Overview

Dataset statistics

Number of variables12
Number of observations21
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory2.2 KiB
Average record size in memory106.3 B

Variable types

Numeric3
Text5
Categorical4

Alerts

자료출처 has constant value ""Constant
공개여부 has constant value ""Constant
작성일 has constant value ""Constant
갱신주기 has constant value ""Constant
순번 is highly overall correlated with 스크린수High correlation
스크린수 is highly overall correlated with 순번 and 1 other fieldsHigh correlation
좌석 is highly overall correlated with 스크린수High correlation
순번 has unique valuesUnique
영화관명 has unique valuesUnique
스크린수 has 1 (4.8%) zerosZeros

Reproduction

Analysis started2024-03-14 00:48:08.356354
Analysis finished2024-03-14 00:48:09.422586
Duration1.07 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

순번
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct21
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean11
Minimum1
Maximum21
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size321.0 B
2024-03-14T09:48:09.470269image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile2
Q16
median11
Q316
95-th percentile20
Maximum21
Range20
Interquartile range (IQR)10

Descriptive statistics

Standard deviation6.2048368
Coefficient of variation (CV)0.56407607
Kurtosis-1.2
Mean11
Median Absolute Deviation (MAD)5
Skewness0
Sum231
Variance38.5
MonotonicityStrictly increasing
2024-03-14T09:48:09.590256image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=21)
ValueCountFrequency (%)
1 1
 
4.8%
2 1
 
4.8%
21 1
 
4.8%
20 1
 
4.8%
19 1
 
4.8%
18 1
 
4.8%
17 1
 
4.8%
16 1
 
4.8%
15 1
 
4.8%
14 1
 
4.8%
Other values (11) 11
52.4%
ValueCountFrequency (%)
1 1
4.8%
2 1
4.8%
3 1
4.8%
4 1
4.8%
5 1
4.8%
6 1
4.8%
7 1
4.8%
8 1
4.8%
9 1
4.8%
10 1
4.8%
ValueCountFrequency (%)
21 1
4.8%
20 1
4.8%
19 1
4.8%
18 1
4.8%
17 1
4.8%
16 1
4.8%
15 1
4.8%
14 1
4.8%
13 1
4.8%
12 1
4.8%

시군명
Text

Distinct12
Distinct (%)57.1%
Missing0
Missing (%)0.0%
Memory size300.0 B
2024-03-14T09:48:09.705076image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length3
Median length3
Mean length3
Min length3

Characters and Unicode

Total characters63
Distinct characters22
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

Unique10 ?
Unique (%)47.6%

Sample

1st row전주시
2nd row전주시
3rd row전주시
4th row전주시
5th row전주시
ValueCountFrequency (%)
전주시 9
42.9%
군산시 2
 
9.5%
익산시 1
 
4.8%
정읍시 1
 
4.8%
남원시 1
 
4.8%
김제시 1
 
4.8%
완주군 1
 
4.8%
무주군 1
 
4.8%
장수군 1
 
4.8%
임실군 1
 
4.8%
Other values (2) 2
 
9.5%
2024-03-14T09:48:09.908843image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
시 15
23.8%
주 11
17.5%
전 9
14.3%
군 8
12.7%
산 3
 
4.8%
무 1
 
1.6%
부 1
 
1.6%
창 1
 
1.6%
고 1
 
1.6%
실 1
 
1.6%
Other values (12) 12
19.0%

Most occurring categories

ValueCountFrequency (%)
Other Letter 63
100.0%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
시 15
23.8%
주 11
17.5%
전 9
14.3%
군 8
12.7%
산 3
 
4.8%
무 1
 
1.6%
부 1
 
1.6%
창 1
 
1.6%
고 1
 
1.6%
실 1
 
1.6%
Other values (12) 12
19.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 63
100.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
시 15
23.8%
주 11
17.5%
전 9
14.3%
군 8
12.7%
산 3
 
4.8%
무 1
 
1.6%
부 1
 
1.6%
창 1
 
1.6%
고 1
 
1.6%
실 1
 
1.6%
Other values (12) 12
19.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 63
100.0%

Most frequent character per block

Hangul
ValueCountFrequency (%)
시 15
23.8%
주 11
17.5%
전 9
14.3%
군 8
12.7%
산 3
 
4.8%
무 1
 
1.6%
부 1
 
1.6%
창 1
 
1.6%
고 1
 
1.6%
실 1
 
1.6%
Other values (12) 12
19.0%

영화관명
Text

UNIQUE 

Distinct21
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size300.0 B
2024-03-14T09:48:10.056395image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length14
Median length12
Mean length8.8095238
Min length4

Characters and Unicode

Total characters185
Distinct characters54
Distinct categories5 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique21 ?
Unique (%)100.0%

Sample

1st row롯데시네마 전주
2nd row롯데시네마 평화점
3rd row메가박스 전주
4th row씨너스 송천
5th row전주시네마타운
ValueCountFrequency (%)
cgv 4
 
12.9%
롯데시네마 3
 
9.7%
전주 3
 
9.7%
군산 2
 
6.5%
메가박스 2
 
6.5%
씨너스 1
 
3.2%
지평선 1
 
3.2%
동리시네마(작은영화관 1
 
3.2%
작은별영화관(작은영화관 1
 
3.2%
한누리시네마(작은영화관 1
 
3.2%
Other values (12) 12
38.7%
2024-03-14T09:48:10.464243image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
화 13
 
7.0%
관 12
 
6.5%
영 12
 
6.5%
10
 
5.4%
마 9
 
4.9%
은 8
 
4.3%
시 8
 
4.3%
네 8
 
4.3%
작 8
 
4.3%
주 7
 
3.8%
Other values (44) 90
48.6%

Most occurring categories

ValueCountFrequency (%)
Other Letter 146
78.9%
Uppercase Letter 15
 
8.1%
Space Separator 10
 
5.4%
Open Punctuation 7
 
3.8%
Close Punctuation 7
 
3.8%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
화 13
 
8.9%
관 12
 
8.2%
영 12
 
8.2%
마 9
 
6.2%
은 8
 
5.5%
시 8
 
5.5%
네 8
 
5.5%
작 8
 
5.5%
주 7
 
4.8%
전 6
 
4.1%
Other values (38) 55
37.7%
Uppercase Letter
ValueCountFrequency (%)
V 5
33.3%
G 5
33.3%
C 5
33.3%
Space Separator
ValueCountFrequency (%)
10
100.0%
Open Punctuation
ValueCountFrequency (%)
( 7
100.0%
Close Punctuation
ValueCountFrequency (%)
) 7
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 146
78.9%
Common 24
 
13.0%
Latin 15
 
8.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
화 13
 
8.9%
관 12
 
8.2%
영 12
 
8.2%
마 9
 
6.2%
은 8
 
5.5%
시 8
 
5.5%
네 8
 
5.5%
작 8
 
5.5%
주 7
 
4.8%
전 6
 
4.1%
Other values (38) 55
37.7%
Common
ValueCountFrequency (%)
10
41.7%
( 7
29.2%
) 7
29.2%
Latin
ValueCountFrequency (%)
V 5
33.3%
G 5
33.3%
C 5
33.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 146
78.9%
ASCII 39
 
21.1%

Most frequent character per block

Hangul
ValueCountFrequency (%)
화 13
 
8.9%
관 12
 
8.2%
영 12
 
8.2%
마 9
 
6.2%
은 8
 
5.5%
시 8
 
5.5%
네 8
 
5.5%
작 8
 
5.5%
주 7
 
4.8%
전 6
 
4.1%
Other values (38) 55
37.7%
ASCII
ValueCountFrequency (%)
10
25.6%
( 7
17.9%
) 7
17.9%
V 5
12.8%
G 5
12.8%
C 5
12.8%

스크린수
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct10
Distinct (%)47.6%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean4.5714286
Minimum0
Maximum10
Zeros1
Zeros (%)4.8%
Negative0
Negative (%)0.0%
Memory size321.0 B
2024-03-14T09:48:10.571335image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile1
Q12
median4
Q37
95-th percentile9
Maximum10
Range10
Interquartile range (IQR)5

Descriptive statistics

Standard deviation2.959247
Coefficient of variation (CV)0.64733528
Kurtosis-1.2647062
Mean4.5714286
Median Absolute Deviation (MAD)2
Skewness0.24702355
Sum96
Variance8.7571429
MonotonicityNot monotonic
2024-03-14T09:48:10.677052image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=10)
ValueCountFrequency (%)
2 7
33.3%
7 3
14.3%
8 2
 
9.5%
6 2
 
9.5%
4 2
 
9.5%
10 1
 
4.8%
1 1
 
4.8%
0 1
 
4.8%
5 1
 
4.8%
9 1
 
4.8%
ValueCountFrequency (%)
0 1
 
4.8%
1 1
 
4.8%
2 7
33.3%
4 2
 
9.5%
5 1
 
4.8%
6 2
 
9.5%
7 3
14.3%
8 2
 
9.5%
9 1
 
4.8%
10 1
 
4.8%
ValueCountFrequency (%)
10 1
 
4.8%
9 1
 
4.8%
8 2
 
9.5%
7 3
14.3%
6 2
 
9.5%
5 1
 
4.8%
4 2
 
9.5%
2 7
33.3%
1 1
 
4.8%
0 1
 
4.8%

좌석
Real number (ℝ)

HIGH CORRELATION 

Distinct11
Distinct (%)52.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean185.52381
Minimum1
Maximum975
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size321.0 B
2024-03-14T09:48:10.807055image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q11
median90
Q399
95-th percentile922
Maximum975
Range974
Interquartile range (IQR)98

Descriptive statistics

Standard deviation304.16782
Coefficient of variation (CV)1.6395083
Kurtosis2.3903397
Mean185.52381
Median Absolute Deviation (MAD)89
Skewness1.8983864
Sum3896
Variance92518.062
MonotonicityNot monotonic
2024-03-14T09:48:10.898443image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=11)
ValueCountFrequency (%)
1 8
38.1%
98 2
 
9.5%
99 2
 
9.5%
90 2
 
9.5%
922 1
 
4.8%
50 1
 
4.8%
975 1
 
4.8%
565 1
 
4.8%
615 1
 
4.8%
94 1
 
4.8%
ValueCountFrequency (%)
1 8
38.1%
50 1
 
4.8%
90 2
 
9.5%
93 1
 
4.8%
94 1
 
4.8%
98 2
 
9.5%
99 2
 
9.5%
565 1
 
4.8%
615 1
 
4.8%
922 1
 
4.8%
ValueCountFrequency (%)
975 1
4.8%
922 1
4.8%
615 1
4.8%
565 1
4.8%
99 2
9.5%
98 2
9.5%
94 1
4.8%
93 1
4.8%
90 2
9.5%
50 1
4.8%

도로명주소
Text

Distinct20
Distinct (%)95.2%
Missing0
Missing (%)0.0%
Memory size300.0 B
2024-03-14T09:48:11.057973image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length20
Median length17
Mean length15.142857
Min length10

Characters and Unicode

Total characters318
Distinct characters73
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

Unique19 ?
Unique (%)90.5%

Sample

1st row전주시 완산구 온고을로 2
2nd row전주시 완산구 백제대로 10
3rd row전주시 완산구 전주객사4길 74-10
4th row전주시 덕진구 동부대로 1215
5th row전주시 완산구 전주객사3길 67
ValueCountFrequency (%)
전주시 9
 
11.8%
완산구 8
 
10.5%
전주객사3길 3
 
3.9%
군산시 2
 
2.6%
67 2
 
2.6%
예술회관길 1
 
1.3%
부안읍 1
 
1.3%
둔산3로 1
 
1.3%
94 1
 
1.3%
무주군 1
 
1.3%
Other values (47) 47
61.8%
2024-03-14T09:48:11.361604image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
55
 
17.3%
주 17
 
5.3%
시 15
 
4.7%
전 14
 
4.4%
2 14
 
4.4%
1 13
 
4.1%
로 12
 
3.8%
산 12
 
3.8%
3 10
 
3.1%
완 9
 
2.8%
Other values (63) 147
46.2%

Most occurring categories

ValueCountFrequency (%)
Other Letter 190
59.7%
Decimal Number 68
 
21.4%
Space Separator 55
 
17.3%
Dash Punctuation 5
 
1.6%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
주 17
 
8.9%
시 15
 
7.9%
전 14
 
7.4%
로 12
 
6.3%
산 12
 
6.3%
완 9
 
4.7%
구 9
 
4.7%
길 9
 
4.7%
군 8
 
4.2%
읍 7
 
3.7%
Other values (51) 78
41.1%
Decimal Number
ValueCountFrequency (%)
2 14
20.6%
1 13
19.1%
3 10
14.7%
6 7
10.3%
0 6
8.8%
7 6
8.8%
4 5
 
7.4%
5 4
 
5.9%
9 2
 
2.9%
8 1
 
1.5%
Space Separator
ValueCountFrequency (%)
55
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 5
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 190
59.7%
Common 128
40.3%

Most frequent character per script

Hangul
ValueCountFrequency (%)
주 17
 
8.9%
시 15
 
7.9%
전 14
 
7.4%
로 12
 
6.3%
산 12
 
6.3%
완 9
 
4.7%
구 9
 
4.7%
길 9
 
4.7%
군 8
 
4.2%
읍 7
 
3.7%
Other values (51) 78
41.1%
Common
ValueCountFrequency (%)
55
43.0%
2 14
 
10.9%
1 13
 
10.2%
3 10
 
7.8%
6 7
 
5.5%
0 6
 
4.7%
7 6
 
4.7%
4 5
 
3.9%
- 5
 
3.9%
5 4
 
3.1%
Other values (2) 3
 
2.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 190
59.7%
ASCII 128
40.3%

Most frequent character per block

ASCII
ValueCountFrequency (%)
55
43.0%
2 14
 
10.9%
1 13
 
10.2%
3 10
 
7.8%
6 7
 
5.5%
0 6
 
4.7%
7 6
 
4.7%
4 5
 
3.9%
- 5
 
3.9%
5 4
 
3.1%
Other values (2) 3
 
2.3%
Hangul
ValueCountFrequency (%)
주 17
 
8.9%
시 15
 
7.9%
전 14
 
7.4%
로 12
 
6.3%
산 12
 
6.3%
완 9
 
4.7%
구 9
 
4.7%
길 9
 
4.7%
군 8
 
4.2%
읍 7
 
3.7%
Other values (51) 78
41.1%

지번주소
Text

Distinct20
Distinct (%)95.2%
Missing0
Missing (%)0.0%
Memory size300.0 B
2024-03-14T09:48:11.545136image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length20
Median length19
Mean length15.666667
Min length12

Characters and Unicode

Total characters329
Distinct characters65
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

Unique19 ?
Unique (%)90.5%

Sample

1st row전주시 완산구 서신동 971
2nd row전주시 완산구 평화동1가 604-1
3rd row전주시 완산구 고사동 181
4th row전주시 덕진구 송천동2가 661-15
5th row전주시 완산구 고사동 340-3
ValueCountFrequency (%)
전주시 9
 
11.4%
완산구 8
 
10.1%
고사동 5
 
6.3%
군산시 2
 
2.5%
나운동 2
 
2.5%
340-3 2
 
2.5%
부안읍 1
 
1.3%
부안군 1
 
1.3%
881 1
 
1.3%
무주군 1
 
1.3%
Other values (47) 47
59.5%
2024-03-14T09:48:11.838267image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
58
17.6%
1 20
 
6.1%
4 17
 
5.2%
동 16
 
4.9%
산 16
 
4.9%
시 15
 
4.6%
- 14
 
4.3%
주 12
 
3.6%
전 9
 
2.7%
구 9
 
2.7%
Other values (55) 143
43.5%

Most occurring categories

ValueCountFrequency (%)
Other Letter 175
53.2%
Decimal Number 82
24.9%
Space Separator 58
 
17.6%
Dash Punctuation 14
 
4.3%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
동 16
 
9.1%
산 16
 
9.1%
시 15
 
8.6%
주 12
 
6.9%
전 9
 
5.1%
구 9
 
5.1%
완 9
 
5.1%
군 8
 
4.6%
읍 8
 
4.6%
고 7
 
4.0%
Other values (43) 66
37.7%
Decimal Number
ValueCountFrequency (%)
1 20
24.4%
4 17
20.7%
5 8
 
9.8%
2 8
 
9.8%
3 7
 
8.5%
6 5
 
6.1%
9 5
 
6.1%
7 5
 
6.1%
8 4
 
4.9%
0 3
 
3.7%
Space Separator
ValueCountFrequency (%)
58
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 14
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 175
53.2%
Common 154
46.8%

Most frequent character per script

Hangul
ValueCountFrequency (%)
동 16
 
9.1%
산 16
 
9.1%
시 15
 
8.6%
주 12
 
6.9%
전 9
 
5.1%
구 9
 
5.1%
완 9
 
5.1%
군 8
 
4.6%
읍 8
 
4.6%
고 7
 
4.0%
Other values (43) 66
37.7%
Common
ValueCountFrequency (%)
58
37.7%
1 20
 
13.0%
4 17
 
11.0%
- 14
 
9.1%
5 8
 
5.2%
2 8
 
5.2%
3 7
 
4.5%
6 5
 
3.2%
9 5
 
3.2%
7 5
 
3.2%
Other values (2) 7
 
4.5%

Most occurring blocks

ValueCountFrequency (%)
Hangul 175
53.2%
ASCII 154
46.8%

Most frequent character per block

ASCII
ValueCountFrequency (%)
58
37.7%
1 20
 
13.0%
4 17
 
11.0%
- 14
 
9.1%
5 8
 
5.2%
2 8
 
5.2%
3 7
 
4.5%
6 5
 
3.2%
9 5
 
3.2%
7 5
 
3.2%
Other values (2) 7
 
4.5%
Hangul
ValueCountFrequency (%)
동 16
 
9.1%
산 16
 
9.1%
시 15
 
8.6%
주 12
 
6.9%
전 9
 
5.1%
구 9
 
5.1%
완 9
 
5.1%
군 8
 
4.6%
읍 8
 
4.6%
고 7
 
4.0%
Other values (43) 66
37.7%

전화번호
Text

Distinct13
Distinct (%)61.9%
Missing0
Missing (%)0.0%
Memory size300.0 B
2024-03-14T09:48:11.968622image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length12
Median length9
Mean length10.428571
Min length9

Characters and Unicode

Total characters219
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

Unique10 ?
Unique (%)47.6%

Sample

1st row1544-8855
2nd row1544-8855
3rd row1544-0070
4th row1544-0070
5th row063-283-7722
ValueCountFrequency (%)
1544-1122 5
23.8%
1544-8855 3
14.3%
1544-0070 3
14.3%
063-283-7722 1
 
4.8%
063-231-3377 1
 
4.8%
063-231-0100 1
 
4.8%
063-547-5801 1
 
4.8%
063-263-9012 1
 
4.8%
063-322-7053 1
 
4.8%
063-352-7050 1
 
4.8%
Other values (3) 3
14.3%
2024-03-14T09:48:12.192044image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
- 31
14.2%
0 30
13.7%
1 28
12.8%
4 27
12.3%
5 25
11.4%
2 23
10.5%
3 20
9.1%
6 13
5.9%
7 11
 
5.0%
8 10
 
4.6%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 188
85.8%
Dash Punctuation 31
 
14.2%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 30
16.0%
1 28
14.9%
4 27
14.4%
5 25
13.3%
2 23
12.2%
3 20
10.6%
6 13
6.9%
7 11
 
5.9%
8 10
 
5.3%
9 1
 
0.5%
Dash Punctuation
ValueCountFrequency (%)
- 31
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 219
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
- 31
14.2%
0 30
13.7%
1 28
12.8%
4 27
12.3%
5 25
11.4%
2 23
10.5%
3 20
9.1%
6 13
5.9%
7 11
 
5.0%
8 10
 
4.6%

Most occurring blocks

ValueCountFrequency (%)
ASCII 219
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
- 31
14.2%
0 30
13.7%
1 28
12.8%
4 27
12.3%
5 25
11.4%
2 23
10.5%
3 20
9.1%
6 13
5.9%
7 11
 
5.0%
8 10
 
4.6%

자료출처
Categorical

CONSTANT 

Distinct1
Distinct (%)4.8%
Missing0
Missing (%)0.0%
Memory size300.0 B
문화예술과
21 

Length

Max length5
Median length5
Mean length5
Min length5

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
문화예술과 21
100.0%

Length

2024-03-14T09:48:12.298291image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-14T09:48:12.405558image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
문화예술과 21
100.0%

공개여부
Categorical

CONSTANT 

Distinct1
Distinct (%)4.8%
Missing0
Missing (%)0.0%
Memory size300.0 B
공개
21 

Length

Max length2
Median length2
Mean length2
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
공개 21
100.0%

Length

2024-03-14T09:48:12.555996image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-14T09:48:12.663876image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
공개 21
100.0%

작성일
Categorical

CONSTANT 

Distinct1
Distinct (%)4.8%
Missing0
Missing (%)0.0%
Memory size300.0 B
2015.1
21 

Length

Max length6
Median length6
Mean length6
Min length6

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2015.1
2nd row2015.1
3rd row2015.1
4th row2015.1
5th row2015.1

Common Values

ValueCountFrequency (%)
2015.1 21
100.0%

Length

2024-03-14T09:48:12.740791image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-14T09:48:12.815450image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2015.1 21
100.0%

갱신주기
Categorical

CONSTANT 

Distinct1
Distinct (%)4.8%
Missing0
Missing (%)0.0%
Memory size300.0 B
1년
21 

Length

Max length2
Median length2
Mean length2
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row1년
2nd row1년
3rd row1년
4th row1년
5th row1년

Common Values

ValueCountFrequency (%)
1년 21
100.0%

Length

2024-03-14T09:48:13.094313image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-14T09:48:13.162652image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
1년 21
100.0%

Interactions

2024-03-14T09:48:09.040451image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T09:48:08.638706image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T09:48:08.833354image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T09:48:09.108402image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T09:48:08.708715image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T09:48:08.904058image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T09:48:09.166842image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T09:48:08.771146image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T09:48:08.974482image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-03-14T09:48:13.217752image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
순번시군명영화관명스크린수좌석도로명주소지번주소전화번호
순번1.0000.4931.0000.7650.3641.0001.0000.750
시군명0.4931.0001.0000.0000.8941.0001.0000.859
영화관명1.0001.0001.0001.0001.0001.0001.0001.000
스크린수0.7650.0001.0001.0000.5920.9110.9110.000
좌석0.3640.8941.0000.5921.0001.0001.0000.000
도로명주소1.0001.0001.0000.9111.0001.0001.0000.938
지번주소1.0001.0001.0000.9111.0001.0001.0000.938
전화번호0.7500.8591.0000.0000.0000.9380.9381.000
2024-03-14T09:48:13.320082image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
순번스크린수좌석
순번1.000-0.6250.402
스크린수-0.6251.000-0.551
좌석0.402-0.5511.000

Missing values

2024-03-14T09:48:09.255812image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-03-14T09:48:09.375786image/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

순번시군명영화관명스크린수좌석도로명주소지번주소전화번호자료출처공개여부작성일갱신주기
01전주시롯데시네마 전주81전주시 완산구 온고을로 2전주시 완산구 서신동 9711544-8855문화예술과공개2015.11년
12전주시롯데시네마 평화점6922전주시 완산구 백제대로 10전주시 완산구 평화동1가 604-11544-8855문화예술과공개2015.11년
23전주시메가박스 전주101전주시 완산구 전주객사4길 74-10전주시 완산구 고사동 1811544-0070문화예술과공개2015.11년
34전주시씨너스 송천81전주시 덕진구 동부대로 1215전주시 덕진구 송천동2가 661-151544-0070문화예술과공개2015.11년
45전주시전주시네마타운71전주시 완산구 전주객사3길 67전주시 완산구 고사동 340-3063-283-7722문화예술과공개2015.11년
56전주시CGV 전주61전주시 완산구 전주객사3길 67전주시 완산구 고사동 340-31544-1122문화예술과공개2015.11년
67전주시전주디지털독립영화관198전주시 완산구 전주객사3길 22전주시 완산구 고사동 429-5063-231-3377문화예술과공개2015.11년
78전주시CGV효자동71전주시 완산구 용머리로45전주시 완산구 효자동1가 4341544-1122문화예술과공개2015.11년
89전주시전주영화도서관050전주시 완산구 전주객사2길 28-27전주시 완산구 고사동 462-4063-231-0100문화예술과공개2015.11년
910군산시롯데시네마 군산5975군산시 백토로 166군산시 나운동 124-41544-8855문화예술과공개2015.11년
순번시군명영화관명스크린수좌석도로명주소지번주소전화번호자료출처공개여부작성일갱신주기
1112익산시CGV 익산91익산시 무왕로 1052익산시 영등동 149-11544-1122문화예술과공개2015.11년
1213정읍시CGV 정읍4565정읍시 중앙1길 1정읍시 수성동 525-11544-1122문화예술과공개2015.11년
1314남원시메가박스4615남원시 향단로 26남원시 쌍교동 82-11544-0070문화예술과공개2015.11년
1415김제시지평선 시네마(작은영화관)299김제시 도작로 224-32김제시 검산동 산 62-1063-547-5801문화예술과공개2015.11년
1516완주군휴시네마(작은영화관)290완주군 봉동읍 둔산3로 94완주군 봉동읍 둔산리 881063-263-9012문화예술과공개2015.11년
1617무주군무주산골영화관(작은영화관)298무주군 무주읍 한풍루로326-17무주군 무주읍 당산리 1199-3063-322-7053문화예술과공개2015.11년
1718장수군한누리시네마(작은영화관)290장수군 장수읍 한누리로 393장수군 장수읍 두산리 474063-352-7050문화예술과공개2015.11년
1819임실군작은별영화관(작은영화관)294임실군 임실읍 호국로 1703임실군 임실읍 이도리 277063-644-7050문화예술과공개2015.11년
1920고창군동리시네마(작은영화관)293고창군 고창읍 판소리길 20고창군 고창읍 읍내리 457063-564-1340문화예술과공개2015.11년
2021부안군마실영화관(작은영화관)299부안군 부안읍 예술회관길 11부안군 부안읍 서외리 455-51063-582-1228문화예술과공개2015.11년