Overview

Dataset statistics

Number of variables6
Number of observations155
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory7.5 KiB
Average record size in memory49.8 B

Variable types

Numeric1
Categorical2
Text3

Dataset

Description서울특별시 강북구의 집단급식소(위탁) 현황 (연번 자료, 업소명 자료, 소재지 자료, 연락처 자료)등의 데이터를 제공합니다.
Author서울특별시 강북구
URLhttps://www.data.go.kr/data/15034597/fileData.do

Alerts

업종명 has constant value ""Constant
데이터 기준일자 has constant value ""Constant
연번 has unique valuesUnique

Reproduction

Analysis started2024-03-14 12:44:29.772396
Analysis finished2024-03-14 12:44:31.045750
Duration1.27 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

연번
Real number (ℝ)

UNIQUE 

Distinct155
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean78
Minimum1
Maximum155
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.5 KiB
2024-03-14T21:44:31.258215image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile8.7
Q139.5
median78
Q3116.5
95-th percentile147.3
Maximum155
Range154
Interquartile range (IQR)77

Descriptive statistics

Standard deviation44.888751
Coefficient of variation (CV)0.57549681
Kurtosis-1.2
Mean78
Median Absolute Deviation (MAD)39
Skewness0
Sum12090
Variance2015
MonotonicityStrictly increasing
2024-03-14T21:44:31.910343image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 1
 
0.6%
108 1
 
0.6%
101 1
 
0.6%
102 1
 
0.6%
103 1
 
0.6%
104 1
 
0.6%
105 1
 
0.6%
106 1
 
0.6%
107 1
 
0.6%
109 1
 
0.6%
Other values (145) 145
93.5%
ValueCountFrequency (%)
1 1
0.6%
2 1
0.6%
3 1
0.6%
4 1
0.6%
5 1
0.6%
6 1
0.6%
7 1
0.6%
8 1
0.6%
9 1
0.6%
10 1
0.6%
ValueCountFrequency (%)
155 1
0.6%
154 1
0.6%
153 1
0.6%
152 1
0.6%
151 1
0.6%
150 1
0.6%
149 1
0.6%
148 1
0.6%
147 1
0.6%
146 1
0.6%

업종명
Categorical

CONSTANT 

Distinct1
Distinct (%)0.6%
Missing0
Missing (%)0.0%
Memory size1.3 KiB
집단급식소
155 

Length

Max length5
Median length5
Mean length5
Min length5

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
집단급식소 155
100.0%

Length

2024-03-14T21:44:32.204330image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-14T21:44:32.380470image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
집단급식소 155
100.0%

업소명
Text

Distinct154
Distinct (%)99.4%
Missing0
Missing (%)0.0%
Memory size1.3 KiB
2024-03-14T21:44:33.328690image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length30
Median length15
Mean length7.916129
Min length3

Characters and Unicode

Total characters1227
Distinct characters212
Distinct categories7 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique153 ?
Unique (%)98.7%

Sample

1st row삼양교통
2nd row대한병원
3rd row한빛맹아원
4th row영신여객
5th row강북구청후생복지원
ValueCountFrequency (%)
어린이집 4
 
2.1%
구립 4
 
2.1%
주식회사 3
 
1.6%
동아운수 2
 
1.1%
햇빛병원 2
 
1.1%
사단법인 2
 
1.1%
서울현대병원 2
 
1.1%
부설 2
 
1.1%
농협문화복지재단 1
 
0.5%
롯데쇼핑(주 1
 
0.5%
Other values (165) 165
87.8%
2024-03-14T21:44:34.564713image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
이 57
 
4.6%
린 48
 
3.9%
집 48
 
3.9%
어 47
 
3.8%
교 41
 
3.3%
원 40
 
3.3%
학 38
 
3.1%
33
 
2.7%
북 27
 
2.2%
동 23
 
1.9%
Other values (202) 825
67.2%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1171
95.4%
Space Separator 33
 
2.7%
Close Punctuation 7
 
0.6%
Open Punctuation 7
 
0.6%
Decimal Number 6
 
0.5%
Uppercase Letter 2
 
0.2%
Other Punctuation 1
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
이 57
 
4.9%
린 48
 
4.1%
집 48
 
4.1%
어 47
 
4.0%
교 41
 
3.5%
원 40
 
3.4%
학 38
 
3.2%
북 27
 
2.3%
동 23
 
2.0%
구 23
 
2.0%
Other values (192) 779
66.5%
Decimal Number
ValueCountFrequency (%)
2 3
50.0%
5 1
 
16.7%
3 1
 
16.7%
1 1
 
16.7%
Uppercase Letter
ValueCountFrequency (%)
T 1
50.0%
K 1
50.0%
Space Separator
ValueCountFrequency (%)
33
100.0%
Close Punctuation
ValueCountFrequency (%)
) 7
100.0%
Open Punctuation
ValueCountFrequency (%)
( 7
100.0%
Other Punctuation
ValueCountFrequency (%)
. 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1171
95.4%
Common 54
 
4.4%
Latin 2
 
0.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
이 57
 
4.9%
린 48
 
4.1%
집 48
 
4.1%
어 47
 
4.0%
교 41
 
3.5%
원 40
 
3.4%
학 38
 
3.2%
북 27
 
2.3%
동 23
 
2.0%
구 23
 
2.0%
Other values (192) 779
66.5%
Common
ValueCountFrequency (%)
33
61.1%
) 7
 
13.0%
( 7
 
13.0%
2 3
 
5.6%
5 1
 
1.9%
3 1
 
1.9%
. 1
 
1.9%
1 1
 
1.9%
Latin
ValueCountFrequency (%)
T 1
50.0%
K 1
50.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1171
95.4%
ASCII 56
 
4.6%

Most frequent character per block

Hangul
ValueCountFrequency (%)
이 57
 
4.9%
린 48
 
4.1%
집 48
 
4.1%
어 47
 
4.0%
교 41
 
3.5%
원 40
 
3.4%
학 38
 
3.2%
북 27
 
2.3%
동 23
 
2.0%
구 23
 
2.0%
Other values (192) 779
66.5%
ASCII
ValueCountFrequency (%)
33
58.9%
) 7
 
12.5%
( 7
 
12.5%
2 3
 
5.4%
5 1
 
1.8%
3 1
 
1.8%
. 1
 
1.8%
1 1
 
1.8%
T 1
 
1.8%
K 1
 
1.8%

소재지(도로명)
Text

Distinct150
Distinct (%)96.8%
Missing0
Missing (%)0.0%
Memory size1.3 KiB
2024-03-14T21:44:35.731910image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length46
Median length40
Mean length29.251613
Min length21

Characters and Unicode

Total characters4534
Distinct characters181
Distinct categories8 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique145 ?
Unique (%)93.5%

Sample

1st row서울특별시 강북구 삼양로173길 12 (우이동)
2nd row서울특별시 강북구 도봉로 301 (수유동)
3rd row서울특별시 강북구 삼양로73가길 47 (수유동)
4th row서울특별시 강북구 삼양로173길 22 (우이동)
5th row서울특별시 강북구 도봉로89길 13 (수유동)
ValueCountFrequency (%)
서울특별시 155
17.6%
강북구 155
17.6%
미아동 57
 
6.5%
수유동 50
 
5.7%
번동 27
 
3.1%
도봉로 14
 
1.6%
우이동 12
 
1.4%
1층 11
 
1.2%
인수봉로 10
 
1.1%
지하1층 8
 
0.9%
Other values (267) 383
43.4%
2024-03-14T21:44:37.255697image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
727
 
16.0%
서 169
 
3.7%
동 168
 
3.7%
울 167
 
3.7%
북 166
 
3.7%
강 163
 
3.6%
1 162
 
3.6%
( 161
 
3.6%
) 161
 
3.6%
시 158
 
3.5%
Other values (171) 2332
51.4%

Most occurring categories

ValueCountFrequency (%)
Other Letter 2734
60.3%
Space Separator 727
 
16.0%
Decimal Number 645
 
14.2%
Open Punctuation 161
 
3.6%
Close Punctuation 161
 
3.6%
Other Punctuation 81
 
1.8%
Uppercase Letter 13
 
0.3%
Dash Punctuation 12
 
0.3%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
서 169
 
6.2%
동 168
 
6.1%
울 167
 
6.1%
북 166
 
6.1%
강 163
 
6.0%
시 158
 
5.8%
구 157
 
5.7%
별 156
 
5.7%
특 155
 
5.7%
로 155
 
5.7%
Other values (147) 1120
41.0%
Decimal Number
ValueCountFrequency (%)
1 162
25.1%
2 79
12.2%
4 68
10.5%
9 66
10.2%
3 57
 
8.8%
7 55
 
8.5%
5 50
 
7.8%
0 41
 
6.4%
6 36
 
5.6%
8 31
 
4.8%
Uppercase Letter
ValueCountFrequency (%)
B 4
30.8%
K 3
23.1%
S 2
15.4%
Y 1
 
7.7%
A 1
 
7.7%
T 1
 
7.7%
P 1
 
7.7%
Other Punctuation
ValueCountFrequency (%)
, 75
92.6%
. 5
 
6.2%
@ 1
 
1.2%
Space Separator
ValueCountFrequency (%)
727
100.0%
Open Punctuation
ValueCountFrequency (%)
( 161
100.0%
Close Punctuation
ValueCountFrequency (%)
) 161
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 12
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 2734
60.3%
Common 1787
39.4%
Latin 13
 
0.3%

Most frequent character per script

Hangul
ValueCountFrequency (%)
서 169
 
6.2%
동 168
 
6.1%
울 167
 
6.1%
북 166
 
6.1%
강 163
 
6.0%
시 158
 
5.8%
구 157
 
5.7%
별 156
 
5.7%
특 155
 
5.7%
로 155
 
5.7%
Other values (147) 1120
41.0%
Common
ValueCountFrequency (%)
727
40.7%
1 162
 
9.1%
( 161
 
9.0%
) 161
 
9.0%
2 79
 
4.4%
, 75
 
4.2%
4 68
 
3.8%
9 66
 
3.7%
3 57
 
3.2%
7 55
 
3.1%
Other values (7) 176
 
9.8%
Latin
ValueCountFrequency (%)
B 4
30.8%
K 3
23.1%
S 2
15.4%
Y 1
 
7.7%
A 1
 
7.7%
T 1
 
7.7%
P 1
 
7.7%

Most occurring blocks

ValueCountFrequency (%)
Hangul 2734
60.3%
ASCII 1800
39.7%

Most frequent character per block

ASCII
ValueCountFrequency (%)
727
40.4%
1 162
 
9.0%
( 161
 
8.9%
) 161
 
8.9%
2 79
 
4.4%
, 75
 
4.2%
4 68
 
3.8%
9 66
 
3.7%
3 57
 
3.2%
7 55
 
3.1%
Other values (14) 189
 
10.5%
Hangul
ValueCountFrequency (%)
서 169
 
6.2%
동 168
 
6.1%
울 167
 
6.1%
북 166
 
6.1%
강 163
 
6.0%
시 158
 
5.8%
구 157
 
5.7%
별 156
 
5.7%
특 155
 
5.7%
로 155
 
5.7%
Other values (147) 1120
41.0%

소재지전화
Text

Distinct129
Distinct (%)83.2%
Missing0
Missing (%)0.0%
Memory size1.3 KiB
2024-03-14T21:44:38.404367image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length13
Median length11
Mean length10.4
Min length7

Characters and Unicode

Total characters1612
Distinct characters18
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

Unique128 ?
Unique (%)82.6%

Sample

1st row02-904-0572
2nd row02-903-3231
3rd row02-989-6017
4th row02-996-3501
5th row02-903-6360
ValueCountFrequency (%)
데이터 27
 
14.8%
미집계 27
 
14.8%
02-986-6148 1
 
0.5%
02-982-6104 1
 
0.5%
02-980-3535 1
 
0.5%
02-986-2299 1
 
0.5%
02-991-4379 1
 
0.5%
070-7525-2209 1
 
0.5%
02-3397-6137 1
 
0.5%
02-993-2143 1
 
0.5%
Other values (120) 120
65.9%
2024-03-14T21:44:39.962860image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
- 256
15.9%
0 225
14.0%
9 190
11.8%
2 186
11.5%
8 115
7.1%
1 89
 
5.5%
6 82
 
5.1%
7 74
 
4.6%
5 72
 
4.5%
3 71
 
4.4%
Other values (8) 252
15.6%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 1167
72.4%
Dash Punctuation 256
 
15.9%
Other Letter 162
 
10.0%
Space Separator 27
 
1.7%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 225
19.3%
9 190
16.3%
2 186
15.9%
8 115
9.9%
1 89
 
7.6%
6 82
 
7.0%
7 74
 
6.3%
5 72
 
6.2%
3 71
 
6.1%
4 63
 
5.4%
Other Letter
ValueCountFrequency (%)
이 27
16.7%
계 27
16.7%
집 27
16.7%
미 27
16.7%
터 27
16.7%
데 27
16.7%
Dash Punctuation
ValueCountFrequency (%)
- 256
100.0%
Space Separator
ValueCountFrequency (%)
27
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 1450
90.0%
Hangul 162
 
10.0%

Most frequent character per script

Common
ValueCountFrequency (%)
- 256
17.7%
0 225
15.5%
9 190
13.1%
2 186
12.8%
8 115
7.9%
1 89
 
6.1%
6 82
 
5.7%
7 74
 
5.1%
5 72
 
5.0%
3 71
 
4.9%
Other values (2) 90
 
6.2%
Hangul
ValueCountFrequency (%)
이 27
16.7%
계 27
16.7%
집 27
16.7%
미 27
16.7%
터 27
16.7%
데 27
16.7%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1450
90.0%
Hangul 162
 
10.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
- 256
17.7%
0 225
15.5%
9 190
13.1%
2 186
12.8%
8 115
7.9%
1 89
 
6.1%
6 82
 
5.7%
7 74
 
5.1%
5 72
 
5.0%
3 71
 
4.9%
Other values (2) 90
 
6.2%
Hangul
ValueCountFrequency (%)
이 27
16.7%
계 27
16.7%
집 27
16.7%
미 27
16.7%
터 27
16.7%
데 27
16.7%

데이터 기준일자
Categorical

CONSTANT 

Distinct1
Distinct (%)0.6%
Missing0
Missing (%)0.0%
Memory size1.3 KiB
2024-01-15
155 

Length

Max length10
Median length10
Mean length10
Min length10

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2024-01-15
2nd row2024-01-15
3rd row2024-01-15
4th row2024-01-15
5th row2024-01-15

Common Values

ValueCountFrequency (%)
2024-01-15 155
100.0%

Length

2024-03-14T21:44:40.191313image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-14T21:44:40.360426image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2024-01-15 155
100.0%

Interactions

2024-03-14T21:44:30.202982image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Missing values

2024-03-14T21:44:30.559734image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-03-14T21:44:30.907752image/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

연번업종명업소명소재지(도로명)소재지전화데이터 기준일자
01집단급식소삼양교통서울특별시 강북구 삼양로173길 12 (우이동)02-904-05722024-01-15
12집단급식소대한병원서울특별시 강북구 도봉로 301 (수유동)02-903-32312024-01-15
23집단급식소한빛맹아원서울특별시 강북구 삼양로73가길 47 (수유동)02-989-60172024-01-15
34집단급식소영신여객서울특별시 강북구 삼양로173길 22 (우이동)02-996-35012024-01-15
45집단급식소강북구청후생복지원서울특별시 강북구 도봉로89길 13 (수유동)02-903-63602024-01-15
56집단급식소한성운수(주)서울특별시 강북구 한천로 939 (번동)02-981-90012024-01-15
67집단급식소동아운수서울특별시 강북구 인수봉로 145 (주)동아운수 (수유동)02-989-16732024-01-15
78집단급식소영훈초등학교서울특별시 강북구 도봉로13가길 19 (미아동)02-983-21312024-01-15
89집단급식소통일교육원서울특별시 강북구 4.19로 123, 통일교육원 (수유동)02-901-71742024-01-15
910집단급식소신일병원서울특별시 강북구 덕릉로 73 (수유동)02-903-51212024-01-15
연번업종명업소명소재지(도로명)소재지전화데이터 기준일자
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