Overview

Dataset statistics

Number of variables8
Number of observations87
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory5.8 KiB
Average record size in memory68.5 B

Variable types

Numeric3
Text2
Boolean2
Categorical1

Dataset

Description경기도 광주시 시립도서관 홈페이지를 운영하기 위한 공통코드에 대한 데이터로 코드번호, 사용여부, 등록날짜, 삭제여부 등의 항목을 제공합니다.
Author경기도 광주시
URLhttps://www.data.go.kr/data/15121581/fileData.do

Alerts

사용여부 has constant value ""Constant
삭제여부 has constant value ""Constant
코드번호 is highly overall correlated with 코드그룹번호 and 1 other fieldsHigh correlation
코드그룹번호 is highly overall correlated with 코드번호 and 1 other fieldsHigh correlation
등록날짜 is highly overall correlated with 코드번호 and 1 other fieldsHigh correlation
코드번호 has unique valuesUnique
순서 has 6 (6.9%) zerosZeros

Reproduction

Analysis started2023-12-12 22:07:08.643708
Analysis finished2023-12-12 22:07:10.144830
Duration1.5 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

코드번호
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct87
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean54.850575
Minimum1
Maximum221
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size915.0 B
2023-12-13T07:07:10.228769image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile5.3
Q122.5
median44
Q365.5
95-th percentile161.7
Maximum221
Range220
Interquartile range (IQR)43

Descriptive statistics

Standard deviation47.105406
Coefficient of variation (CV)0.85879512
Kurtosis2.490533
Mean54.850575
Median Absolute Deviation (MAD)22
Skewness1.5899667
Sum4772
Variance2218.9193
MonotonicityNot monotonic
2023-12-13T07:07:10.638479image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 1
 
1.1%
2 1
 
1.1%
65 1
 
1.1%
64 1
 
1.1%
63 1
 
1.1%
62 1
 
1.1%
60 1
 
1.1%
59 1
 
1.1%
58 1
 
1.1%
56 1
 
1.1%
Other values (77) 77
88.5%
ValueCountFrequency (%)
1 1
1.1%
2 1
1.1%
3 1
1.1%
4 1
1.1%
5 1
1.1%
6 1
1.1%
7 1
1.1%
8 1
1.1%
9 1
1.1%
10 1
1.1%
ValueCountFrequency (%)
221 1
1.1%
201 1
1.1%
182 1
1.1%
181 1
1.1%
162 1
1.1%
161 1
1.1%
141 1
1.1%
121 1
1.1%
108 1
1.1%
107 1
1.1%

코드그룹번호
Real number (ℝ)

HIGH CORRELATION 

Distinct8
Distinct (%)9.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean5.6896552
Minimum1
Maximum24
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size915.0 B
2023-12-13T07:07:10.759663image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q11
median5
Q36
95-th percentile24
Maximum24
Range23
Interquartile range (IQR)5

Descriptive statistics

Standard deviation6.3361465
Coefficient of variation (CV)1.1136257
Kurtosis3.957194
Mean5.6896552
Median Absolute Deviation (MAD)3
Skewness2.1603533
Sum495
Variance40.146752
MonotonicityNot monotonic
2023-12-13T07:07:10.880453image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=8)
ValueCountFrequency (%)
1 25
28.7%
6 14
16.1%
5 11
12.6%
8 11
12.6%
3 9
 
10.3%
24 8
 
9.2%
2 6
 
6.9%
4 3
 
3.4%
ValueCountFrequency (%)
1 25
28.7%
2 6
 
6.9%
3 9
 
10.3%
4 3
 
3.4%
5 11
12.6%
6 14
16.1%
8 11
12.6%
24 8
 
9.2%
ValueCountFrequency (%)
24 8
 
9.2%
8 11
12.6%
6 14
16.1%
5 11
12.6%
4 3
 
3.4%
3 9
 
10.3%
2 6
 
6.9%
1 25
28.7%

코드
Text

Distinct64
Distinct (%)73.6%
Missing0
Missing (%)0.0%
Memory size828.0 B
2023-12-13T07:07:11.149757image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length12
Median length2
Mean length2.908046
Min length1

Characters and Unicode

Total characters253
Distinct characters34
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique42 ?
Unique (%)48.3%

Sample

1st row2
2nd row31
3rd row32
4th row33
5th row41
ValueCountFrequency (%)
10 3
 
3.4%
17 2
 
2.3%
16 2
 
2.3%
center 2
 
2.3%
slib 2
 
2.3%
np 2
 
2.3%
all 2
 
2.3%
gj 2
 
2.3%
op 2
 
2.3%
18 2
 
2.3%
Other values (54) 66
75.9%
2023-12-13T07:07:11.534050image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 21
 
8.3%
2 15
 
5.9%
4 15
 
5.9%
o 14
 
5.5%
c 14
 
5.5%
m 13
 
5.1%
a 12
 
4.7%
3 11
 
4.3%
e 10
 
4.0%
n 10
 
4.0%
Other values (24) 118
46.6%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 141
55.7%
Decimal Number 102
40.3%
Other Punctuation 10
 
4.0%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
o 14
9.9%
c 14
9.9%
m 13
 
9.2%
a 12
 
8.5%
e 10
 
7.1%
n 10
 
7.1%
l 10
 
7.1%
t 9
 
6.4%
i 8
 
5.7%
r 7
 
5.0%
Other values (13) 34
24.1%
Decimal Number
ValueCountFrequency (%)
1 21
20.6%
2 15
14.7%
4 15
14.7%
3 11
10.8%
5 9
8.8%
0 8
 
7.8%
6 8
 
7.8%
8 6
 
5.9%
7 5
 
4.9%
9 4
 
3.9%
Other Punctuation
ValueCountFrequency (%)
. 10
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 141
55.7%
Common 112
44.3%

Most frequent character per script

Latin
ValueCountFrequency (%)
o 14
9.9%
c 14
9.9%
m 13
 
9.2%
a 12
 
8.5%
e 10
 
7.1%
n 10
 
7.1%
l 10
 
7.1%
t 9
 
6.4%
i 8
 
5.7%
r 7
 
5.0%
Other values (13) 34
24.1%
Common
ValueCountFrequency (%)
1 21
18.8%
2 15
13.4%
4 15
13.4%
3 11
9.8%
. 10
8.9%
5 9
8.0%
0 8
 
7.1%
6 8
 
7.1%
8 6
 
5.4%
7 5
 
4.5%

Most occurring blocks

ValueCountFrequency (%)
ASCII 253
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 21
 
8.3%
2 15
 
5.9%
4 15
 
5.9%
o 14
 
5.5%
c 14
 
5.5%
m 13
 
5.1%
a 12
 
4.7%
3 11
 
4.3%
e 10
 
4.0%
n 10
 
4.0%
Other values (24) 118
46.6%

코드명
Text

Distinct72
Distinct (%)82.8%
Missing0
Missing (%)0.0%
Memory size828.0 B
2023-12-13T07:07:11.794287image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length12
Median length11
Mean length4.4137931
Min length2

Characters and Unicode

Total characters384
Distinct characters102
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

Unique57 ?
Unique (%)65.5%

Sample

1st row서울특별시
2nd row경기도
3rd row인천광역시
4th row강원도
5th row충청남도
ValueCountFrequency (%)
보기 3
 
3.3%
초월 2
 
2.2%
18 2
 
2.2%
17 2
 
2.2%
시립중앙 2
 
2.2%
19 2
 
2.2%
능평 2
 
2.2%
곤지암 2
 
2.2%
오포 2
 
2.2%
열람실1 2
 
2.2%
Other values (64) 71
77.2%
2023-12-13T07:07:12.177107image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 18
 
4.7%
도 18
 
4.7%
o 11
 
2.9%
m 11
 
2.9%
시 11
 
2.9%
. 10
 
2.6%
a 10
 
2.6%
작 9
 
2.3%
은 9
 
2.3%
서 9
 
2.3%
Other values (92) 268
69.8%

Most occurring categories

ValueCountFrequency (%)
Other Letter 253
65.9%
Lowercase Letter 78
 
20.3%
Decimal Number 38
 
9.9%
Other Punctuation 10
 
2.6%
Space Separator 5
 
1.3%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
도 18
 
7.1%
시 11
 
4.3%
작 9
 
3.6%
은 9
 
3.6%
서 9
 
3.6%
광 8
 
3.2%
관 8
 
3.2%
실 8
 
3.2%
열 7
 
2.8%
람 7
 
2.8%
Other values (63) 159
62.8%
Lowercase Letter
ValueCountFrequency (%)
o 11
14.1%
m 11
14.1%
a 10
12.8%
c 7
9.0%
e 6
7.7%
n 5
 
6.4%
t 4
 
5.1%
r 4
 
5.1%
i 4
 
5.1%
l 3
 
3.8%
Other values (9) 13
16.7%
Decimal Number
ValueCountFrequency (%)
1 18
47.4%
0 7
 
18.4%
7 3
 
7.9%
8 3
 
7.9%
6 2
 
5.3%
9 2
 
5.3%
2 2
 
5.3%
5 1
 
2.6%
Other Punctuation
ValueCountFrequency (%)
. 10
100.0%
Space Separator
ValueCountFrequency (%)
5
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 253
65.9%
Latin 78
 
20.3%
Common 53
 
13.8%

Most frequent character per script

Hangul
ValueCountFrequency (%)
도 18
 
7.1%
시 11
 
4.3%
작 9
 
3.6%
은 9
 
3.6%
서 9
 
3.6%
광 8
 
3.2%
관 8
 
3.2%
실 8
 
3.2%
열 7
 
2.8%
람 7
 
2.8%
Other values (63) 159
62.8%
Latin
ValueCountFrequency (%)
o 11
14.1%
m 11
14.1%
a 10
12.8%
c 7
9.0%
e 6
7.7%
n 5
 
6.4%
t 4
 
5.1%
r 4
 
5.1%
i 4
 
5.1%
l 3
 
3.8%
Other values (9) 13
16.7%
Common
ValueCountFrequency (%)
1 18
34.0%
. 10
18.9%
0 7
 
13.2%
5
 
9.4%
7 3
 
5.7%
8 3
 
5.7%
6 2
 
3.8%
9 2
 
3.8%
2 2
 
3.8%
5 1
 
1.9%

Most occurring blocks

ValueCountFrequency (%)
Hangul 253
65.9%
ASCII 131
34.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 18
13.7%
o 11
 
8.4%
m 11
 
8.4%
. 10
 
7.6%
a 10
 
7.6%
c 7
 
5.3%
0 7
 
5.3%
e 6
 
4.6%
n 5
 
3.8%
5
 
3.8%
Other values (19) 41
31.3%
Hangul
ValueCountFrequency (%)
도 18
 
7.1%
시 11
 
4.3%
작 9
 
3.6%
은 9
 
3.6%
서 9
 
3.6%
광 8
 
3.2%
관 8
 
3.2%
실 8
 
3.2%
열 7
 
2.8%
람 7
 
2.8%
Other values (63) 159
62.8%

사용여부
Boolean

CONSTANT 

Distinct1
Distinct (%)1.1%
Missing0
Missing (%)0.0%
Memory size219.0 B
True
87 
ValueCountFrequency (%)
True 87
100.0%
2023-12-13T07:07:12.302969image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

순서
Real number (ℝ)

ZEROS 

Distinct25
Distinct (%)28.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean6.6666667
Minimum0
Maximum24
Zeros6
Zeros (%)6.9%
Negative0
Negative (%)0.0%
Memory size915.0 B
2023-12-13T07:07:12.466403image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q12.5
median5
Q39
95-th percentile19.7
Maximum24
Range24
Interquartile range (IQR)6.5

Descriptive statistics

Standard deviation5.7782001
Coefficient of variation (CV)0.86673002
Kurtosis1.2223165
Mean6.6666667
Median Absolute Deviation (MAD)3
Skewness1.2937632
Sum580
Variance33.387597
MonotonicityNot monotonic
2023-12-13T07:07:12.587765image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=25)
ValueCountFrequency (%)
1 8
9.2%
2 8
9.2%
3 8
9.2%
4 8
9.2%
5 8
9.2%
0 6
 
6.9%
6 6
 
6.9%
7 6
 
6.9%
8 6
 
6.9%
9 4
 
4.6%
Other values (15) 19
21.8%
ValueCountFrequency (%)
0 6
6.9%
1 8
9.2%
2 8
9.2%
3 8
9.2%
4 8
9.2%
5 8
9.2%
6 6
6.9%
7 6
6.9%
8 6
6.9%
9 4
4.6%
ValueCountFrequency (%)
24 1
1.1%
23 1
1.1%
22 1
1.1%
21 1
1.1%
20 1
1.1%
19 1
1.1%
18 1
1.1%
17 1
1.1%
16 1
1.1%
15 1
1.1%

등록날짜
Categorical

HIGH CORRELATION 

Distinct12
Distinct (%)13.8%
Missing0
Missing (%)0.0%
Memory size828.0 B
2017-08-05
40 
2017-11-19
26 
2020-07-24
8 
2017-08-20
 
3
2022-09-28
 
2
Other values (7)
8 

Length

Max length10
Median length10
Mean length10
Min length10

Unique

Unique6 ?
Unique (%)6.9%

Sample

1st row2017-08-05
2nd row2017-08-05
3rd row2017-08-05
4th row2017-08-05
5th row2017-08-05

Common Values

ValueCountFrequency (%)
2017-08-05 40
46.0%
2017-11-19 26
29.9%
2020-07-24 8
 
9.2%
2017-08-20 3
 
3.4%
2022-09-28 2
 
2.3%
2022-12-26 2
 
2.3%
2017-12-10 1
 
1.1%
2018-12-06 1
 
1.1%
2021-10-27 1
 
1.1%
2023-01-27 1
 
1.1%
Other values (2) 2
 
2.3%

Length

2023-12-13T07:07:12.715249image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
2017-08-05 40
46.0%
2017-11-19 26
29.9%
2020-07-24 8
 
9.2%
2017-08-20 3
 
3.4%
2022-09-28 2
 
2.3%
2022-12-26 2
 
2.3%
2017-12-10 1
 
1.1%
2018-12-06 1
 
1.1%
2021-10-27 1
 
1.1%
2023-01-27 1
 
1.1%
Other values (2) 2
 
2.3%

삭제여부
Boolean

CONSTANT 

Distinct1
Distinct (%)1.1%
Missing0
Missing (%)0.0%
Memory size219.0 B
False
87 
ValueCountFrequency (%)
False 87
100.0%
2023-12-13T07:07:12.808706image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Interactions

2023-12-13T07:07:09.661470image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T07:07:09.151488image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T07:07:09.411797image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T07:07:09.740964image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T07:07:09.237698image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T07:07:09.490184image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T07:07:09.819631image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T07:07:09.325386image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T07:07:09.573349image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-13T07:07:12.870916image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
코드번호코드그룹번호코드코드명순서등록날짜
코드번호1.0000.9700.0000.0000.5600.970
코드그룹번호0.9701.0000.0000.1830.0000.903
코드0.0000.0001.0000.9950.7680.200
코드명0.0000.1830.9951.0000.0000.891
순서0.5600.0000.7680.0001.0000.327
등록날짜0.9700.9030.2000.8910.3271.000
2023-12-13T07:07:12.978381image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
코드번호코드그룹번호순서등록날짜
코드번호1.0000.920-0.0710.866
코드그룹번호0.9201.000-0.2960.751
순서-0.071-0.2961.0000.112
등록날짜0.8660.7510.1121.000

Missing values

2023-12-13T07:07:09.944949image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-13T07:07:10.087495image/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

코드번호코드그룹번호코드코드명사용여부순서등록날짜삭제여부
0112서울특별시Y02017-08-05N
12131경기도Y12017-08-05N
23132인천광역시Y22017-08-05N
34133강원도Y32017-08-05N
45141충청남도Y42017-08-05N
56142대전광역시Y52017-08-05N
67143충청북도Y62017-08-05N
78144세종특별자치시Y72017-08-05N
89151부산광역시Y82017-08-05N
910152울산광역시Y92017-08-05N
코드번호코드그룹번호코드코드명사용여부순서등록날짜삭제여부
77105245일반 열람실1Y52020-07-24N
78106246제1열람실Y62020-07-24N
79107247제2열람실Y72020-07-24N
80108248성인열람실Y82020-07-24N
81121625양벌Y42021-10-26N
82181623퇴촌Y112022-12-26N
83182624만선Y122022-12-26N
84708yb양벌Y52017-11-19N
851618tc퇴촌Y82022-09-28N
862215ms만선도서관Y102023-03-20N