Overview

Dataset statistics

Number of variables13
Number of observations29
Missing cells108
Missing cells (%)28.6%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory3.2 KiB
Average record size in memory111.6 B

Variable types

Numeric1
Categorical4
Text5
Boolean1
DateTime2

Dataset

Description제주관광정보센터 상담 S/W 내 외부기관 데이터로 외부기관ID, 기관구분, 기관명 및 주소, 외부기관홈페이지 주소등의 정보를 제공합니다.
Author제주관광공사
URLhttps://www.data.go.kr/data/15038968/fileData.do

Alerts

사용여부 has constant value ""Constant
외부기관홈페이지 has constant value ""Constant
기관구분 is highly overall correlated with 우편번호 and 1 other fieldsHigh correlation
작성자아이디 is highly overall correlated with 우편번호 and 1 other fieldsHigh correlation
수정자아이디 is highly overall correlated with 기관구분 and 2 other fieldsHigh correlation
우편번호 is highly overall correlated with 외부기관아이디 and 3 other fieldsHigh correlation
외부기관아이디 is highly overall correlated with 우편번호High correlation
기관구분 is highly imbalanced (78.4%)Imbalance
우편번호 is highly imbalanced (72.8%)Imbalance
도로명주소1 has 26 (89.7%) missing valuesMissing
도로명주소2 has 27 (93.1%) missing valuesMissing
메모 has 27 (93.1%) missing valuesMissing
외부기관홈페이지 has 28 (96.6%) missing valuesMissing
외부기관아이디 has unique valuesUnique
기관명 has unique valuesUnique

Reproduction

Analysis started2023-12-11 23:37:23.639452
Analysis finished2023-12-11 23:37:24.721591
Duration1.08 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

외부기관아이디
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct29
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean334.24138
Minimum75
Maximum622
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size393.0 B
2023-12-12T08:37:24.769543image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum75
5-th percentile104.4
Q1181
median321
Q3481
95-th percentile593
Maximum622
Range547
Interquartile range (IQR)300

Descriptive statistics

Standard deviation171.04086
Coefficient of variation (CV)0.51172856
Kurtosis-1.3062808
Mean334.24138
Median Absolute Deviation (MAD)159
Skewness0.14659852
Sum9693
Variance29254.975
MonotonicityNot monotonic
2023-12-12T08:37:24.879730image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=29)
ValueCountFrequency (%)
121 1
 
3.4%
141 1
 
3.4%
161 1
 
3.4%
562 1
 
3.4%
441 1
 
3.4%
341 1
 
3.4%
601 1
 
3.4%
541 1
 
3.4%
501 1
 
3.4%
221 1
 
3.4%
Other values (19) 19
65.5%
ValueCountFrequency (%)
75 1
3.4%
104 1
3.4%
105 1
3.4%
121 1
3.4%
141 1
3.4%
161 1
3.4%
162 1
3.4%
181 1
3.4%
201 1
3.4%
221 1
3.4%
ValueCountFrequency (%)
622 1
3.4%
601 1
3.4%
581 1
3.4%
562 1
3.4%
541 1
3.4%
521 1
3.4%
501 1
3.4%
481 1
3.4%
461 1
3.4%
441 1
3.4%

기관구분
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct2
Distinct (%)6.9%
Missing0
Missing (%)0.0%
Memory size364.0 B
150000
28 
180000
 
1

Length

Max length6
Median length6
Mean length6
Min length6

Unique

Unique1 ?
Unique (%)3.4%

Sample

1st row150000
2nd row150000
3rd row150000
4th row150000
5th row150000

Common Values

ValueCountFrequency (%)
150000 28
96.6%
180000 1
 
3.4%

Length

2023-12-12T08:37:25.003905image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T08:37:25.100533image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
150000 28
96.6%
180000 1
 
3.4%

기관명
Text

UNIQUE 

Distinct29
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size364.0 B
2023-12-12T08:37:25.289644image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length20
Median length12
Mean length7.5172414
Min length3

Characters and Unicode

Total characters218
Distinct characters105
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique29 ?
Unique (%)100.0%

Sample

1st row올레고객센터
2nd row제주세계자연유산센터(거문오름탐방문의)
3rd row항림항 도선대합실
4th row제주관광협회(하이제주)
5th row산방산관리사무소
ValueCountFrequency (%)
올레고객센터 1
 
3.0%
이도동 1
 
3.0%
추자면사무소 1
 
3.0%
관광진흥기금 1
 
3.0%
성읍민속마을 1
 
3.0%
제주올레 1
 
3.0%
한라산국립공원 1
 
3.0%
관광약자접근성안내센터 1
 
3.0%
제주실탄사격장 1
 
3.0%
제주목관아 1
 
3.0%
Other values (23) 23
69.7%
2023-12-12T08:37:25.675901image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
제 11
 
5.0%
주 11
 
5.0%
관 8
 
3.7%
산 8
 
3.7%
공 6
 
2.8%
광 6
 
2.8%
사 6
 
2.8%
자 5
 
2.3%
원 5
 
2.3%
터 5
 
2.3%
Other values (95) 147
67.4%

Most occurring categories

ValueCountFrequency (%)
Other Letter 210
96.3%
Space Separator 4
 
1.8%
Close Punctuation 2
 
0.9%
Open Punctuation 2
 
0.9%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
제 11
 
5.2%
주 11
 
5.2%
관 8
 
3.8%
산 8
 
3.8%
공 6
 
2.9%
광 6
 
2.9%
사 6
 
2.9%
자 5
 
2.4%
원 5
 
2.4%
터 5
 
2.4%
Other values (92) 139
66.2%
Space Separator
ValueCountFrequency (%)
4
100.0%
Close Punctuation
ValueCountFrequency (%)
) 2
100.0%
Open Punctuation
ValueCountFrequency (%)
( 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 210
96.3%
Common 8
 
3.7%

Most frequent character per script

Hangul
ValueCountFrequency (%)
제 11
 
5.2%
주 11
 
5.2%
관 8
 
3.8%
산 8
 
3.8%
공 6
 
2.9%
광 6
 
2.9%
사 6
 
2.9%
자 5
 
2.4%
원 5
 
2.4%
터 5
 
2.4%
Other values (92) 139
66.2%
Common
ValueCountFrequency (%)
4
50.0%
) 2
25.0%
( 2
25.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 210
96.3%
ASCII 8
 
3.7%

Most frequent character per block

Hangul
ValueCountFrequency (%)
제 11
 
5.2%
주 11
 
5.2%
관 8
 
3.8%
산 8
 
3.8%
공 6
 
2.9%
광 6
 
2.9%
사 6
 
2.9%
자 5
 
2.4%
원 5
 
2.4%
터 5
 
2.4%
Other values (92) 139
66.2%
ASCII
ValueCountFrequency (%)
4
50.0%
) 2
25.0%
( 2
25.0%

우편번호
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct3
Distinct (%)10.3%
Missing0
Missing (%)0.0%
Memory size364.0 B
<NA>
27 
63122
 
1
63232
 
1

Length

Max length5
Median length4
Mean length4.0689655
Min length4

Unique

Unique2 ?
Unique (%)6.9%

Sample

1st row<NA>
2nd row<NA>
3rd row<NA>
4th row<NA>
5th row<NA>

Common Values

ValueCountFrequency (%)
<NA> 27
93.1%
63122 1
 
3.4%
63232 1
 
3.4%

Length

2023-12-12T08:37:25.840608image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T08:37:25.944736image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 27
93.1%
63122 1
 
3.4%
63232 1
 
3.4%

도로명주소1
Text

MISSING 

Distinct3
Distinct (%)100.0%
Missing26
Missing (%)89.7%
Memory size364.0 B
2023-12-12T08:37:26.075817image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length19
Median length18
Mean length13.333333
Min length3

Characters and Unicode

Total characters40
Distinct characters18
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique3 ?
Unique (%)100.0%

Sample

1st row제주특별자치도 제주시 선덕로 23
2nd row제주특별자치도 제주시 중앙로 342
3rd row추자도
ValueCountFrequency (%)
제주특별자치도 2
22.2%
제주시 2
22.2%
선덕로 1
11.1%
23 1
11.1%
중앙로 1
11.1%
342 1
11.1%
추자도 1
11.1%
2023-12-12T08:37:26.359509image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
6
15.0%
제 4
 
10.0%
주 4
 
10.0%
자 3
 
7.5%
도 3
 
7.5%
특 2
 
5.0%
별 2
 
5.0%
치 2
 
5.0%
시 2
 
5.0%
로 2
 
5.0%
Other values (8) 10
25.0%

Most occurring categories

ValueCountFrequency (%)
Other Letter 29
72.5%
Space Separator 6
 
15.0%
Decimal Number 5
 
12.5%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
제 4
13.8%
주 4
13.8%
자 3
10.3%
도 3
10.3%
특 2
6.9%
별 2
6.9%
치 2
6.9%
시 2
6.9%
로 2
6.9%
앙 1
 
3.4%
Other values (4) 4
13.8%
Decimal Number
ValueCountFrequency (%)
2 2
40.0%
3 2
40.0%
4 1
20.0%
Space Separator
ValueCountFrequency (%)
6
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 29
72.5%
Common 11
 
27.5%

Most frequent character per script

Hangul
ValueCountFrequency (%)
제 4
13.8%
주 4
13.8%
자 3
10.3%
도 3
10.3%
특 2
6.9%
별 2
6.9%
치 2
6.9%
시 2
6.9%
로 2
6.9%
앙 1
 
3.4%
Other values (4) 4
13.8%
Common
ValueCountFrequency (%)
6
54.5%
2 2
 
18.2%
3 2
 
18.2%
4 1
 
9.1%

Most occurring blocks

ValueCountFrequency (%)
Hangul 29
72.5%
ASCII 11
 
27.5%

Most frequent character per block

ASCII
ValueCountFrequency (%)
6
54.5%
2 2
 
18.2%
3 2
 
18.2%
4 1
 
9.1%
Hangul
ValueCountFrequency (%)
제 4
13.8%
주 4
13.8%
자 3
10.3%
도 3
10.3%
특 2
6.9%
별 2
6.9%
치 2
6.9%
시 2
6.9%
로 2
6.9%
앙 1
 
3.4%
Other values (4) 4
13.8%

도로명주소2
Text

MISSING 

Distinct2
Distinct (%)100.0%
Missing27
Missing (%)93.1%
Memory size364.0 B
2023-12-12T08:37:26.513402image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length7
Median length6
Mean length6
Min length5

Characters and Unicode

Total characters12
Distinct characters10
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 row제주 관광센터
2nd row제주소방서
ValueCountFrequency (%)
제주 1
33.3%
관광센터 1
33.3%
제주소방서 1
33.3%
2023-12-12T08:37:26.828437image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
제 2
16.7%
주 2
16.7%
1
8.3%
관 1
8.3%
광 1
8.3%
센 1
8.3%
터 1
8.3%
소 1
8.3%
방 1
8.3%
서 1
8.3%

Most occurring categories

ValueCountFrequency (%)
Other Letter 11
91.7%
Space Separator 1
 
8.3%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
제 2
18.2%
주 2
18.2%
관 1
9.1%
광 1
9.1%
센 1
9.1%
터 1
9.1%
소 1
9.1%
방 1
9.1%
서 1
9.1%
Space Separator
ValueCountFrequency (%)
1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 11
91.7%
Common 1
 
8.3%

Most frequent character per script

Hangul
ValueCountFrequency (%)
제 2
18.2%
주 2
18.2%
관 1
9.1%
광 1
9.1%
센 1
9.1%
터 1
9.1%
소 1
9.1%
방 1
9.1%
서 1
9.1%
Common
ValueCountFrequency (%)
1
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 11
91.7%
ASCII 1
 
8.3%

Most frequent character per block

Hangul
ValueCountFrequency (%)
제 2
18.2%
주 2
18.2%
관 1
9.1%
광 1
9.1%
센 1
9.1%
터 1
9.1%
소 1
9.1%
방 1
9.1%
서 1
9.1%
ASCII
ValueCountFrequency (%)
1
100.0%

메모
Text

MISSING 

Distinct2
Distinct (%)100.0%
Missing27
Missing (%)93.1%
Memory size364.0 B
2023-12-12T08:37:26.974484image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length9
Median length7.5
Mean length7.5
Min length6

Characters and Unicode

Total characters15
Distinct characters12
Distinct categories3 ?
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 row제주웰컴센터
2nd row1566-4669
ValueCountFrequency (%)
제주웰컴센터 1
50.0%
1566-4669 1
50.0%
2023-12-12T08:37:27.257876image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
6 4
26.7%
제 1
 
6.7%
주 1
 
6.7%
웰 1
 
6.7%
컴 1
 
6.7%
센 1
 
6.7%
터 1
 
6.7%
1 1
 
6.7%
5 1
 
6.7%
- 1
 
6.7%
Other values (2) 2
13.3%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 8
53.3%
Other Letter 6
40.0%
Dash Punctuation 1
 
6.7%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
제 1
16.7%
주 1
16.7%
웰 1
16.7%
컴 1
16.7%
센 1
16.7%
터 1
16.7%
Decimal Number
ValueCountFrequency (%)
6 4
50.0%
1 1
 
12.5%
5 1
 
12.5%
4 1
 
12.5%
9 1
 
12.5%
Dash Punctuation
ValueCountFrequency (%)
- 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 9
60.0%
Hangul 6
40.0%

Most frequent character per script

Common
ValueCountFrequency (%)
6 4
44.4%
1 1
 
11.1%
5 1
 
11.1%
- 1
 
11.1%
4 1
 
11.1%
9 1
 
11.1%
Hangul
ValueCountFrequency (%)
제 1
16.7%
주 1
16.7%
웰 1
16.7%
컴 1
16.7%
센 1
16.7%
터 1
16.7%

Most occurring blocks

ValueCountFrequency (%)
ASCII 9
60.0%
Hangul 6
40.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
6 4
44.4%
1 1
 
11.1%
5 1
 
11.1%
- 1
 
11.1%
4 1
 
11.1%
9 1
 
11.1%
Hangul
ValueCountFrequency (%)
제 1
16.7%
주 1
16.7%
웰 1
16.7%
컴 1
16.7%
센 1
16.7%
터 1
16.7%

사용여부
Boolean

CONSTANT 

Distinct1
Distinct (%)3.4%
Missing0
Missing (%)0.0%
Memory size161.0 B
True
29 
ValueCountFrequency (%)
True 29
100.0%
2023-12-12T08:37:27.356046image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

작성일
Date

Distinct28
Distinct (%)96.6%
Missing0
Missing (%)0.0%
Memory size364.0 B
Minimum2017-10-21 00:00:00
Maximum2022-06-13 00:00:00
2023-12-12T08:37:27.446705image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:37:27.571670image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=28)

작성자아이디
Categorical

HIGH CORRELATION 

Distinct9
Distinct (%)31.0%
Missing0
Missing (%)0.0%
Memory size364.0 B
825010
8 
825007
8 
825006
4 
825011
3 
sysmanager
2 
Other values (4)
4 

Length

Max length10
Median length6
Mean length6.2758621
Min length6

Unique

Unique4 ?
Unique (%)13.8%

Sample

1st row825010
2nd row825007
3rd row825004
4th row825013
5th row825010

Common Values

ValueCountFrequency (%)
825010 8
27.6%
825007 8
27.6%
825006 4
13.8%
825011 3
 
10.3%
sysmanager 2
 
6.9%
825004 1
 
3.4%
825013 1
 
3.4%
825014 1
 
3.4%
825002 1
 
3.4%

Length

2023-12-12T08:37:27.714051image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T08:37:27.917013image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
825010 8
27.6%
825007 8
27.6%
825006 4
13.8%
825011 3
 
10.3%
sysmanager 2
 
6.9%
825004 1
 
3.4%
825013 1
 
3.4%
825014 1
 
3.4%
825002 1
 
3.4%

수정일
Date

Distinct27
Distinct (%)93.1%
Missing0
Missing (%)0.0%
Memory size364.0 B
Minimum2017-11-01 00:00:00
Maximum2023-06-02 00:00:00
2023-12-12T08:37:28.054158image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:37:28.225887image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=27)

수정자아이디
Categorical

HIGH CORRELATION 

Distinct9
Distinct (%)31.0%
Missing0
Missing (%)0.0%
Memory size364.0 B
825010
9 
825007
8 
825006
4 
825011
3 
825004
1 
Other values (4)
4 

Length

Max length10
Median length6
Mean length6.137931
Min length6

Unique

Unique5 ?
Unique (%)17.2%

Sample

1st row825010
2nd row825007
3rd row825004
4th row825013
5th row825010

Common Values

ValueCountFrequency (%)
825010 9
31.0%
825007 8
27.6%
825006 4
13.8%
825011 3
 
10.3%
825004 1
 
3.4%
825013 1
 
3.4%
825014 1
 
3.4%
825000 1
 
3.4%
sysmanager 1
 
3.4%

Length

2023-12-12T08:37:28.408248image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T08:37:28.572877image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
825010 9
31.0%
825007 8
27.6%
825006 4
13.8%
825011 3
 
10.3%
825004 1
 
3.4%
825013 1
 
3.4%
825014 1
 
3.4%
825000 1
 
3.4%
sysmanager 1
 
3.4%

외부기관홈페이지
Text

CONSTANT  MISSING 

Distinct1
Distinct (%)100.0%
Missing28
Missing (%)96.6%
Memory size364.0 B
2023-12-12T08:37:28.754588image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length20
Median length20
Mean length20
Min length20

Characters and Unicode

Total characters20
Distinct characters13
Distinct categories2 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1 ?
Unique (%)100.0%

Sample

1st rowhttp://www.jeju.go.k
ValueCountFrequency (%)
http://www.jeju.go.k 1
100.0%
2023-12-12T08:37:29.046148image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
w 3
15.0%
. 3
15.0%
t 2
10.0%
/ 2
10.0%
j 2
10.0%
h 1
 
5.0%
p 1
 
5.0%
: 1
 
5.0%
e 1
 
5.0%
u 1
 
5.0%
Other values (3) 3
15.0%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 14
70.0%
Other Punctuation 6
30.0%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
w 3
21.4%
t 2
14.3%
j 2
14.3%
h 1
 
7.1%
p 1
 
7.1%
e 1
 
7.1%
u 1
 
7.1%
g 1
 
7.1%
o 1
 
7.1%
k 1
 
7.1%
Other Punctuation
ValueCountFrequency (%)
. 3
50.0%
/ 2
33.3%
: 1
 
16.7%

Most occurring scripts

ValueCountFrequency (%)
Latin 14
70.0%
Common 6
30.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
w 3
21.4%
t 2
14.3%
j 2
14.3%
h 1
 
7.1%
p 1
 
7.1%
e 1
 
7.1%
u 1
 
7.1%
g 1
 
7.1%
o 1
 
7.1%
k 1
 
7.1%
Common
ValueCountFrequency (%)
. 3
50.0%
/ 2
33.3%
: 1
 
16.7%

Most occurring blocks

ValueCountFrequency (%)
ASCII 20
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
w 3
15.0%
. 3
15.0%
t 2
10.0%
/ 2
10.0%
j 2
10.0%
h 1
 
5.0%
p 1
 
5.0%
: 1
 
5.0%
e 1
 
5.0%
u 1
 
5.0%
Other values (3) 3
15.0%

Interactions

2023-12-12T08:37:24.278950image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-12T08:37:29.159444image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
외부기관아이디기관구분기관명우편번호도로명주소1도로명주소2메모작성일작성자아이디수정일수정자아이디
외부기관아이디1.0000.0001.000NaN1.000NaN0.0001.0000.6441.0000.505
기관구분0.0001.0001.0000.0001.0000.000NaN0.0000.5320.0001.000
기관명1.0001.0001.0000.0001.0000.0000.0001.0001.0001.0001.000
우편번호NaN0.0000.0001.0000.0000.000NaN0.000NaNNaN0.000
도로명주소11.0001.0001.0000.0001.0000.000NaN1.0001.0001.0001.000
도로명주소2NaN0.0000.0000.0000.0001.000NaN0.000NaNNaN0.000
메모0.000NaN0.000NaNNaNNaN1.0000.0000.0000.0000.000
작성일1.0000.0001.0000.0001.0000.0000.0001.0000.0001.0000.000
작성자아이디0.6440.5321.000NaN1.000NaN0.0000.0001.0000.0000.997
수정일1.0000.0001.000NaN1.000NaN0.0001.0000.0001.0000.000
수정자아이디0.5051.0001.0000.0001.0000.0000.0000.0000.9970.0001.000
2023-12-12T08:37:29.321193image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
기관구분작성자아이디수정자아이디우편번호
기관구분1.0000.4510.8611.000
작성자아이디0.4511.0000.9081.000
수정자아이디0.8610.9081.0001.000
우편번호1.0001.0001.0001.000
2023-12-12T08:37:29.419832image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
외부기관아이디기관구분우편번호작성자아이디수정자아이디
외부기관아이디1.0000.0001.0000.3320.220
기관구분0.0001.0001.0000.4510.861
우편번호1.0001.0001.0001.0001.000
작성자아이디0.3320.4511.0001.0000.908
수정자아이디0.2200.8611.0000.9081.000

Missing values

2023-12-12T08:37:24.378746image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-12T08:37:24.522837image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Nullity matrix is a data-dense display which lets you quickly visually pick out patterns in data completion.
2023-12-12T08:37:24.660184image/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

외부기관아이디기관구분기관명우편번호도로명주소1도로명주소2메모사용여부작성일작성자아이디수정일수정자아이디외부기관홈페이지
0121150000올레고객센터<NA><NA><NA><NA>Y2018-01-078250102018-02-24825010<NA>
1141150000제주세계자연유산센터(거문오름탐방문의)<NA><NA><NA><NA>Y2018-01-128250072018-01-12825007<NA>
2105150000항림항 도선대합실<NA><NA><NA><NA>Y2017-11-018250042017-11-01825004<NA>
3201150000제주관광협회(하이제주)<NA><NA><NA><NA>Y2018-07-308250132018-07-30825013<NA>
4261150000산방산관리사무소<NA><NA><NA><NA>Y2018-12-308250102018-12-30825010<NA>
5381150000제주공항종합관광안내센터<NA><NA><NA><NA>Y2019-05-248250142019-05-24825014<NA>
6421150000비자림<NA><NA><NA><NA>Y2020-02-208250072020-02-20825007<NA>
7481150000삼양동유적지<NA><NA><NA><NA>Y2020-07-248250112020-07-24825011<NA>
8581150000감귤박람회<NA><NA><NA><NA>Y2021-11-078250062021-11-07825006<NA>
9622150000애월읍사무소<NA><NA><NA><NA>Y2022-06-138250102022-06-13825010<NA>
외부기관아이디기관구분기관명우편번호도로명주소1도로명주소2메모사용여부작성일작성자아이디수정일수정자아이디외부기관홈페이지
19321150000성산일출봉<NA><NA><NA><NA>Y2019-03-208250072019-03-20825007<NA>
20181150000제주목관아<NA><NA><NA><NA>Y2018-07-288250062018-07-28825006<NA>
21221150000제주실탄사격장<NA><NA><NA><NA>Y2018-09-048250062018-09-04825006<NA>
22501150000관광약자접근성안내센터<NA><NA><NA>1566-4669Y2020-07-318250022023-06-02825010<NA>
23541150000한라산국립공원<NA><NA><NA><NA>Y2021-04-258250072021-04-25825007<NA>
24601150000제주올레<NA><NA><NA><NA>Y2022-05-188250062022-05-18825006<NA>
25341150000성읍민속마을<NA><NA><NA><NA>Y2019-03-308250102019-03-30825010<NA>
26441150000관광진흥기금<NA><NA><NA><NA>Y2020-03-208250102020-03-20825010<NA>
27562150000추자면사무소<NA>추자도<NA><NA>Y2021-10-268250102021-10-26825010<NA>
28161150000한라산<NA><NA><NA><NA>Y2018-07-138250072018-07-13825007http://www.jeju.go.k