구
5th row강서양천
ValueCountFrequency (%)
공간정보사업처 7
 
3.2%
지적사업처 2
 
0.9%
연천군 2
 
0.9%
여주시 2
 
0.9%
서울동부지사 1
 
0.5%
서귀포시 1
 
0.5%
남해군 1
 
0.5%
진주시 1
 
0.5%
진안장수 1
 
0.5%
태백시·삼척시·동해 1
 
0.5%
Other values (203) 203
91.4%
2024-04-21T06:32:00.198915image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
시 69
 
7.3%
사 64
 
6.8%
군 61
 
6.5%
부 52
 
5.5%
주 30
 
3.2%
지 29
 
3.1%
처 26
 
2.8%
천 26
 
2.8%
업 26
 
2.8%
남 22
 
2.3%
Other values (122) 537
57.0%

Most occurring categories

ValueCountFrequency (%)
Other Letter 937
99.5%
Other Punctuation 5
 
0.5%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
시 69
 
7.4%
사 64
 
6.8%
군 61
 
6.5%
부 52
 
5.5%
주 30
 
3.2%
지 29
 
3.1%
처 26
 
2.8%
천 26
 
2.8%
업 26
 
2.8%
남 22
 
2.3%
Other values (120) 532
56.8%
Other Punctuation
ValueCountFrequency (%)
· 3
60.0%
. 2
40.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 937
99.5%
Common 5
 
0.5%

Most frequent character per script

Hangul
ValueCountFrequency (%)
시 69
 
7.4%
사 64
 
6.8%
군 61
 
6.5%
부 52
 
5.5%
주 30
 
3.2%
지 29
 
3.1%
처 26
 
2.8%
천 26
 
2.8%
업 26
 
2.8%
남 22
 
2.3%
Other values (120) 532
56.8%
Common
ValueCountFrequency (%)
· 3
60.0%
. 2
40.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 937
99.5%
None 3
 
0.3%
ASCII 2
 
0.2%

Most frequent character per block

Hangul
ValueCountFrequency (%)
시 69
 
7.4%
사 64
 
6.8%
군 61
 
6.5%
부 52
 
5.5%
주 30
 
3.2%
지 29
 
3.1%
처 26
 
2.8%
천 26
 
2.8%
업 26
 
2.8%
남 22
 
2.3%
Other values (120) 532
56.8%
None
ValueCountFrequency (%)
· 3
100.0%
ASCII
ValueCountFrequency (%)
. 2
100.0%

기관장명
Text

Distinct207
Distinct (%)93.7%
Missing1
Missing (%)0.5%
Memory size1.9 KiB
2024-04-21T06:32:01.322736image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length3
Median length3
Mean length2.9909502
Min length2

Characters and Unicode

Total characters661
Distinct characters129
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

Unique195 ?
Unique (%)88.2%

Sample

1st row이승택
2nd row김정환
3rd row한종기
4th row이명근
5th row채은식
ValueCountFrequency (%)
전현식 4
 
1.8%
백경화 2
 
0.9%
방성배 2
 
0.9%
정한용 2
 
0.9%
임종삼 2
 
0.9%
박호성 2
 
0.9%
강영구 2
 
0.9%
김원준 2
 
0.9%
이재득 2
 
0.9%
김창호 2
 
0.9%
Other values (197) 199
90.0%
2024-04-21T06:32:02.659960image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
김 39
 
5.9%
이 38
 
5.7%
영 23
 
3.5%
박 19
 
2.9%
최 17
 
2.6%
종 17
 
2.6%
정 16
 
2.4%
원 14
 
2.1%
재 13
 
2.0%
식 13
 
2.0%
Other values (119) 452
68.4%

Most occurring categories

ValueCountFrequency (%)
Other Letter 661
100.0%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
김 39
 
5.9%
이 38
 
5.7%
영 23
 
3.5%
박 19
 
2.9%
최 17
 
2.6%
종 17
 
2.6%
정 16
 
2.4%
원 14
 
2.1%
재 13
 
2.0%
식 13
 
2.0%
Other values (119) 452
68.4%

Most occurring scripts

ValueCountFrequency (%)
Hangul 661
100.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
김 39
 
5.9%
이 38
 
5.7%
영 23
 
3.5%
박 19
 
2.9%
최 17
 
2.6%
종 17
 
2.6%
정 16
 
2.4%
원 14
 
2.1%
재 13
 
2.0%
식 13
 
2.0%
Other values (119) 452
68.4%

Most occurring blocks

ValueCountFrequency (%)
Hangul 661
100.0%

Most frequent character per block

Hangul
ValueCountFrequency (%)
김 39
 
5.9%
이 38
 
5.7%
영 23
 
3.5%
박 19
 
2.9%
최 17
 
2.6%
종 17
 
2.6%
정 16
 
2.4%
원 14
 
2.1%
재 13
 
2.0%
식 13
 
2.0%
Other values (119) 452
68.4%

전화번호
Real number (ℝ)

HIGH CORRELATION 

Distinct197
Distinct (%)89.1%
Missing1
Missing (%)0.5%
Infinite0
Infinite (%)0.0%
Mean7.209987 × 108
Minimum2.69372 × 108
Maximum3.1809989 × 109
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size2.1 KiB
2024-04-21T06:32:03.012357image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum2.69372 × 108
5-th percentile2.6937237 × 108
Q13.3853834 × 108
median5.3714793 × 108
Q36.1876642 × 108
95-th percentile3.1806671 × 109
Maximum3.1809989 × 109
Range2.9116269 × 109
Interquartile range (IQR)2.8022808 × 108

Descriptive statistics

Standard deviation7.860452 × 108
Coefficient of variation (CV)1.0902172
Kurtosis5.919426
Mean7.209987 × 108
Median Absolute Deviation (MAD)1.001552 × 108
Skewness2.7563134
Sum1.5934071 × 1011
Variance6.1786705 × 1017
MonotonicityNot monotonic
2024-04-21T06:32:03.440858image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
312500942 6
 
2.7%
517945002 3
 
1.4%
332505350 3
 
1.4%
627146888 3
 
1.4%
632402740 3
 
1.4%
312904401 3
 
1.4%
537147800 3
 
1.4%
437104212 3
 
1.4%
552505303 3
 
1.4%
327132501 3
 
1.4%
Other values (187) 188
84.7%
ValueCountFrequency (%)
269372000 1
0.5%
269372020 1
0.5%
269372040 1
0.5%
269372120 1
0.5%
269372150 1
0.5%
269372180 1
0.5%
269372210 1
0.5%
269372240 1
0.5%
269372270 1
0.5%
269372300 1
0.5%
ValueCountFrequency (%)
3180998860 1
0.5%
3180998830 1
0.5%
3180988960 1
0.5%
3180892930 1
0.5%
3180882900 1
0.5%
3180873460 1
0.5%
3180793800 1
0.5%
3180783400 1
0.5%
3180770670 1
0.5%
3180770600 1
0.5%

지적공사기관구분코드
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct4
Distinct (%)1.8%
Missing0
Missing (%)0.0%
Memory size1.9 KiB
3
171 
4
37 
2
 
13
1
 
1

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique1 ?
Unique (%)0.5%

Sample

1st row1
2nd row2
3rd row4
4th row3
5th row3

Common Values

ValueCountFrequency (%)
3 171
77.0%
4 37
 
16.7%
2 13
 
5.9%
1 1
 
0.5%

Length

2024-04-21T06:32:03.842350image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-21T06:32:04.169196image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
3 171
77.0%
4 37
 
16.7%
2 13
 
5.9%
1 1
 
0.5%

지적공사기관구분명
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct4
Distinct (%)1.8%
Missing0
Missing (%)0.0%
Memory size1.9 KiB
지사
171 
처 또는 추진단
37 
본부
 
13
본사
 
1

Length

Max length8
Median length2
Mean length3
Min length2

Unique

Unique1 ?
Unique (%)0.5%

Sample

1st row본사
2nd row본부
3rd row처 또는 추진단
4th row지사
5th row지사

Common Values

ValueCountFrequency (%)
지사 171
77.0%
처 또는 추진단 37
 
16.7%
본부 13
 
5.9%
본사 1
 
0.5%

Length

2024-04-21T06:32:04.558891image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-21T06:32:04.857509image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
지사 171
57.8%
처 37
 
12.5%
또는 37
 
12.5%
추진단 37
 
12.5%
본부 13
 
4.4%
본사 1
 
0.3%

Interactions

2024-04-21T06:31:51.855905image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T06:31:50.814966image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T06:31:51.414412image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T06:31:52.012090image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T06:31:50.991219image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T06:31:51.548522image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T06:31:52.169868image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T06:31:51.222330image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T06:31:51.690849image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-04-21T06:32:04.987366image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
상위지적공사기관코드지적공사기관코드전화번호지적공사기관구분코드지적공사기관구분명
상위지적공사기관코드1.0001.0000.5180.0000.000
지적공사기관코드1.0001.0000.5170.0000.000
전화번호0.5180.5171.0000.2320.232
지적공사기관구분코드0.0000.0000.2321.0001.000
지적공사기관구분명0.0000.0000.2321.0001.000
2024-04-21T06:32:05.153157image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
지적공사기관구분코드지적공사기관구분명
지적공사기관구분코드1.0001.000
지적공사기관구분명1.0001.000
2024-04-21T06:32:05.311622image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
상위지적공사기관코드지적공사기관코드전화번호지적공사기관구분코드지적공사기관구분명
상위지적공사기관코드1.0000.8970.4810.7010.701
지적공사기관코드0.8971.0000.5200.5710.571
전화번호0.4810.5201.0000.0750.075
지적공사기관구분코드0.7010.5710.0751.0001.000
지적공사기관구분명0.7010.5710.0751.0001.000

Missing values

2024-04-21T06:31:52.416363image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-04-21T06:31:52.677144image/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.
2024-04-21T06:31:52.866240image/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

상위지적공사기관코드상위지적공사기관명지적공사기관코드지적공사기관명지적공사기관약어기관장명전화번호지적공사기관구분코드지적공사기관구분명
0<NA>본사100000본사본사<NA><NA>1본사
1100000서울지역본부700000서울지역본부서울본부이승택2693720002본부
2700000서울사업처700021서울사업처서울사업처김정환2693720204처 또는 추진단
3700000강동송파지사700190강동송파지사강동송파구한종기2693721503지사
4700000강서양천지사700320강서양천지사강서양천이명근2693721803지사
5700000용산마포지사700370용산마포지사용산마포채은식2693723003지사
6100000인천지역본부730000인천지역본부인천본부이화영3271325012본부
7730000강화지사730190강화지사강화군김영수3271328003지사
8730000인천북부지사730230인천북부지사인천북부지사이원재3271328403지사
9<NA>구리시지사810300구리시지사구리시전병헌3156643983지사
상위지적공사기관코드상위지적공사기관명지적공사기관코드지적공사기관명지적공사기관약어기관장명전화번호지적공사기관구분코드지적공사기관구분명
212930000안성지사930210안성지사안성시조미숙31804658003지사
213930000여주지사930220여주지사여주시최용태31808734603지사
214100000경기북부지역본부940000경기북부지역본부경기북부본부방성배3125009422본부
215940000경기북부사업처940021경기북부사업처경기북부사업처전현식3125009424처 또는 추진단
216940000경기북부지적재조사추진단940040경기북부지적재조사추진단경기북부재조사전현식3125009424처 또는 추진단
217870000공간정보사업처870411공간정보사업처공간정보사업처최광수5371478134처 또는 추진단
218870000청송영양지사870392청송영양지사청송영양서재훈5451977803지사
219920000공간정보사업처920311공간정보사업처경남공간정보사업처최창용5525053034처 또는 추진단
220940000공간정보사업처940050공간정보사업처경기공간정보사업처박호성3129044014처 또는 추진단
221940000고양지사940060고양지사고양시윤태윤3199524303지사