Overview

Dataset statistics

Number of variables5
Number of observations368
Missing cells3
Missing cells (%)0.2%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory14.9 KiB
Average record size in memory41.4 B

Variable types

Numeric1
Categorical1
Text3

Dataset

Description경기도 부천시 관내의 경로당 현황으로 관할광역동명, 경로당명, 소재지주소(도로주소명), 전화번호 등의 정보를 제공합니다.
Author경기도 부천시
URLhttps://www.data.go.kr/data/15051023/fileData.do

Alerts

연번 is highly overall correlated with 관할동High correlation
관할동 is highly overall correlated with 연번High correlation
연번 has unique valuesUnique

Reproduction

Analysis started2023-12-12 12:57:41.022209
Analysis finished2023-12-12 12:57:41.614689
Duration0.59 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

연번
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct368
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean184.5
Minimum1
Maximum368
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size3.4 KiB
2023-12-12T21:57:41.681753image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile19.35
Q192.75
median184.5
Q3276.25
95-th percentile349.65
Maximum368
Range367
Interquartile range (IQR)183.5

Descriptive statistics

Standard deviation106.37669
Coefficient of variation (CV)0.57656742
Kurtosis-1.2
Mean184.5
Median Absolute Deviation (MAD)92
Skewness0
Sum67896
Variance11316
MonotonicityStrictly increasing
2023-12-12T21:57:41.810520image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 1
 
0.3%
244 1
 
0.3%
253 1
 
0.3%
252 1
 
0.3%
251 1
 
0.3%
250 1
 
0.3%
249 1
 
0.3%
248 1
 
0.3%
247 1
 
0.3%
246 1
 
0.3%
Other values (358) 358
97.3%
ValueCountFrequency (%)
1 1
0.3%
2 1
0.3%
3 1
0.3%
4 1
0.3%
5 1
0.3%
6 1
0.3%
7 1
0.3%
8 1
0.3%
9 1
0.3%
10 1
0.3%
ValueCountFrequency (%)
368 1
0.3%
367 1
0.3%
366 1
0.3%
365 1
0.3%
364 1
0.3%
363 1
0.3%
362 1
0.3%
361 1
0.3%
360 1
0.3%
359 1
0.3%

관할동
Categorical

HIGH CORRELATION 

Distinct10
Distinct (%)2.7%
Missing0
Missing (%)0.0%
Memory size3.0 KiB
신중동
57 
오정동
50 
성곡동
44 
대산동
43 
상동
38 
Other values (5)
136 

Length

Max length4
Median length3
Mean length2.9429348
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
신중동 57
15.5%
오정동 50
13.6%
성곡동 44
12.0%
대산동 43
11.7%
상동 38
10.3%
범안동 38
10.3%
부천동 37
10.1%
소사본동 30
8.2%
심곡동 18
 
4.9%
중동 13
 
3.5%

Length

2023-12-12T21:57:41.944895image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T21:57:42.067918image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
신중동 57
15.5%
오정동 50
13.6%
성곡동 44
12.0%
대산동 43
11.7%
상동 38
10.3%
범안동 38
10.3%
부천동 37
10.1%
소사본동 30
8.2%
심곡동 18
 
4.9%
중동 13
 
3.5%

경로당명
Text

Distinct360
Distinct (%)97.8%
Missing0
Missing (%)0.0%
Memory size3.0 KiB
2023-12-12T21:57:42.292814image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length19
Median length15
Mean length8.9809783
Min length5

Characters and Unicode

Total characters3305
Distinct characters253
Distinct categories9 ?
Distinct scripts3 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique355 ?
Unique (%)96.5%

Sample

1st row봄비경로당
2nd row장미경로당
3rd row진말공원경로당
4th row광장경로당
5th row중앙경로당
ValueCountFrequency (%)
공원경로당 5
 
1.3%
경로당 3
 
0.8%
중앙경로당 2
 
0.5%
장수경로당 2
 
0.5%
영화아파트경로당 2
 
0.5%
장미경로당 2
 
0.5%
범박휴먼시아 2
 
0.5%
복사골경로당 1
 
0.3%
삼익3차경로당 1
 
0.3%
신일해피트리경로당 1
 
0.3%
Other values (355) 355
94.4%
2023-12-12T21:57:42.623378image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
경 370
 
11.2%
당 368
 
11.1%
로 367
 
11.1%
아 126
 
3.8%
트 117
 
3.5%
파 104
 
3.1%
( 65
 
2.0%
) 65
 
2.0%
마 63
 
1.9%
을 62
 
1.9%
Other values (243) 1598
48.4%

Most occurring categories

ValueCountFrequency (%)
Other Letter 3055
92.4%
Decimal Number 84
 
2.5%
Open Punctuation 65
 
2.0%
Close Punctuation 65
 
2.0%
Uppercase Letter 15
 
0.5%
Lowercase Letter 8
 
0.2%
Space Separator 8
 
0.2%
Dash Punctuation 3
 
0.1%
Other Punctuation 2
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
경 370
 
12.1%
당 368
 
12.0%
로 367
 
12.0%
아 126
 
4.1%
트 117
 
3.8%
파 104
 
3.4%
마 63
 
2.1%
을 62
 
2.0%
지 56
 
1.8%
동 45
 
1.5%
Other values (220) 1377
45.1%
Decimal Number
ValueCountFrequency (%)
1 26
31.0%
2 25
29.8%
3 16
19.0%
5 6
 
7.1%
4 5
 
6.0%
6 2
 
2.4%
8 1
 
1.2%
7 1
 
1.2%
0 1
 
1.2%
9 1
 
1.2%
Uppercase Letter
ValueCountFrequency (%)
L 4
26.7%
K 3
20.0%
H 3
20.0%
S 2
13.3%
C 2
13.3%
G 1
 
6.7%
Other Punctuation
ValueCountFrequency (%)
， 1
50.0%
· 1
50.0%
Open Punctuation
ValueCountFrequency (%)
( 65
100.0%
Close Punctuation
ValueCountFrequency (%)
) 65
100.0%
Lowercase Letter
ValueCountFrequency (%)
e 8
100.0%
Space Separator
ValueCountFrequency (%)
8
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 3
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 3055
92.4%
Common 227
 
6.9%
Latin 23
 
0.7%

Most frequent character per script

Hangul
ValueCountFrequency (%)
경 370
 
12.1%
당 368
 
12.0%
로 367
 
12.0%
아 126
 
4.1%
트 117
 
3.8%
파 104
 
3.4%
마 63
 
2.1%
을 62
 
2.0%
지 56
 
1.8%
동 45
 
1.5%
Other values (220) 1377
45.1%
Common
ValueCountFrequency (%)
( 65
28.6%
) 65
28.6%
1 26
 
11.5%
2 25
 
11.0%
3 16
 
7.0%
8
 
3.5%
5 6
 
2.6%
4 5
 
2.2%
- 3
 
1.3%
6 2
 
0.9%
Other values (6) 6
 
2.6%
Latin
ValueCountFrequency (%)
e 8
34.8%
L 4
17.4%
K 3
 
13.0%
H 3
 
13.0%
S 2
 
8.7%
C 2
 
8.7%
G 1
 
4.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 3055
92.4%
ASCII 248
 
7.5%
None 2
 
0.1%

Most frequent character per block

Hangul
ValueCountFrequency (%)
경 370
 
12.1%
당 368
 
12.0%
로 367
 
12.0%
아 126
 
4.1%
트 117
 
3.8%
파 104
 
3.4%
마 63
 
2.1%
을 62
 
2.0%
지 56
 
1.8%
동 45
 
1.5%
Other values (220) 1377
45.1%
ASCII
ValueCountFrequency (%)
( 65
26.2%
) 65
26.2%
1 26
 
10.5%
2 25
 
10.1%
3 16
 
6.5%
e 8
 
3.2%
8
 
3.2%
5 6
 
2.4%
4 5
 
2.0%
L 4
 
1.6%
Other values (11) 20
 
8.1%
None
ValueCountFrequency (%)
， 1
50.0%
· 1
50.0%

도로명주소
Text

Distinct329
Distinct (%)89.4%
Missing0
Missing (%)0.0%
Memory size3.0 KiB
2023-12-12T21:57:42.897228image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length48
Median length41
Mean length25.133152
Min length17

Characters and Unicode

Total characters9249
Distinct characters196
Distinct categories9 ?
Distinct scripts3 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique291 ?
Unique (%)79.1%

Sample

1st row경기도 부천시 부흥로 369 (심곡동)
2nd row경기도 부천시 부천로53번길 64-4(심곡동)
3rd row경기도 부천시 장말로 337(심곡동)
4th row경기도 부천시 원미로7번길 42-1 (심곡동)
5th row경기도 부천시 부천로36번길 32-1(심곡동)
ValueCountFrequency (%)
경기도 368
21.9%
부천시 368
21.9%
중동로 15
 
0.9%
송내동， 14
 
0.8%
괴안동， 14
 
0.8%
도약로 13
 
0.8%
조마루로 12
 
0.7%
부흥로 10
 
0.6%
계남로 10
 
0.6%
옥산로 10
 
0.6%
Other values (608) 844
50.3%
2023-12-12T21:57:43.266017image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1362
 
14.7%
부 415
 
4.5%
천 407
 
4.4%
동 403
 
4.4%
경 391
 
4.2%
도 390
 
4.2%
시 370
 
4.0%
로 369
 
4.0%
기 368
 
4.0%
( 356
 
3.8%
Other values (186) 4418
47.8%

Most occurring categories

ValueCountFrequency (%)
Other Letter 5404
58.4%
Decimal Number 1586
 
17.1%
Space Separator 1362
 
14.7%
Open Punctuation 356
 
3.8%
Close Punctuation 355
 
3.8%
Other Punctuation 97
 
1.0%
Dash Punctuation 71
 
0.8%
Uppercase Letter 14
 
0.2%
Lowercase Letter 4
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
부 415
 
7.7%
천 407
 
7.5%
동 403
 
7.5%
경 391
 
7.2%
도 390
 
7.2%
시 370
 
6.8%
로 369
 
6.8%
기 368
 
6.8%
길 238
 
4.4%
번 216
 
4.0%
Other values (162) 1837
34.0%
Decimal Number
ValueCountFrequency (%)
1 318
20.1%
2 243
15.3%
3 169
10.7%
6 146
9.2%
4 145
9.1%
0 135
8.5%
7 134
8.4%
5 118
 
7.4%
8 112
 
7.1%
9 66
 
4.2%
Uppercase Letter
ValueCountFrequency (%)
L 4
28.6%
H 4
28.6%
C 2
14.3%
B 2
14.3%
K 1
 
7.1%
A 1
 
7.1%
Lowercase Letter
ValueCountFrequency (%)
e 2
50.0%
s 1
25.0%
k 1
25.0%
Space Separator
ValueCountFrequency (%)
1362
100.0%
Open Punctuation
ValueCountFrequency (%)
( 356
100.0%
Close Punctuation
ValueCountFrequency (%)
) 355
100.0%
Other Punctuation
ValueCountFrequency (%)
， 97
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 71
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 5404
58.4%
Common 3827
41.4%
Latin 18
 
0.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
부 415
 
7.7%
천 407
 
7.5%
동 403
 
7.5%
경 391
 
7.2%
도 390
 
7.2%
시 370
 
6.8%
로 369
 
6.8%
기 368
 
6.8%
길 238
 
4.4%
번 216
 
4.0%
Other values (162) 1837
34.0%
Common
ValueCountFrequency (%)
1362
35.6%
( 356
 
9.3%
) 355
 
9.3%
1 318
 
8.3%
2 243
 
6.3%
3 169
 
4.4%
6 146
 
3.8%
4 145
 
3.8%
0 135
 
3.5%
7 134
 
3.5%
Other values (5) 464
 
12.1%
Latin
ValueCountFrequency (%)
L 4
22.2%
H 4
22.2%
C 2
11.1%
B 2
11.1%
e 2
11.1%
s 1
 
5.6%
k 1
 
5.6%
K 1
 
5.6%
A 1
 
5.6%

Most occurring blocks

ValueCountFrequency (%)
Hangul 5404
58.4%
ASCII 3748
40.5%
None 97
 
1.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1362
36.3%
( 356
 
9.5%
) 355
 
9.5%
1 318
 
8.5%
2 243
 
6.5%
3 169
 
4.5%
6 146
 
3.9%
4 145
 
3.9%
0 135
 
3.6%
7 134
 
3.6%
Other values (13) 385
 
10.3%
Hangul
ValueCountFrequency (%)
부 415
 
7.7%
천 407
 
7.5%
동 403
 
7.5%
경 391
 
7.2%
도 390
 
7.2%
시 370
 
6.8%
로 369
 
6.8%
기 368
 
6.8%
길 238
 
4.4%
번 216
 
4.0%
Other values (162) 1837
34.0%
None
ValueCountFrequency (%)
， 97
100.0%

전화번호
Text

Distinct363
Distinct (%)99.5%
Missing3
Missing (%)0.8%
Memory size3.0 KiB
2023-12-12T21:57:43.499687image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length13
Median length12
Mean length12.010959
Min length12

Characters and Unicode

Total characters4384
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

Unique361 ?
Unique (%)98.9%

Sample

1st row032-651-8939
2nd row032-613-6393
3rd row032-668-2434
4th row032-611-7851
5th row032-665-9939
ValueCountFrequency (%)
032-681-3003 2
 
0.5%
032-683-3004 2
 
0.5%
032-219-7600 1
 
0.3%
032-344-7889 1
 
0.3%
032-348-8033 1
 
0.3%
032-342-0420 1
 
0.3%
032-341-6436 1
 
0.3%
032-341-8400 1
 
0.3%
032-344-7402 1
 
0.3%
032-342-3887 1
 
0.3%
Other values (353) 353
96.7%
2023-12-12T21:57:43.956810image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
3 730
16.7%
- 730
16.7%
2 634
14.5%
0 569
13.0%
6 393
9.0%
1 246
 
5.6%
7 246
 
5.6%
4 245
 
5.6%
5 232
 
5.3%
8 213
 
4.9%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 3654
83.3%
Dash Punctuation 730
 
16.7%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
3 730
20.0%
2 634
17.4%
0 569
15.6%
6 393
10.8%
1 246
 
6.7%
7 246
 
6.7%
4 245
 
6.7%
5 232
 
6.3%
8 213
 
5.8%
9 146
 
4.0%
Dash Punctuation
ValueCountFrequency (%)
- 730
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 4384
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
3 730
16.7%
- 730
16.7%
2 634
14.5%
0 569
13.0%
6 393
9.0%
1 246
 
5.6%
7 246
 
5.6%
4 245
 
5.6%
5 232
 
5.3%
8 213
 
4.9%

Most occurring blocks

ValueCountFrequency (%)
ASCII 4384
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
3 730
16.7%
- 730
16.7%
2 634
14.5%
0 569
13.0%
6 393
9.0%
1 246
 
5.6%
7 246
 
5.6%
4 245
 
5.6%
5 232
 
5.3%
8 213
 
4.9%

Interactions

2023-12-12T21:57:41.328175image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-12T21:57:44.074727image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연번관할동
연번1.0000.971
관할동0.9711.000
2023-12-12T21:57:44.175722image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연번관할동
연번1.0000.705
관할동0.7051.000

Missing values

2023-12-12T21:57:41.468466image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-12T21:57:41.578856image/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

연번관할동경로당명도로명주소전화번호
01심곡동봄비경로당경기도 부천시 부흥로 369 (심곡동)032-651-8939
12심곡동장미경로당경기도 부천시 부천로53번길 64-4(심곡동)032-613-6393
23심곡동진말공원경로당경기도 부천시 장말로 337(심곡동)032-668-2434
34심곡동광장경로당경기도 부천시 원미로7번길 42-1 (심곡동)032-611-7851
45심곡동중앙경로당경기도 부천시 부천로36번길 32-1(심곡동)032-665-9939
56심곡동진말경로당경기도 부천시 신흥로56번길 30(심곡동)032-651-4526
67심곡동먹적골경로당경기도 부천시 장말로278번길 7 (심곡동)032-664-7479
78심곡동먹적골공원경로당경기도 부천시 신흥로73번길 75(심곡동)032-652-9783
89심곡동천사경로당경기도 부천시 신흥로45번길 36 (심곡동)032-651-8721
910심곡동해바라기경로당경기도 부천시 심중로8번길 8(심곡동)032-664-0411
연번관할동경로당명도로명주소전화번호
358359오정동삼두아파트경로당경기도 부천시 오정로 252번길 56-16(오정동)032-676-3372
359360오정동오정경로당경기도 부천시 오정로244번길 19(오정동)032-677-5861
360361오정동오정(여)경로당경기도 부천시 오정로244번길 19(오정동)032-679-1449
361362오정동오정제1(남)경로당경기도 부천시 부천로 456번길 52(오정동)032-681-9703
362363오정동오정제1(여)경로당경기도 부천시 부천로 456번길 52(오정동)032-671-6573
363364오정동삼성경로당경기도 부천시 오정로 212번길 22(오정동)032-671-0248
364365오정동형제사랑방경로당경기도 부천시 상오정로 94번길 42-1(오정동)032-672-7383
365366오정동오정휴먼시아아파트1단지경로당경기도 부천시 오정로 251번길 39(오정동) 106동032-219-7500
366367오정동오정휴먼시아아파트2단지경로당경기도 부천시 오정로 253(오정동)032-219-7600
367368오정동오정휴먼시아아파트3단지경로당경기도 부천시 오정로 289(오정동)032-676-8537