Overview

Dataset statistics

Number of variables6
Number of observations517
Missing cells171
Missing cells (%)5.5%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory24.9 KiB
Average record size in memory49.3 B

Variable types

Numeric1
Text3
Categorical1
DateTime1

Dataset

Description경기도 남양주시 관내에 등록된 집단급식소 데이터로 급식소명, 소재지도로명주소, 급식소 구분, 전화번호 등의 항목을 제공합니다.
Author경기도 남양주시
URLhttps://www.data.go.kr/data/15088395/fileData.do

Alerts

데이터기준일자 has constant value ""Constant
소재지(도로명) has 42 (8.1%) missing valuesMissing
소재지전화 has 129 (25.0%) missing valuesMissing
연번 has unique valuesUnique

Reproduction

Analysis started2023-12-12 22:05:21.556811
Analysis finished2023-12-12 22:05:22.584080
Duration1.03 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

연번
Real number (ℝ)

UNIQUE 

Distinct517
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean259
Minimum1
Maximum517
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size4.7 KiB
2023-12-13T07:05:22.664639image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile26.8
Q1130
median259
Q3388
95-th percentile491.2
Maximum517
Range516
Interquartile range (IQR)258

Descriptive statistics

Standard deviation149.38931
Coefficient of variation (CV)0.57679271
Kurtosis-1.2
Mean259
Median Absolute Deviation (MAD)129
Skewness0
Sum133903
Variance22317.167
MonotonicityStrictly increasing
2023-12-13T07:05:23.093879image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 1
 
0.2%
325 1
 
0.2%
355 1
 
0.2%
354 1
 
0.2%
353 1
 
0.2%
352 1
 
0.2%
351 1
 
0.2%
350 1
 
0.2%
349 1
 
0.2%
348 1
 
0.2%
Other values (507) 507
98.1%
ValueCountFrequency (%)
1 1
0.2%
2 1
0.2%
3 1
0.2%
4 1
0.2%
5 1
0.2%
6 1
0.2%
7 1
0.2%
8 1
0.2%
9 1
0.2%
10 1
0.2%
ValueCountFrequency (%)
517 1
0.2%
516 1
0.2%
515 1
0.2%
514 1
0.2%
513 1
0.2%
512 1
0.2%
511 1
0.2%
510 1
0.2%
509 1
0.2%
508 1
0.2%

업소명
Text

Distinct512
Distinct (%)99.0%
Missing0
Missing (%)0.0%
Memory size4.2 KiB
2023-12-13T07:05:23.315111image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length24
Median length19
Mean length7.8588008
Min length3

Characters and Unicode

Total characters4063
Distinct characters352
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

Unique509 ?
Unique (%)98.5%

Sample

1st row신신상사집단급식소
2nd row서울리조트집단급식소
3rd row답내초등학교
4th row양정초등학교
5th row금곡고등학교
ValueCountFrequency (%)
어린이집 26
 
4.3%
시립 10
 
1.6%
주식회사 8
 
1.3%
남양주 5
 
0.8%
주)대원운수 4
 
0.7%
구내식당 3
 
0.5%
집단급식소 2
 
0.3%
주)이마트 2
 
0.3%
양오초등학교 2
 
0.3%
의료법인 2
 
0.3%
Other values (545) 547
89.5%
2023-12-13T07:05:23.724129image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
이 236
 
5.8%
집 203
 
5.0%
어 200
 
4.9%
린 199
 
4.9%
원 146
 
3.6%
학 142
 
3.5%
교 139
 
3.4%
양 100
 
2.5%
94
 
2.3%
등 90
 
2.2%
Other values (342) 2514
61.9%

Most occurring categories

ValueCountFrequency (%)
Other Letter 3882
95.5%
Space Separator 94
 
2.3%
Close Punctuation 33
 
0.8%
Open Punctuation 32
 
0.8%
Uppercase Letter 11
 
0.3%
Decimal Number 8
 
0.2%
Lowercase Letter 2
 
< 0.1%
Dash Punctuation 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
이 236
 
6.1%
집 203
 
5.2%
어 200
 
5.2%
린 199
 
5.1%
원 146
 
3.8%
학 142
 
3.7%
교 139
 
3.6%
양 100
 
2.6%
등 90
 
2.3%
주 86
 
2.2%
Other values (327) 2341
60.3%
Uppercase Letter
ValueCountFrequency (%)
A 3
27.3%
S 2
18.2%
E 1
 
9.1%
C 1
 
9.1%
P 1
 
9.1%
H 1
 
9.1%
L 1
 
9.1%
D 1
 
9.1%
Decimal Number
ValueCountFrequency (%)
2 4
50.0%
1 4
50.0%
Space Separator
ValueCountFrequency (%)
94
100.0%
Close Punctuation
ValueCountFrequency (%)
) 33
100.0%
Open Punctuation
ValueCountFrequency (%)
( 32
100.0%
Lowercase Letter
ValueCountFrequency (%)
e 2
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 3882
95.5%
Common 168
 
4.1%
Latin 13
 
0.3%

Most frequent character per script

Hangul
ValueCountFrequency (%)
이 236
 
6.1%
집 203
 
5.2%
어 200
 
5.2%
린 199
 
5.1%
원 146
 
3.8%
학 142
 
3.7%
교 139
 
3.6%
양 100
 
2.6%
등 90
 
2.3%
주 86
 
2.2%
Other values (327) 2341
60.3%
Latin
ValueCountFrequency (%)
A 3
23.1%
S 2
15.4%
e 2
15.4%
E 1
 
7.7%
C 1
 
7.7%
P 1
 
7.7%
H 1
 
7.7%
L 1
 
7.7%
D 1
 
7.7%
Common
ValueCountFrequency (%)
94
56.0%
) 33
 
19.6%
( 32
 
19.0%
2 4
 
2.4%
1 4
 
2.4%
- 1
 
0.6%

Most occurring blocks

ValueCountFrequency (%)
Hangul 3882
95.5%
ASCII 181
 
4.5%

Most frequent character per block

Hangul
ValueCountFrequency (%)
이 236
 
6.1%
집 203
 
5.2%
어 200
 
5.2%
린 199
 
5.1%
원 146
 
3.8%
학 142
 
3.7%
교 139
 
3.6%
양 100
 
2.6%
등 90
 
2.3%
주 86
 
2.2%
Other values (327) 2341
60.3%
ASCII
ValueCountFrequency (%)
94
51.9%
) 33
 
18.2%
( 32
 
17.7%
2 4
 
2.2%
1 4
 
2.2%
A 3
 
1.7%
S 2
 
1.1%
e 2
 
1.1%
E 1
 
0.6%
C 1
 
0.6%
Other values (5) 5
 
2.8%

소재지(도로명)
Text

MISSING 

Distinct467
Distinct (%)98.3%
Missing42
Missing (%)8.1%
Memory size4.2 KiB
2023-12-13T07:05:24.023127image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length53
Median length44
Mean length27.945263
Min length19

Characters and Unicode

Total characters13274
Distinct characters288
Distinct categories11 ?
Distinct scripts3 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique459 ?
Unique (%)96.6%

Sample

1st row경기도 남양주시 호평로68번길 68-142 (호평동)
2nd row경기도 남양주시 경춘로 468-33 (다산동)
3rd row경기도 남양주시 경춘로 1037 (금곡동 남양주시청)
4th row경기도 남양주시 경춘로 933 (금곡동)
5th row경기도 남양주시 진접읍 광릉내로82번길 29
ValueCountFrequency (%)
경기도 475
 
17.3%
남양주시 475
 
17.3%
진접읍 79
 
2.9%
화도읍 69
 
2.5%
다산동 55
 
2.0%
1층 50
 
1.8%
별내동 47
 
1.7%
호평동 37
 
1.4%
오남읍 32
 
1.2%
와부읍 31
 
1.1%
Other values (738) 1389
50.7%
2023-12-13T07:05:24.483888image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
2264
 
17.1%
남 566
 
4.3%
도 561
 
4.2%
경 542
 
4.1%
주 516
 
3.9%
양 510
 
3.8%
1 497
 
3.7%
시 489
 
3.7%
기 479
 
3.6%
로 470
 
3.5%
Other values (278) 6380
48.1%

Most occurring categories

ValueCountFrequency (%)
Other Letter 8201
61.8%
Space Separator 2264
 
17.1%
Decimal Number 2195
 
16.5%
Open Punctuation 222
 
1.7%
Close Punctuation 222
 
1.7%
Dash Punctuation 147
 
1.1%
Uppercase Letter 16
 
0.1%
Lowercase Letter 2
 
< 0.1%
Other Punctuation 2
 
< 0.1%
Math Symbol 2
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
남 566
 
6.9%
도 561
 
6.8%
경 542
 
6.6%
주 516
 
6.3%
양 510
 
6.2%
시 489
 
6.0%
기 479
 
5.8%
로 470
 
5.7%
동 257
 
3.1%
읍 250
 
3.0%
Other values (249) 3561
43.4%
Uppercase Letter
ValueCountFrequency (%)
E 3
18.8%
L 3
18.8%
B 2
12.5%
H 1
 
6.2%
C 1
 
6.2%
Z 1
 
6.2%
P 1
 
6.2%
S 1
 
6.2%
N 1
 
6.2%
W 1
 
6.2%
Decimal Number
ValueCountFrequency (%)
1 497
22.6%
2 338
15.4%
3 233
10.6%
5 202
9.2%
4 191
 
8.7%
0 166
 
7.6%
7 147
 
6.7%
8 143
 
6.5%
6 140
 
6.4%
9 138
 
6.3%
Space Separator
ValueCountFrequency (%)
2264
100.0%
Open Punctuation
ValueCountFrequency (%)
( 222
100.0%
Close Punctuation
ValueCountFrequency (%)
) 222
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 147
100.0%
Lowercase Letter
ValueCountFrequency (%)
e 2
100.0%
Other Punctuation
ValueCountFrequency (%)
@ 2
100.0%
Math Symbol
ValueCountFrequency (%)
~ 2
100.0%
Other Symbol
ValueCountFrequency (%)
㈜ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 8202
61.8%
Common 5054
38.1%
Latin 18
 
0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
남 566
 
6.9%
도 561
 
6.8%
경 542
 
6.6%
주 516
 
6.3%
양 510
 
6.2%
시 489
 
6.0%
기 479
 
5.8%
로 470
 
5.7%
동 257
 
3.1%
읍 250
 
3.0%
Other values (250) 3562
43.4%
Common
ValueCountFrequency (%)
2264
44.8%
1 497
 
9.8%
2 338
 
6.7%
3 233
 
4.6%
( 222
 
4.4%
) 222
 
4.4%
5 202
 
4.0%
4 191
 
3.8%
0 166
 
3.3%
- 147
 
2.9%
Other values (6) 572
 
11.3%
Latin
ValueCountFrequency (%)
E 3
16.7%
L 3
16.7%
e 2
11.1%
B 2
11.1%
H 1
 
5.6%
C 1
 
5.6%
Z 1
 
5.6%
P 1
 
5.6%
S 1
 
5.6%
N 1
 
5.6%
Other values (2) 2
11.1%

Most occurring blocks

ValueCountFrequency (%)
Hangul 8201
61.8%
ASCII 5072
38.2%
None 1
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
2264
44.6%
1 497
 
9.8%
2 338
 
6.7%
3 233
 
4.6%
( 222
 
4.4%
) 222
 
4.4%
5 202
 
4.0%
4 191
 
3.8%
0 166
 
3.3%
- 147
 
2.9%
Other values (18) 590
 
11.6%
Hangul
ValueCountFrequency (%)
남 566
 
6.9%
도 561
 
6.8%
경 542
 
6.6%
주 516
 
6.3%
양 510
 
6.2%
시 489
 
6.0%
기 479
 
5.8%
로 470
 
5.7%
동 257
 
3.1%
읍 250
 
3.0%
Other values (249) 3561
43.4%
None
ValueCountFrequency (%)
㈜ 1
100.0%

소재지전화
Text

MISSING 

Distinct384
Distinct (%)99.0%
Missing129
Missing (%)25.0%
Memory size4.2 KiB
2023-12-13T07:05:24.783102image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length13
Median length12
Mean length12.015464
Min length11

Characters and Unicode

Total characters4662
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

Unique380 ?
Unique (%)97.9%

Sample

1st row031-591-1204
2nd row031-591-1230
3rd row031-593-9569
4th row031-554-2911
5th row031-592-7048
ValueCountFrequency (%)
031-592-7642 2
 
0.5%
031-594-2299 2
 
0.5%
031-576-7447 2
 
0.5%
031-559-5353 2
 
0.5%
031-577-5761 1
 
0.3%
031-572-7300 1
 
0.3%
031-566-2980 1
 
0.3%
031-521-5988 1
 
0.3%
031-521-9473 1
 
0.3%
031-595-1675 1
 
0.3%
Other values (374) 374
96.4%
2023-12-13T07:05:25.294297image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
- 776
16.6%
0 672
14.4%
1 616
13.2%
5 596
12.8%
3 581
12.5%
7 326
7.0%
2 279
 
6.0%
9 264
 
5.7%
4 199
 
4.3%
6 190
 
4.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 3886
83.4%
Dash Punctuation 776
 
16.6%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 672
17.3%
1 616
15.9%
5 596
15.3%
3 581
15.0%
7 326
8.4%
2 279
7.2%
9 264
 
6.8%
4 199
 
5.1%
6 190
 
4.9%
8 163
 
4.2%
Dash Punctuation
ValueCountFrequency (%)
- 776
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 4662
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
- 776
16.6%
0 672
14.4%
1 616
13.2%
5 596
12.8%
3 581
12.5%
7 326
7.0%
2 279
 
6.0%
9 264
 
5.7%
4 199
 
4.3%
6 190
 
4.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 4662
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
- 776
16.6%
0 672
14.4%
1 616
13.2%
5 596
12.8%
3 581
12.5%
7 326
7.0%
2 279
 
6.0%
9 264
 
5.7%
4 199
 
4.3%
6 190
 
4.1%

급식소종류
Categorical

Distinct12
Distinct (%)2.3%
Missing0
Missing (%)0.0%
Memory size4.2 KiB
기타
122 
<NA>
113 
어린이집
74 
학교
50 
사회복지시설
50 
Other values (7)
108 

Length

Max length6
Median length4
Mean length3.4003868
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row사업체
2nd row사업체
3rd row<NA>
4th row<NA>
5th row기타

Common Values

ValueCountFrequency (%)
기타 122
23.6%
<NA> 113
21.9%
어린이집 74
14.3%
학교 50
9.7%
사회복지시설 50
9.7%
병원 31
 
6.0%
사업체 21
 
4.1%
산업체 16
 
3.1%
교육훈련기관 14
 
2.7%
유치원 11
 
2.1%
Other values (2) 15
 
2.9%

Length

2023-12-13T07:05:25.452226image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
기타 122
23.6%
na 113
21.9%
어린이집 74
14.3%
학교 50
9.7%
사회복지시설 50
9.7%
병원 31
 
6.0%
사업체 21
 
4.1%
산업체 16
 
3.1%
교육훈련기관 14
 
2.7%
유치원 11
 
2.1%
Other values (2) 15
 
2.9%

데이터기준일자
Date

CONSTANT 

Distinct1
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size4.2 KiB
Minimum2022-09-01 00:00:00
Maximum2022-09-01 00:00:00
2023-12-13T07:05:25.582183image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T07:05:25.688989image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=1)

Interactions

2023-12-13T07:05:22.184760image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-13T07:05:25.777684image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연번급식소종류
연번1.0000.603
급식소종류0.6031.000
2023-12-13T07:05:25.899758image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연번급식소종류
연번1.0000.308
급식소종류0.3081.000

Missing values

2023-12-13T07:05:22.333317image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-13T07:05:22.431055image/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.
2023-12-13T07:05:22.531954image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
The correlation heatmap measures nullity correlation: how strongly the presence or absence of one variable affects the presence of another.

Sample

연번업소명소재지(도로명)소재지전화급식소종류데이터기준일자
01신신상사집단급식소<NA>031-591-1204사업체2022-09-01
12서울리조트집단급식소경기도 남양주시 호평로68번길 68-142 (호평동)031-591-1230사업체2022-09-01
23답내초등학교<NA>031-593-9569<NA>2022-09-01
34양정초등학교경기도 남양주시 경춘로 468-33 (다산동)031-554-2911<NA>2022-09-01
45금곡고등학교<NA>031-592-7048기타2022-09-01
56남양주시청경기도 남양주시 경춘로 1037 (금곡동 남양주시청)031-590-2716기타2022-09-01
67마석초등학교<NA>031-593-9847기타2022-09-01
78양병원급식소경기도 남양주시 경춘로 933 (금곡동)031-590-9361<NA>2022-09-01
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