Overview

Dataset statistics

Number of variables11
Number of observations109
Missing cells21
Missing cells (%)1.8%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory9.7 KiB
Average record size in memory91.2 B

Variable types

Numeric1
Categorical4
Text5
Boolean1

Dataset

Description전북특별자치도 관광안내소 및 관광지, 관광특구 안내(명칭, 위치 등)2015년 10월 1일 기준으로 기록된 전북특별자치도에 소재하고 있는 관광지를 일컫는 이름
Author전북특별자치도
URLhttps://www.data.go.kr/data/3081273/fileData.do

Alerts

자료출처 has constant value ""Constant
공개여부 has constant value ""Constant
작성일 has constant value ""Constant
갱신주기(년) has constant value ""Constant
순번 is highly overall correlated with 시군명High correlation
시군명 is highly overall correlated with 순번High correlation
전화번호 has 21 (19.3%) missing valuesMissing
순번 has unique valuesUnique
명칭 has unique valuesUnique
구분 has unique valuesUnique

Reproduction

Analysis started2024-03-15 01:19:49.251115
Analysis finished2024-03-15 01:19:51.022111
Duration1.77 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

순번
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct109
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean55
Minimum1
Maximum109
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.1 KiB
2024-03-15T10:19:51.161660image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile6.4
Q128
median55
Q382
95-th percentile103.6
Maximum109
Range108
Interquartile range (IQR)54

Descriptive statistics

Standard deviation31.609598
Coefficient of variation (CV)0.57471996
Kurtosis-1.2
Mean55
Median Absolute Deviation (MAD)27
Skewness0
Sum5995
Variance999.16667
MonotonicityStrictly increasing
2024-03-15T10:19:51.658808image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 1
 
0.9%
70 1
 
0.9%
81 1
 
0.9%
80 1
 
0.9%
79 1
 
0.9%
78 1
 
0.9%
77 1
 
0.9%
76 1
 
0.9%
75 1
 
0.9%
74 1
 
0.9%
Other values (99) 99
90.8%
ValueCountFrequency (%)
1 1
0.9%
2 1
0.9%
3 1
0.9%
4 1
0.9%
5 1
0.9%
6 1
0.9%
7 1
0.9%
8 1
0.9%
9 1
0.9%
10 1
0.9%
ValueCountFrequency (%)
109 1
0.9%
108 1
0.9%
107 1
0.9%
106 1
0.9%
105 1
0.9%
104 1
0.9%
103 1
0.9%
102 1
0.9%
101 1
0.9%
100 1
0.9%

시군명
Categorical

HIGH CORRELATION 

Distinct14
Distinct (%)12.8%
Missing0
Missing (%)0.0%
Memory size1000.0 B
완주군
12 
전주시
10 
군산시
10 
남원시
10 
김제시
10 
Other values (9)
57 

Length

Max length3
Median length3
Mean length3
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
완주군 12
11.0%
전주시 10
9.2%
군산시 10
9.2%
남원시 10
9.2%
김제시 10
9.2%
정읍시 9
8.3%
고창군 9
8.3%
부안군 8
7.3%
익산시 6
 
5.5%
순창군 6
 
5.5%
Other values (4) 19
17.4%

Length

2024-03-15T10:19:52.278427image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
완주군 12
11.0%
전주시 10
9.2%
군산시 10
9.2%
남원시 10
9.2%
김제시 10
9.2%
정읍시 9
8.3%
고창군 9
8.3%
부안군 8
7.3%
익산시 6
 
5.5%
순창군 6
 
5.5%
Other values (4) 19
17.4%

명칭
Text

UNIQUE 

Distinct109
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size1000.0 B
2024-03-15T10:19:53.326550image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length14
Median length11
Mean length5.7981651
Min length2

Characters and Unicode

Total characters632
Distinct characters218
Distinct categories5 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique109 ?
Unique (%)100.0%

Sample

1st row전동성당
2nd row경기전
3rd row오목대
4th row최명희문학관
5th row전주시향교
ValueCountFrequency (%)
전동성당 1
 
0.8%
편백나무 1
 
0.8%
봉화산철쭉군락지 1
 
0.8%
머루와인동굴 1
 
0.8%
금강래프팅 1
 
0.8%
구천동계곡 1
 
0.8%
태권도원 1
 
0.8%
반디랜드 1
 
0.8%
메타세콰이어길 1
 
0.8%
용담댐 1
 
0.8%
Other values (108) 108
91.5%
2024-03-15T10:19:54.925890image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
원 20
 
3.2%
관 19
 
3.0%
산 19
 
3.0%
시 18
 
2.8%
마 15
 
2.4%
사 13
 
2.1%
전 11
 
1.7%
리 11
 
1.7%
지 11
 
1.7%
공 10
 
1.6%
Other values (208) 485
76.7%

Most occurring categories

ValueCountFrequency (%)
Other Letter 612
96.8%
Space Separator 9
 
1.4%
Decimal Number 7
 
1.1%
Close Punctuation 2
 
0.3%
Open Punctuation 2
 
0.3%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
원 20
 
3.3%
관 19
 
3.1%
산 19
 
3.1%
시 18
 
2.9%
마 15
 
2.5%
사 13
 
2.1%
전 11
 
1.8%
리 11
 
1.8%
지 11
 
1.8%
공 10
 
1.6%
Other values (201) 465
76.0%
Decimal Number
ValueCountFrequency (%)
1 3
42.9%
0 2
28.6%
9 1
 
14.3%
5 1
 
14.3%
Space Separator
ValueCountFrequency (%)
9
100.0%
Close Punctuation
ValueCountFrequency (%)
) 2
100.0%
Open Punctuation
ValueCountFrequency (%)
( 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 612
96.8%
Common 20
 
3.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
원 20
 
3.3%
관 19
 
3.1%
산 19
 
3.1%
시 18
 
2.9%
마 15
 
2.5%
사 13
 
2.1%
전 11
 
1.8%
리 11
 
1.8%
지 11
 
1.8%
공 10
 
1.6%
Other values (201) 465
76.0%
Common
ValueCountFrequency (%)
9
45.0%
1 3
 
15.0%
) 2
 
10.0%
( 2
 
10.0%
0 2
 
10.0%
9 1
 
5.0%
5 1
 
5.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 612
96.8%
ASCII 20
 
3.2%

Most frequent character per block

Hangul
ValueCountFrequency (%)
원 20
 
3.3%
관 19
 
3.1%
산 19
 
3.1%
시 18
 
2.9%
마 15
 
2.5%
사 13
 
2.1%
전 11
 
1.8%
리 11
 
1.8%
지 11
 
1.8%
공 10
 
1.6%
Other values (201) 465
76.0%
ASCII
ValueCountFrequency (%)
9
45.0%
1 3
 
15.0%
) 2
 
10.0%
( 2
 
10.0%
0 2
 
10.0%
9 1
 
5.0%
5 1
 
5.0%

구분
Text

UNIQUE 

Distinct109
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size1000.0 B
2024-03-15T10:19:56.144937image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length5
Median length4
Mean length3.5688073
Min length3

Characters and Unicode

Total characters389
Distinct characters34
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

Unique109 ?
Unique (%)100.0%

Sample

1st row전주시1
2nd row전주시2
3rd row전주시3
4th row전주시4
5th row전주시5
ValueCountFrequency (%)
전주시1 1
 
0.9%
완주1 1
 
0.9%
장수3 1
 
0.9%
장수2 1
 
0.9%
장수1 1
 
0.9%
무주5 1
 
0.9%
무주4 1
 
0.9%
무주3 1
 
0.9%
무주2 1
 
0.9%
무주1 1
 
0.9%
Other values (99) 99
90.8%
2024-03-15T10:19:57.800349image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
시 49
 
12.6%
주 27
 
6.9%
1 23
 
5.9%
산 16
 
4.1%
군 15
 
3.9%
2 15
 
3.9%
창 15
 
3.9%
3 14
 
3.6%
4 14
 
3.6%
5 13
 
3.3%
Other values (24) 188
48.3%

Most occurring categories

ValueCountFrequency (%)
Other Letter 272
69.9%
Decimal Number 117
30.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
시 49
18.0%
주 27
 
9.9%
산 16
 
5.9%
군 15
 
5.5%
창 15
 
5.5%
안 13
 
4.8%
완 12
 
4.4%
전 10
 
3.7%
남 10
 
3.7%
원 10
 
3.7%
Other values (14) 95
34.9%
Decimal Number
ValueCountFrequency (%)
1 23
19.7%
2 15
12.8%
3 14
12.0%
4 14
12.0%
5 13
11.1%
6 10
8.5%
7 8
 
6.8%
8 8
 
6.8%
0 6
 
5.1%
9 6
 
5.1%

Most occurring scripts

ValueCountFrequency (%)
Hangul 272
69.9%
Common 117
30.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
시 49
18.0%
주 27
 
9.9%
산 16
 
5.9%
군 15
 
5.5%
창 15
 
5.5%
안 13
 
4.8%
완 12
 
4.4%
전 10
 
3.7%
남 10
 
3.7%
원 10
 
3.7%
Other values (14) 95
34.9%
Common
ValueCountFrequency (%)
1 23
19.7%
2 15
12.8%
3 14
12.0%
4 14
12.0%
5 13
11.1%
6 10
8.5%
7 8
 
6.8%
8 8
 
6.8%
0 6
 
5.1%
9 6
 
5.1%

Most occurring blocks

ValueCountFrequency (%)
Hangul 272
69.9%
ASCII 117
30.1%

Most frequent character per block

Hangul
ValueCountFrequency (%)
시 49
18.0%
주 27
 
9.9%
산 16
 
5.9%
군 15
 
5.5%
창 15
 
5.5%
안 13
 
4.8%
완 12
 
4.4%
전 10
 
3.7%
남 10
 
3.7%
원 10
 
3.7%
Other values (14) 95
34.9%
ASCII
ValueCountFrequency (%)
1 23
19.7%
2 15
12.8%
3 14
12.0%
4 14
12.0%
5 13
11.1%
6 10
8.5%
7 8
 
6.8%
8 8
 
6.8%
0 6
 
5.1%
9 6
 
5.1%

도로명주소
Text

Distinct102
Distinct (%)93.6%
Missing0
Missing (%)0.0%
Memory size1000.0 B
2024-03-15T10:19:59.144771image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length20
Median length18
Mean length15.275229
Min length10

Characters and Unicode

Total characters1665
Distinct characters163
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

Unique97 ?
Unique (%)89.0%

Sample

1st row전주시 완산구 태조로 51
2nd row전주시 완산구 태조로 44
3rd row전주시 완산구 기린대로 55
4th row전주시 완산구 최명희길 29
5th row전주시 완산구 향교로 165
ValueCountFrequency (%)
완주군 12
 
2.9%
김제시 10
 
2.4%
남원시 10
 
2.4%
전주시 10
 
2.4%
군산시 10
 
2.4%
고창군 9
 
2.2%
정읍시 9
 
2.2%
부안군 8
 
1.9%
완산구 8
 
1.9%
익산시 6
 
1.4%
Other values (245) 326
78.0%
2024-03-15T10:20:01.861676image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
309
 
18.6%
면 69
 
4.1%
군 65
 
3.9%
로 65
 
3.9%
시 59
 
3.5%
4 53
 
3.2%
산 52
 
3.1%
1 50
 
3.0%
2 48
 
2.9%
길 44
 
2.6%
Other values (153) 851
51.1%

Most occurring categories

ValueCountFrequency (%)
Other Letter 999
60.0%
Decimal Number 330
 
19.8%
Space Separator 309
 
18.6%
Dash Punctuation 27
 
1.6%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
면 69
 
6.9%
군 65
 
6.5%
로 65
 
6.5%
시 59
 
5.9%
산 52
 
5.2%
길 44
 
4.4%
주 29
 
2.9%
안 22
 
2.2%
읍 22
 
2.2%
고 21
 
2.1%
Other values (141) 551
55.2%
Decimal Number
ValueCountFrequency (%)
4 53
16.1%
1 50
15.2%
2 48
14.5%
6 37
11.2%
5 32
9.7%
3 27
8.2%
0 24
7.3%
9 21
 
6.4%
8 19
 
5.8%
7 19
 
5.8%
Space Separator
ValueCountFrequency (%)
309
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 27
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 999
60.0%
Common 666
40.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
면 69
 
6.9%
군 65
 
6.5%
로 65
 
6.5%
시 59
 
5.9%
산 52
 
5.2%
길 44
 
4.4%
주 29
 
2.9%
안 22
 
2.2%
읍 22
 
2.2%
고 21
 
2.1%
Other values (141) 551
55.2%
Common
ValueCountFrequency (%)
309
46.4%
4 53
 
8.0%
1 50
 
7.5%
2 48
 
7.2%
6 37
 
5.6%
5 32
 
4.8%
- 27
 
4.1%
3 27
 
4.1%
0 24
 
3.6%
9 21
 
3.2%
Other values (2) 38
 
5.7%

Most occurring blocks

ValueCountFrequency (%)
Hangul 999
60.0%
ASCII 666
40.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
309
46.4%
4 53
 
8.0%
1 50
 
7.5%
2 48
 
7.2%
6 37
 
5.6%
5 32
 
4.8%
- 27
 
4.1%
3 27
 
4.1%
0 24
 
3.6%
9 21
 
3.2%
Other values (2) 38
 
5.7%
Hangul
ValueCountFrequency (%)
면 69
 
6.9%
군 65
 
6.5%
로 65
 
6.5%
시 59
 
5.9%
산 52
 
5.2%
길 44
 
4.4%
주 29
 
2.9%
안 22
 
2.2%
읍 22
 
2.2%
고 21
 
2.1%
Other values (141) 551
55.2%

전화번호
Text

MISSING 

Distinct83
Distinct (%)94.3%
Missing21
Missing (%)19.3%
Memory size1000.0 B
2024-03-15T10:20:02.999373image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length13
Median length12
Mean length11.977273
Min length9

Characters and Unicode

Total characters1054
Distinct characters11
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique78 ?
Unique (%)88.6%

Sample

1st row063-284-3222
2nd row063-281-2790
3rd row063-284-0570
4th row063-288-4544
5th row063-280-7000
ValueCountFrequency (%)
063-540-4985 2
 
2.3%
063-620-6788 2
 
2.3%
063-350-2444 2
 
2.3%
063-584-6822 2
 
2.3%
063-859-4631 2
 
2.3%
063-643-2300 1
 
1.1%
063-261-7373 1
 
1.1%
063-433-1666 1
 
1.1%
063-322-4720 1
 
1.1%
063-322-1077 1
 
1.1%
Other values (73) 73
83.0%
2024-03-15T10:20:04.503079image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
- 175
16.6%
0 155
14.7%
6 151
14.3%
3 150
14.2%
4 82
7.8%
5 80
7.6%
2 73
6.9%
8 60
 
5.7%
7 47
 
4.5%
1 42
 
4.0%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 879
83.4%
Dash Punctuation 175
 
16.6%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 155
17.6%
6 151
17.2%
3 150
17.1%
4 82
9.3%
5 80
9.1%
2 73
8.3%
8 60
 
6.8%
7 47
 
5.3%
1 42
 
4.8%
9 39
 
4.4%
Dash Punctuation
ValueCountFrequency (%)
- 175
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 1054
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
- 175
16.6%
0 155
14.7%
6 151
14.3%
3 150
14.2%
4 82
7.8%
5 80
7.6%
2 73
6.9%
8 60
 
5.7%
7 47
 
4.5%
1 42
 
4.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1054
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
- 175
16.6%
0 155
14.7%
6 151
14.3%
3 150
14.2%
4 82
7.8%
5 80
7.6%
2 73
6.9%
8 60
 
5.7%
7 47
 
4.5%
1 42
 
4.0%

소개
Text

Distinct108
Distinct (%)99.1%
Missing0
Missing (%)0.0%
Memory size1000.0 B
2024-03-15T10:20:06.311580image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length46
Median length33
Mean length24.93578
Min length1

Characters and Unicode

Total characters2718
Distinct characters425
Distinct categories8 ?
Distinct scripts3 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique107 ?
Unique (%)98.2%

Sample

1st row천주교 최초 순교자 터, 국내에서 가장 아름다운 성당으로 이름 난 곳
2nd row조선 왕조의 발상지이자 태조의 본향, 태조 이성계의 어진을 봉안한 경기전
3rd row한옥마을을 가장 잘 담을 수 있는 포토 존
4th row혼불의 저자 최명희씨의 문학관
5th row조선시대 유학의 기틀을 마련한 선비들의 자취 고스란히 묻은 곳
ValueCountFrequency (%)
곳 16
 
2.3%
국내 7
 
1.0%
있는 7
 
1.0%
가장 5
 
0.7%
위해 4
 
0.6%
사이로 4
 
0.6%
우리나라 4
 
0.6%
공원 4
 
0.6%
중 4
 
0.6%
마련한 4
 
0.6%
Other values (580) 637
91.5%
2024-03-15T10:20:07.836933image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
587
 
21.6%
이 59
 
2.2%
의 56
 
2.1%
한 39
 
1.4%
을 29
 
1.1%
지 29
 
1.1%
로 29
 
1.1%
는 28
 
1.0%
장 25
 
0.9%
사 25
 
0.9%
Other values (415) 1812
66.7%

Most occurring categories

ValueCountFrequency (%)
Other Letter 2039
75.0%
Space Separator 587
 
21.6%
Decimal Number 53
 
1.9%
Other Punctuation 27
 
1.0%
Lowercase Letter 6
 
0.2%
Dash Punctuation 2
 
0.1%
Open Punctuation 2
 
0.1%
Close Punctuation 2
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
이 59
 
2.9%
의 56
 
2.7%
한 39
 
1.9%
을 29
 
1.4%
지 29
 
1.4%
로 29
 
1.4%
는 28
 
1.4%
장 25
 
1.2%
사 25
 
1.2%
대 24
 
1.2%
Other values (394) 1696
83.2%
Decimal Number
ValueCountFrequency (%)
0 11
20.8%
1 8
15.1%
6 6
11.3%
9 6
11.3%
8 6
11.3%
3 5
9.4%
4 3
 
5.7%
5 3
 
5.7%
7 3
 
5.7%
2 2
 
3.8%
Lowercase Letter
ValueCountFrequency (%)
m 3
50.0%
a 1
 
16.7%
h 1
 
16.7%
c 1
 
16.7%
Other Punctuation
ValueCountFrequency (%)
, 23
85.2%
. 3
 
11.1%
& 1
 
3.7%
Space Separator
ValueCountFrequency (%)
587
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 2
100.0%
Open Punctuation
ValueCountFrequency (%)
( 2
100.0%
Close Punctuation
ValueCountFrequency (%)
) 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 2039
75.0%
Common 673
 
24.8%
Latin 6
 
0.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
이 59
 
2.9%
의 56
 
2.7%
한 39
 
1.9%
을 29
 
1.4%
지 29
 
1.4%
로 29
 
1.4%
는 28
 
1.4%
장 25
 
1.2%
사 25
 
1.2%
대 24
 
1.2%
Other values (394) 1696
83.2%
Common
ValueCountFrequency (%)
587
87.2%
, 23
 
3.4%
0 11
 
1.6%
1 8
 
1.2%
6 6
 
0.9%
9 6
 
0.9%
8 6
 
0.9%
3 5
 
0.7%
4 3
 
0.4%
5 3
 
0.4%
Other values (7) 15
 
2.2%
Latin
ValueCountFrequency (%)
m 3
50.0%
a 1
 
16.7%
h 1
 
16.7%
c 1
 
16.7%

Most occurring blocks

ValueCountFrequency (%)
Hangul 2038
75.0%
ASCII 679
 
25.0%
Compat Jamo 1
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
587
86.5%
, 23
 
3.4%
0 11
 
1.6%
1 8
 
1.2%
6 6
 
0.9%
9 6
 
0.9%
8 6
 
0.9%
3 5
 
0.7%
4 3
 
0.4%
m 3
 
0.4%
Other values (11) 21
 
3.1%
Hangul
ValueCountFrequency (%)
이 59
 
2.9%
의 56
 
2.7%
한 39
 
1.9%
을 29
 
1.4%
지 29
 
1.4%
로 29
 
1.4%
는 28
 
1.4%
장 25
 
1.2%
사 25
 
1.2%
대 24
 
1.2%
Other values (393) 1695
83.2%
Compat Jamo
ValueCountFrequency (%)
ㄱ 1
100.0%

자료출처
Categorical

CONSTANT 

Distinct1
Distinct (%)0.9%
Missing0
Missing (%)0.0%
Memory size1000.0 B
관광총괄과
109 

Length

Max length5
Median length5
Mean length5
Min length5

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
관광총괄과 109
100.0%

Length

2024-03-15T10:20:08.149749image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-15T10:20:08.471458image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
관광총괄과 109
100.0%

공개여부
Boolean

CONSTANT 

Distinct1
Distinct (%)0.9%
Missing0
Missing (%)0.0%
Memory size237.0 B
True
109 
ValueCountFrequency (%)
True 109
100.0%
2024-03-15T10:20:08.722391image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

작성일
Categorical

CONSTANT 

Distinct1
Distinct (%)0.9%
Missing0
Missing (%)0.0%
Memory size1000.0 B
2015-10-01
109 

Length

Max length10
Median length10
Mean length10
Min length10

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2015-10-01
2nd row2015-10-01
3rd row2015-10-01
4th row2015-10-01
5th row2015-10-01

Common Values

ValueCountFrequency (%)
2015-10-01 109
100.0%

Length

2024-03-15T10:20:09.033055image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-15T10:20:09.332761image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2015-10-01 109
100.0%

갱신주기(년)
Categorical

CONSTANT 

Distinct1
Distinct (%)0.9%
Missing0
Missing (%)0.0%
Memory size1000.0 B
1
109 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row1
2nd row1
3rd row1
4th row1
5th row1

Common Values

ValueCountFrequency (%)
1 109
100.0%

Length

2024-03-15T10:20:09.660278image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-15T10:20:09.958421image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
1 109
100.0%

Interactions

2024-03-15T10:19:50.088221image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-03-15T10:20:10.130544image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
순번시군명전화번호
순번1.0000.9610.992
시군명0.9611.0000.995
전화번호0.9920.9951.000
2024-03-15T10:20:10.381018image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
순번시군명
순번1.0000.828
시군명0.8281.000

Missing values

2024-03-15T10:19:50.438326image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-03-15T10:19:50.919363image/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.

Sample

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