Overview

Dataset statistics

Number of variables5
Number of observations22
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory1.0 KiB
Average record size in memory47.0 B

Variable types

Numeric1
DateTime1
Text3

Dataset

Description인천광역시 부평구 청소년 게임 제공업 현황 데이터는 청소년 게임 제공업 상호, 주소, 등록(신고)일에 대한 데이터를 제공합니다.
Author인천광역시 부평구
URLhttps://data.incheon.go.kr/findData/publicDataDetail?dataId=15104165&srcSe=7661IVAWM27C61E190

Alerts

순번 has unique valuesUnique
등록(신고)일자 has unique valuesUnique
상호 has unique valuesUnique
영업소소재지(도로명) has unique valuesUnique
영업소소재지(지번) has unique valuesUnique

Reproduction

Analysis started2024-01-28 06:38:14.026837
Analysis finished2024-01-28 06:38:14.435869
Duration0.41 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

순번
Real number (ℝ)

UNIQUE 

Distinct22
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean11.5
Minimum1
Maximum22
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size330.0 B
2024-01-28T15:38:14.482249image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile2.05
Q16.25
median11.5
Q316.75
95-th percentile20.95
Maximum22
Range21
Interquartile range (IQR)10.5

Descriptive statistics

Standard deviation6.4935866
Coefficient of variation (CV)0.5646597
Kurtosis-1.2
Mean11.5
Median Absolute Deviation (MAD)5.5
Skewness0
Sum253
Variance42.166667
MonotonicityStrictly increasing
2024-01-28T15:38:14.579214image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=22)
ValueCountFrequency (%)
1 1
 
4.5%
13 1
 
4.5%
22 1
 
4.5%
21 1
 
4.5%
20 1
 
4.5%
19 1
 
4.5%
18 1
 
4.5%
17 1
 
4.5%
16 1
 
4.5%
15 1
 
4.5%
Other values (12) 12
54.5%
ValueCountFrequency (%)
1 1
4.5%
2 1
4.5%
3 1
4.5%
4 1
4.5%
5 1
4.5%
6 1
4.5%
7 1
4.5%
8 1
4.5%
9 1
4.5%
10 1
4.5%
ValueCountFrequency (%)
22 1
4.5%
21 1
4.5%
20 1
4.5%
19 1
4.5%
18 1
4.5%
17 1
4.5%
16 1
4.5%
15 1
4.5%
14 1
4.5%
13 1
4.5%

등록(신고)일자
Date

UNIQUE 

Distinct22
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size308.0 B
Minimum2008-05-22 00:00:00
Maximum2023-02-14 00:00:00
2024-01-28T15:38:14.657958image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-28T15:38:14.736061image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=22)

상호
Text

UNIQUE 

Distinct22
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size308.0 B
2024-01-28T15:38:14.881503image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length24
Median length14.5
Mean length6.5454545
Min length3

Characters and Unicode

Total characters144
Distinct characters84
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

Unique22 ?
Unique (%)100.0%

Sample

1st row펀스퀘어
2nd row인형뽑기
3rd row인형뽑기방(토이랜드)
4th row뽑기 #
5th row스마일 뽑기방
ValueCountFrequency (%)
펀스퀘어 1
 
3.4%
짱오락실 1
 
3.4%
premium 1
 
3.4%
사격팡 1
 
3.4%
어드벤처 1
 
3.4%
라라키즈 1
 
3.4%
픽미업뽑기방 1
 
3.4%
십정장터뽑기매니아 1
 
3.4%
써니호 1
 
3.4%
쿠마샵 1
 
3.4%
Other values (19) 19
65.5%
2024-01-28T15:38:15.131386image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
뽑 10
 
6.9%
기 10
 
6.9%
7
 
4.9%
아 3
 
2.1%
니 3
 
2.1%
방 3
 
2.1%
스 3
 
2.1%
라 3
 
2.1%
r 3
 
2.1%
O 3
 
2.1%
Other values (74) 96
66.7%

Most occurring categories

ValueCountFrequency (%)
Other Letter 102
70.8%
Uppercase Letter 15
 
10.4%
Lowercase Letter 13
 
9.0%
Space Separator 7
 
4.9%
Close Punctuation 2
 
1.4%
Open Punctuation 2
 
1.4%
Other Punctuation 2
 
1.4%
Decimal Number 1
 
0.7%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
뽑 10
 
9.8%
기 10
 
9.8%
아 3
 
2.9%
니 3
 
2.9%
방 3
 
2.9%
스 3
 
2.9%
라 3
 
2.9%
매 2
 
2.0%
짱 2
 
2.0%
파 2
 
2.0%
Other values (49) 61
59.8%
Uppercase Letter
ValueCountFrequency (%)
O 3
20.0%
E 2
13.3%
P 2
13.3%
N 2
13.3%
G 1
 
6.7%
I 1
 
6.7%
T 1
 
6.7%
H 1
 
6.7%
S 1
 
6.7%
Z 1
 
6.7%
Lowercase Letter
ValueCountFrequency (%)
r 3
23.1%
e 2
15.4%
m 2
15.4%
i 1
 
7.7%
u 1
 
7.7%
n 1
 
7.7%
t 1
 
7.7%
a 1
 
7.7%
k 1
 
7.7%
Other Punctuation
ValueCountFrequency (%)
＃ 1
50.0%
# 1
50.0%
Space Separator
ValueCountFrequency (%)
7
100.0%
Close Punctuation
ValueCountFrequency (%)
) 2
100.0%
Open Punctuation
ValueCountFrequency (%)
( 2
100.0%
Decimal Number
ValueCountFrequency (%)
7 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 102
70.8%
Latin 28
 
19.4%
Common 14
 
9.7%

Most frequent character per script

Hangul
ValueCountFrequency (%)
뽑 10
 
9.8%
기 10
 
9.8%
아 3
 
2.9%
니 3
 
2.9%
방 3
 
2.9%
스 3
 
2.9%
라 3
 
2.9%
매 2
 
2.0%
짱 2
 
2.0%
파 2
 
2.0%
Other values (49) 61
59.8%
Latin
ValueCountFrequency (%)
r 3
 
10.7%
O 3
 
10.7%
E 2
 
7.1%
e 2
 
7.1%
m 2
 
7.1%
P 2
 
7.1%
N 2
 
7.1%
i 1
 
3.6%
G 1
 
3.6%
u 1
 
3.6%
Other values (9) 9
32.1%
Common
ValueCountFrequency (%)
7
50.0%
) 2
 
14.3%
( 2
 
14.3%
＃ 1
 
7.1%
# 1
 
7.1%
7 1
 
7.1%

Most occurring blocks

ValueCountFrequency (%)
Hangul 102
70.8%
ASCII 41
28.5%
None 1
 
0.7%

Most frequent character per block

Hangul
ValueCountFrequency (%)
뽑 10
 
9.8%
기 10
 
9.8%
아 3
 
2.9%
니 3
 
2.9%
방 3
 
2.9%
스 3
 
2.9%
라 3
 
2.9%
매 2
 
2.0%
짱 2
 
2.0%
파 2
 
2.0%
Other values (49) 61
59.8%
ASCII
ValueCountFrequency (%)
7
17.1%
r 3
 
7.3%
O 3
 
7.3%
E 2
 
4.9%
e 2
 
4.9%
m 2
 
4.9%
P 2
 
4.9%
N 2
 
4.9%
) 2
 
4.9%
( 2
 
4.9%
Other values (14) 14
34.1%
None
ValueCountFrequency (%)
＃ 1
100.0%

영업소소재지(도로명)
Text

UNIQUE 

Distinct22
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size308.0 B
2024-01-28T15:38:15.309407image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length40
Median length37
Mean length32.136364
Min length26

Characters and Unicode

Total characters707
Distinct characters78
Distinct categories7 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique22 ?
Unique (%)100.0%

Sample

1st row인천광역시 부평구 마장로 489 (청천동, 아이즈빌아울렛)
2nd row인천광역시 부평구 시장로12번길 5, 1층 (부평동)
3rd row인천광역시 부평구 길주로647번길 20, 1층 (삼산동, 삼성프라자)
4th row인천광역시 부평구 평천로 315, 1층 (갈산동)
5th row인천광역시 부평구 시장로 27, 1층 (부평동)
ValueCountFrequency (%)
인천광역시 22
 
15.8%
부평구 22
 
15.8%
1층 12
 
8.6%
부평동 10
 
7.2%
마장로 3
 
2.2%
청천동 3
 
2.2%
십정동 3
 
2.2%
갈산동 2
 
1.4%
상가동 2
 
1.4%
부일로113번길 2
 
1.4%
Other values (51) 58
41.7%
2024-01-28T15:38:15.789875image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
117
 
16.5%
부 42
 
5.9%
평 39
 
5.5%
1 36
 
5.1%
천 27
 
3.8%
시 24
 
3.4%
, 24
 
3.4%
동 24
 
3.4%
인 23
 
3.3%
광 23
 
3.3%
Other values (68) 328
46.4%

Most occurring categories

ValueCountFrequency (%)
Other Letter 405
57.3%
Space Separator 117
 
16.5%
Decimal Number 114
 
16.1%
Other Punctuation 24
 
3.4%
Open Punctuation 22
 
3.1%
Close Punctuation 22
 
3.1%
Dash Punctuation 3
 
0.4%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
부 42
 
10.4%
평 39
 
9.6%
천 27
 
6.7%
시 24
 
5.9%
동 24
 
5.9%
인 23
 
5.7%
광 23
 
5.7%
역 23
 
5.7%
구 22
 
5.4%
로 22
 
5.4%
Other values (53) 136
33.6%
Decimal Number
ValueCountFrequency (%)
1 36
31.6%
4 15
13.2%
2 14
 
12.3%
0 11
 
9.6%
7 7
 
6.1%
3 7
 
6.1%
5 7
 
6.1%
8 6
 
5.3%
6 6
 
5.3%
9 5
 
4.4%
Space Separator
ValueCountFrequency (%)
117
100.0%
Other Punctuation
ValueCountFrequency (%)
, 24
100.0%
Open Punctuation
ValueCountFrequency (%)
( 22
100.0%
Close Punctuation
ValueCountFrequency (%)
) 22
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 3
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 405
57.3%
Common 302
42.7%

Most frequent character per script

Hangul
ValueCountFrequency (%)
부 42
 
10.4%
평 39
 
9.6%
천 27
 
6.7%
시 24
 
5.9%
동 24
 
5.9%
인 23
 
5.7%
광 23
 
5.7%
역 23
 
5.7%
구 22
 
5.4%
로 22
 
5.4%
Other values (53) 136
33.6%
Common
ValueCountFrequency (%)
117
38.7%
1 36
 
11.9%
, 24
 
7.9%
( 22
 
7.3%
) 22
 
7.3%
4 15
 
5.0%
2 14
 
4.6%
0 11
 
3.6%
7 7
 
2.3%
3 7
 
2.3%
Other values (5) 27
 
8.9%

Most occurring blocks

ValueCountFrequency (%)
Hangul 405
57.3%
ASCII 302
42.7%

Most frequent character per block

ASCII
ValueCountFrequency (%)
117
38.7%
1 36
 
11.9%
, 24
 
7.9%
( 22
 
7.3%
) 22
 
7.3%
4 15
 
5.0%
2 14
 
4.6%
0 11
 
3.6%
7 7
 
2.3%
3 7
 
2.3%
Other values (5) 27
 
8.9%
Hangul
ValueCountFrequency (%)
부 42
 
10.4%
평 39
 
9.6%
천 27
 
6.7%
시 24
 
5.9%
동 24
 
5.9%
인 23
 
5.7%
광 23
 
5.7%
역 23
 
5.7%
구 22
 
5.4%
로 22
 
5.4%
Other values (53) 136
33.6%

영업소소재지(지번)
Text

UNIQUE 

Distinct22
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size308.0 B
2024-01-28T15:38:15.946744image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length30
Median length24
Mean length22.590909
Min length18

Characters and Unicode

Total characters497
Distinct characters44
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

Unique22 ?
Unique (%)100.0%

Sample

1st row인천광역시 부평구 청천동 386
2nd row인천광역시 부평구 부평동 153-22 1층
3rd row인천광역시 부평구 삼산동 460-1 1층
4th row인천광역시 부평구 갈산동 160-30 1층
5th row인천광역시 부평구 부평동 193-1 1층
ValueCountFrequency (%)
인천광역시 22
21.2%
부평구 22
21.2%
부평동 10
 
9.6%
1층 6
 
5.8%
십정동 3
 
2.9%
청천동 3
 
2.9%
1 2
 
1.9%
갈산동 2
 
1.9%
부개동 2
 
1.9%
950 1
 
1.0%
Other values (31) 31
29.8%
2024-01-28T15:38:16.204698image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
102
20.5%
부 36
 
7.2%
평 34
 
6.8%
1 25
 
5.0%
천 25
 
5.0%
역 23
 
4.6%
동 23
 
4.6%
인 22
 
4.4%
광 22
 
4.4%
시 22
 
4.4%
Other values (34) 163
32.8%

Most occurring categories

ValueCountFrequency (%)
Other Letter 272
54.7%
Decimal Number 105
 
21.1%
Space Separator 102
 
20.5%
Dash Punctuation 18
 
3.6%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
부 36
13.2%
평 34
12.5%
천 25
9.2%
역 23
8.5%
동 23
8.5%
인 22
8.1%
광 22
8.1%
시 22
8.1%
구 22
8.1%
층 7
 
2.6%
Other values (22) 36
13.2%
Decimal Number
ValueCountFrequency (%)
1 25
23.8%
3 13
12.4%
0 12
11.4%
2 11
10.5%
4 9
 
8.6%
5 9
 
8.6%
9 8
 
7.6%
8 7
 
6.7%
7 6
 
5.7%
6 5
 
4.8%
Space Separator
ValueCountFrequency (%)
102
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 18
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 272
54.7%
Common 225
45.3%

Most frequent character per script

Hangul
ValueCountFrequency (%)
부 36
13.2%
평 34
12.5%
천 25
9.2%
역 23
8.5%
동 23
8.5%
인 22
8.1%
광 22
8.1%
시 22
8.1%
구 22
8.1%
층 7
 
2.6%
Other values (22) 36
13.2%
Common
ValueCountFrequency (%)
102
45.3%
1 25
 
11.1%
- 18
 
8.0%
3 13
 
5.8%
0 12
 
5.3%
2 11
 
4.9%
4 9
 
4.0%
5 9
 
4.0%
9 8
 
3.6%
8 7
 
3.1%
Other values (2) 11
 
4.9%

Most occurring blocks

ValueCountFrequency (%)
Hangul 272
54.7%
ASCII 225
45.3%

Most frequent character per block

ASCII
ValueCountFrequency (%)
102
45.3%
1 25
 
11.1%
- 18
 
8.0%
3 13
 
5.8%
0 12
 
5.3%
2 11
 
4.9%
4 9
 
4.0%
5 9
 
4.0%
9 8
 
3.6%
8 7
 
3.1%
Other values (2) 11
 
4.9%
Hangul
ValueCountFrequency (%)
부 36
13.2%
평 34
12.5%
천 25
9.2%
역 23
8.5%
동 23
8.5%
인 22
8.1%
광 22
8.1%
시 22
8.1%
구 22
8.1%
층 7
 
2.6%
Other values (22) 36
13.2%

Interactions

2024-01-28T15:38:14.232746image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-01-28T15:38:16.277544image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
순번등록(신고)일자상호영업소소재지(도로명)영업소소재지(지번)
순번1.0001.0001.0001.0001.000
등록(신고)일자1.0001.0001.0001.0001.000
상호1.0001.0001.0001.0001.000
영업소소재지(도로명)1.0001.0001.0001.0001.000
영업소소재지(지번)1.0001.0001.0001.0001.000

Missing values

2024-01-28T15:38:14.318993image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-01-28T15:38:14.406661image/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

순번등록(신고)일자상호영업소소재지(도로명)영업소소재지(지번)
012008-05-22펀스퀘어인천광역시 부평구 마장로 489 (청천동, 아이즈빌아울렛)인천광역시 부평구 청천동 386
122016-09-02인형뽑기인천광역시 부평구 시장로12번길 5, 1층 (부평동)인천광역시 부평구 부평동 153-22 1층
232016-11-15인형뽑기방(토이랜드)인천광역시 부평구 길주로647번길 20, 1층 (삼산동, 삼성프라자)인천광역시 부평구 삼산동 460-1 1층
342016-12-12뽑기 #인천광역시 부평구 평천로 315, 1층 (갈산동)인천광역시 부평구 갈산동 160-30 1층
452016-12-16스마일 뽑기방인천광역시 부평구 시장로 27, 1층 (부평동)인천광역시 부평구 부평동 193-1 1층
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