Overview

Dataset statistics

Number of variables3
Number of observations204
Missing cells15
Missing cells (%)2.5%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory5.1 KiB
Average record size in memory25.6 B

Variable types

Numeric1
Text2

Dataset

Description인천광역시 부평구 다중이용시설 현황 데이터는 부평구 내의 다중이용시설에 대한 시설명, 주소 정보를 제공하고 있습니다.
Author공공데이터포털
URLhttps://www.data.go.kr/data/15118789/fileData.do

Alerts

주소 has 15 (7.4%) missing valuesMissing
연번 has unique valuesUnique

Reproduction

Analysis started2024-04-17 18:27:08.972416
Analysis finished2024-04-17 18:27:09.336333
Duration0.36 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

연번
Real number (ℝ)

UNIQUE 

Distinct204
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean102.5
Minimum1
Maximum204
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.9 KiB
2024-04-18T03:27:09.405191image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile11.15
Q151.75
median102.5
Q3153.25
95-th percentile193.85
Maximum204
Range203
Interquartile range (IQR)101.5

Descriptive statistics

Standard deviation59.033889
Coefficient of variation (CV)0.57594038
Kurtosis-1.2
Mean102.5
Median Absolute Deviation (MAD)51
Skewness0
Sum20910
Variance3485
MonotonicityStrictly increasing
2024-04-18T03:27:09.523425image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 1
 
0.5%
142 1
 
0.5%
132 1
 
0.5%
133 1
 
0.5%
134 1
 
0.5%
135 1
 
0.5%
136 1
 
0.5%
137 1
 
0.5%
138 1
 
0.5%
139 1
 
0.5%
Other values (194) 194
95.1%
ValueCountFrequency (%)
1 1
0.5%
2 1
0.5%
3 1
0.5%
4 1
0.5%
5 1
0.5%
6 1
0.5%
7 1
0.5%
8 1
0.5%
9 1
0.5%
10 1
0.5%
ValueCountFrequency (%)
204 1
0.5%
203 1
0.5%
202 1
0.5%
201 1
0.5%
200 1
0.5%
199 1
0.5%
198 1
0.5%
197 1
0.5%
196 1
0.5%
195 1
0.5%

시설명
Text

Distinct197
Distinct (%)96.6%
Missing0
Missing (%)0.0%
Memory size1.7 KiB
2024-04-18T03:27:09.727171image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length25
Median length22
Mean length8.5392157
Min length4

Characters and Unicode

Total characters1742
Distinct characters321
Distinct categories10 ?
Distinct scripts3 ?
Distinct blocks4 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique191 ?
Unique (%)93.6%

Sample

1st row부평구청역(7호선)
2nd row굴포천역(7호선)
3rd row삼산체육관역(7호선)
4th row부평역(인천1호선)
5th row갈산역(인천1호선)
ValueCountFrequency (%)
pc 13
 
4.9%
요양원 4
 
1.5%
premium 4
 
1.5%
롯데쇼핑㈜롯데마트 4
 
1.5%
pc방 3
 
1.1%
bon's 3
 
1.1%
인천성모병원 3
 
1.1%
부평점 3
 
1.1%
부평 2
 
0.7%
3pop 2
 
0.7%
Other values (217) 226
84.6%
2024-04-18T03:27:10.013547image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
이 66
 
3.8%
66
 
3.8%
원 50
 
2.9%
부 50
 
2.9%
어 49
 
2.8%
집 49
 
2.8%
린 48
 
2.8%
평 47
 
2.7%
인 28
 
1.6%
병 26
 
1.5%
Other values (311) 1263
72.5%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1387
79.6%
Uppercase Letter 125
 
7.2%
Space Separator 66
 
3.8%
Decimal Number 47
 
2.7%
Lowercase Letter 46
 
2.6%
Open Punctuation 23
 
1.3%
Close Punctuation 23
 
1.3%
Other Symbol 12
 
0.7%
Other Punctuation 12
 
0.7%
Dash Punctuation 1
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
이 66
 
4.8%
원 50
 
3.6%
부 50
 
3.6%
어 49
 
3.5%
집 49
 
3.5%
린 48
 
3.5%
평 47
 
3.4%
인 28
 
2.0%
병 26
 
1.9%
양 26
 
1.9%
Other values (254) 948
68.3%
Uppercase Letter
ValueCountFrequency (%)
C 25
20.0%
P 19
15.2%
A 10
 
8.0%
O 9
 
7.2%
E 7
 
5.6%
R 6
 
4.8%
M 6
 
4.8%
N 6
 
4.8%
T 5
 
4.0%
B 5
 
4.0%
Other values (12) 27
21.6%
Lowercase Letter
ValueCountFrequency (%)
p 13
28.3%
c 9
19.6%
m 6
13.0%
r 4
 
8.7%
u 3
 
6.5%
i 3
 
6.5%
e 3
 
6.5%
a 2
 
4.3%
f 1
 
2.2%
o 1
 
2.2%
Decimal Number
ValueCountFrequency (%)
1 15
31.9%
2 9
19.1%
0 8
17.0%
7 4
 
8.5%
3 4
 
8.5%
6 2
 
4.3%
8 2
 
4.3%
5 1
 
2.1%
9 1
 
2.1%
4 1
 
2.1%
Other Punctuation
ValueCountFrequency (%)
' 3
25.0%
. 2
16.7%
, 2
16.7%
& 2
16.7%
? 2
16.7%
! 1
 
8.3%
Open Punctuation
ValueCountFrequency (%)
( 17
73.9%
[ 6
 
26.1%
Close Punctuation
ValueCountFrequency (%)
) 17
73.9%
] 6
 
26.1%
Other Symbol
ValueCountFrequency (%)
㈜ 11
91.7%
★ 1
 
8.3%
Space Separator
ValueCountFrequency (%)
66
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1398
80.3%
Common 173
 
9.9%
Latin 171
 
9.8%

Most frequent character per script

Hangul
ValueCountFrequency (%)
이 66
 
4.7%
원 50
 
3.6%
부 50
 
3.6%
어 49
 
3.5%
집 49
 
3.5%
린 48
 
3.4%
평 47
 
3.4%
인 28
 
2.0%
병 26
 
1.9%
양 26
 
1.9%
Other values (255) 959
68.6%
Latin
ValueCountFrequency (%)
C 25
14.6%
P 19
 
11.1%
p 13
 
7.6%
A 10
 
5.8%
O 9
 
5.3%
c 9
 
5.3%
E 7
 
4.1%
R 6
 
3.5%
M 6
 
3.5%
N 6
 
3.5%
Other values (23) 61
35.7%
Common
ValueCountFrequency (%)
66
38.2%
( 17
 
9.8%
) 17
 
9.8%
1 15
 
8.7%
2 9
 
5.2%
0 8
 
4.6%
[ 6
 
3.5%
] 6
 
3.5%
7 4
 
2.3%
3 4
 
2.3%
Other values (13) 21
 
12.1%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1387
79.6%
ASCII 343
 
19.7%
None 11
 
0.6%
Misc Symbols 1
 
0.1%

Most frequent character per block

Hangul
ValueCountFrequency (%)
이 66
 
4.8%
원 50
 
3.6%
부 50
 
3.6%
어 49
 
3.5%
집 49
 
3.5%
린 48
 
3.5%
평 47
 
3.4%
인 28
 
2.0%
병 26
 
1.9%
양 26
 
1.9%
Other values (254) 948
68.3%
ASCII
ValueCountFrequency (%)
66
19.2%
C 25
 
7.3%
P 19
 
5.5%
( 17
 
5.0%
) 17
 
5.0%
1 15
 
4.4%
p 13
 
3.8%
A 10
 
2.9%
O 9
 
2.6%
c 9
 
2.6%
Other values (45) 143
41.7%
None
ValueCountFrequency (%)
㈜ 11
100.0%
Misc Symbols
ValueCountFrequency (%)
★ 1
100.0%

주소
Text

MISSING 

Distinct175
Distinct (%)92.6%
Missing15
Missing (%)7.4%
Memory size1.7 KiB
2024-04-18T03:27:10.251112image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length46
Median length39
Mean length26.322751
Min length20

Characters and Unicode

Total characters4975
Distinct characters137
Distinct categories10 ?
Distinct scripts3 ?
Distinct blocks4 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique163 ?
Unique (%)86.2%

Sample

1st row인천광역시 부평구 부평대로 지하189 (청천동)
2nd row인천광역시 부평구 길주로 지하 623 (삼산동)
3rd row인천광역시 부평구 길주로 지하 713 (삼산동)
4th row인천광역시 부평구 광장로 지하15(부평동)
5th row인천광역시 부평구 부평대로 지하286 (갈산동)
ValueCountFrequency (%)
인천광역시 189
19.5%
부평구 189
19.5%
부평동 64
 
6.6%
삼산동 24
 
2.5%
부평대로 17
 
1.8%
산곡동 15
 
1.6%
청천동 14
 
1.4%
장제로 13
 
1.3%
경원대로 12
 
1.2%
길주로 12
 
1.2%
Other values (292) 418
43.2%
2024-04-18T03:27:10.582827image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
781
 
15.7%
부 331
 
6.7%
평 309
 
6.2%
천 214
 
4.3%
동 206
 
4.1%
인 198
 
4.0%
광 195
 
3.9%
시 195
 
3.9%
구 192
 
3.9%
로 192
 
3.9%
Other values (127) 2162
43.5%

Most occurring categories

ValueCountFrequency (%)
Other Letter 3030
60.9%
Space Separator 781
 
15.7%
Decimal Number 686
 
13.8%
Open Punctuation 189
 
3.8%
Close Punctuation 189
 
3.8%
Other Punctuation 66
 
1.3%
Dash Punctuation 17
 
0.3%
Math Symbol 12
 
0.2%
Uppercase Letter 4
 
0.1%
Letter Number 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
부 331
10.9%
평 309
 
10.2%
천 214
 
7.1%
동 206
 
6.8%
인 198
 
6.5%
광 195
 
6.4%
시 195
 
6.4%
구 192
 
6.3%
로 192
 
6.3%
역 189
 
6.2%
Other values (106) 809
26.7%
Decimal Number
ValueCountFrequency (%)
1 133
19.4%
2 83
12.1%
3 78
11.4%
6 74
10.8%
5 71
10.3%
4 61
8.9%
0 53
 
7.7%
7 49
 
7.1%
8 43
 
6.3%
9 41
 
6.0%
Other Punctuation
ValueCountFrequency (%)
, 64
97.0%
? 1
 
1.5%
＆ 1
 
1.5%
Uppercase Letter
ValueCountFrequency (%)
B 2
50.0%
C 2
50.0%
Space Separator
ValueCountFrequency (%)
781
100.0%
Open Punctuation
ValueCountFrequency (%)
( 189
100.0%
Close Punctuation
ValueCountFrequency (%)
) 189
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 17
100.0%
Math Symbol
ValueCountFrequency (%)
~ 12
100.0%
Letter Number
ValueCountFrequency (%)
Ⅱ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 3030
60.9%
Common 1940
39.0%
Latin 5
 
0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
부 331
10.9%
평 309
 
10.2%
천 214
 
7.1%
동 206
 
6.8%
인 198
 
6.5%
광 195
 
6.4%
시 195
 
6.4%
구 192
 
6.3%
로 192
 
6.3%
역 189
 
6.2%
Other values (106) 809
26.7%
Common
ValueCountFrequency (%)
781
40.3%
( 189
 
9.7%
) 189
 
9.7%
1 133
 
6.9%
2 83
 
4.3%
3 78
 
4.0%
6 74
 
3.8%
5 71
 
3.7%
, 64
 
3.3%
4 61
 
3.1%
Other values (8) 217
 
11.2%
Latin
ValueCountFrequency (%)
B 2
40.0%
C 2
40.0%
Ⅱ 1
20.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 3030
60.9%
ASCII 1943
39.1%
None 1
 
< 0.1%
Number Forms 1
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
781
40.2%
( 189
 
9.7%
) 189
 
9.7%
1 133
 
6.8%
2 83
 
4.3%
3 78
 
4.0%
6 74
 
3.8%
5 71
 
3.7%
, 64
 
3.3%
4 61
 
3.1%
Other values (9) 220
 
11.3%
Hangul
ValueCountFrequency (%)
부 331
10.9%
평 309
 
10.2%
천 214
 
7.1%
동 206
 
6.8%
인 198
 
6.5%
광 195
 
6.4%
시 195
 
6.4%
구 192
 
6.3%
로 192
 
6.3%
역 189
 
6.2%
Other values (106) 809
26.7%
None
ValueCountFrequency (%)
＆ 1
100.0%
Number Forms
ValueCountFrequency (%)
Ⅱ 1
100.0%

Interactions

2024-04-18T03:27:09.165775image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Missing values

2024-04-18T03:27:09.253925image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-04-18T03:27:09.310146image/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

연번시설명주소
01부평구청역(7호선)인천광역시 부평구 부평대로 지하189 (청천동)
12굴포천역(7호선)인천광역시 부평구 길주로 지하 623 (삼산동)
23삼산체육관역(7호선)인천광역시 부평구 길주로 지하 713 (삼산동)
34부평역(인천1호선)인천광역시 부평구 광장로 지하15(부평동)
45갈산역(인천1호선)인천광역시 부평구 부평대로 지하286 (갈산동)
56부평시장역(인천1호선)인천광역시 부평구 부평대로 지하69(부평동)
67동수역(인천1호선)인천광역시 부평구 경인로 지하877(부평동)
78부평삼거리역(인천1호선)인천광역시 부평구 경인로 지하765(십정동)
89부평구청역(인천1호선)인천광역시 부평구 부평대로 지하189 (청천동)
910부평역(국철)인천광역시 부평구 광장로 지하15(부평동)
연번시설명주소
194195인천성모병원인천광역시 부평구 동수로 56 (부평동)
195196부평한라비발디인천광역시 부평구 대정로 7(부평동)
196197인천테크노밸리U1센터지점인천광역시 부평구 주부토로 236(갈산동)
197198부평우림라이온스벨리인천광역시 부평구 부평대로 283 (청천동)
198199갈산24시불가마사우나인천광역시 부평구 주부토로 231 (갈산동)
199200대박사우나인천광역시 부평구 경인로 1038, 지하1층 (부개동, 그린힐)
200201전방자수정비치사우나인천광역시 부평구 안남로 261, 지하1층(산곡동, 전방프라자)
201202수랜드사우나인천광역시 부평구 원적로 434, 6, 7층 (산곡동, 혜성프라자)
202203천제연불가마사우나인천광역시 부평구 부평북로 448, 4층~6층 (삼산동, 로얄프라자)
203204건영사우나인천광역시 부평구 부흥로304번길 17 (부평동, 건영캐스빌)