Overview

Dataset statistics

Number of variables13
Number of observations72
Missing cells372
Missing cells (%)39.7%
Duplicate rows1
Duplicate rows (%)1.4%
Total size in memory7.9 KiB
Average record size in memory111.8 B

Variable types

Categorical3
Text5
Numeric4
DateTime1

Dataset

Description경기도 여주시의 집단급식소 위탁운영 현황 데이터입니다. 업소명, 소재지도로명주소, 소재지지번주소, 업소전화번호, 1일급식인원, 위탁급식업소명 등의 데이터를 제공합니다.
URLhttps://www.data.go.kr/data/15100776/fileData.do

Alerts

데이터기준일자 has constant value ""Constant
Dataset has 1 (1.4%) duplicate rowsDuplicates
급식인원(기타) is highly overall correlated with 1일급식인원 and 5 other fieldsHigh correlation
시군명 is highly overall correlated with 1일급식인원 and 5 other fieldsHigh correlation
급식인원(야식) is highly overall correlated with 급식인원(아침) and 3 other fieldsHigh correlation
1일급식인원 is highly overall correlated with 급식인원(점심) and 3 other fieldsHigh correlation
급식인원(아침) is highly overall correlated with 시군명 and 2 other fieldsHigh correlation
급식인원(점심) is highly overall correlated with 1일급식인원 and 2 other fieldsHigh correlation
급식인원(저녁) is highly overall correlated with 1일급식인원 and 3 other fieldsHigh correlation
업소명 has 37 (51.4%) missing valuesMissing
소재지도로명주소 has 37 (51.4%) missing valuesMissing
소재지지번주소 has 37 (51.4%) missing valuesMissing
업소전화번호 has 39 (54.2%) missing valuesMissing
1일급식인원 has 37 (51.4%) missing valuesMissing
급식인원(아침) has 37 (51.4%) missing valuesMissing
급식인원(점심) has 37 (51.4%) missing valuesMissing
급식인원(저녁) has 37 (51.4%) missing valuesMissing
위탁급식업소명 has 37 (51.4%) missing valuesMissing
데이터기준일자 has 37 (51.4%) missing valuesMissing
급식인원(아침) has 14 (19.4%) zerosZeros
급식인원(저녁) has 6 (8.3%) zerosZeros

Reproduction

Analysis started2023-12-12 06:05:28.680139
Analysis finished2023-12-12 06:05:31.928172
Duration3.25 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

시군명
Categorical

HIGH CORRELATION 

Distinct2
Distinct (%)2.8%
Missing0
Missing (%)0.0%
Memory size708.0 B
<NA>
37 
여주시
35 

Length

Max length4
Median length4
Mean length3.5138889
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 37
51.4%
여주시 35
48.6%

Length

2023-12-12T15:05:31.997944image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T15:05:32.092653image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 37
51.4%
여주시 35
48.6%

업소명
Text

MISSING 

Distinct35
Distinct (%)100.0%
Missing37
Missing (%)51.4%
Memory size708.0 B
2023-12-12T15:05:32.289731image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length22
Median length15
Mean length10.028571
Min length4

Characters and Unicode

Total characters351
Distinct characters133
Distinct categories6 ?
Distinct scripts3 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique35 ?
Unique (%)100.0%

Sample

1st row㈜고영테크놀러지 여주공장
2nd row(주)금강레저
3rd row(주)세정
4th row(주)신세계 인터내셔날
5th row(주)신세계사이먼
ValueCountFrequency (%)
여주공장 3
 
7.0%
주)금강레저 1
 
2.3%
씨제이대한통운(주 1
 
2.3%
여주cc직원식당 1
 
2.3%
비씨월드제약 1
 
2.3%
산림조합중앙회 1
 
2.3%
중부목재사업본부 1
 
2.3%
삼표피앤씨 1
 
2.3%
상일식품(주 1
 
2.3%
수원지방법원여주지원 1
 
2.3%
Other values (31) 31
72.1%
2023-12-12T15:05:32.691776image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
주 33
 
9.4%
( 19
 
5.4%
) 19
 
5.4%
여 14
 
4.0%
이 11
 
3.1%
8
 
2.3%
원 8
 
2.3%
식 7
 
2.0%
지 6
 
1.7%
대 6
 
1.7%
Other values (123) 220
62.7%

Most occurring categories

ValueCountFrequency (%)
Other Letter 301
85.8%
Open Punctuation 19
 
5.4%
Close Punctuation 19
 
5.4%
Space Separator 8
 
2.3%
Uppercase Letter 2
 
0.6%
Other Symbol 2
 
0.6%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
주 33
 
11.0%
여 14
 
4.7%
이 11
 
3.7%
원 8
 
2.7%
식 7
 
2.3%
지 6
 
2.0%
대 6
 
2.0%
씨 6
 
2.0%
당 6
 
2.0%
아 6
 
2.0%
Other values (118) 198
65.8%
Open Punctuation
ValueCountFrequency (%)
( 19
100.0%
Close Punctuation
ValueCountFrequency (%)
) 19
100.0%
Space Separator
ValueCountFrequency (%)
8
100.0%
Uppercase Letter
ValueCountFrequency (%)
C 2
100.0%
Other Symbol
ValueCountFrequency (%)
㈜ 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 303
86.3%
Common 46
 
13.1%
Latin 2
 
0.6%

Most frequent character per script

Hangul
ValueCountFrequency (%)
주 33
 
10.9%
여 14
 
4.6%
이 11
 
3.6%
원 8
 
2.6%
식 7
 
2.3%
지 6
 
2.0%
대 6
 
2.0%
씨 6
 
2.0%
당 6
 
2.0%
아 6
 
2.0%
Other values (119) 200
66.0%
Common
ValueCountFrequency (%)
( 19
41.3%
) 19
41.3%
8
17.4%
Latin
ValueCountFrequency (%)
C 2
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 301
85.8%
ASCII 48
 
13.7%
None 2
 
0.6%

Most frequent character per block

Hangul
ValueCountFrequency (%)
주 33
 
11.0%
여 14
 
4.7%
이 11
 
3.7%
원 8
 
2.7%
식 7
 
2.3%
지 6
 
2.0%
대 6
 
2.0%
씨 6
 
2.0%
당 6
 
2.0%
아 6
 
2.0%
Other values (118) 198
65.8%
ASCII
ValueCountFrequency (%)
( 19
39.6%
) 19
39.6%
8
16.7%
C 2
 
4.2%
None
ValueCountFrequency (%)
㈜ 2
100.0%

소재지도로명주소
Text

MISSING 

Distinct33
Distinct (%)94.3%
Missing37
Missing (%)51.4%
Memory size708.0 B
2023-12-12T15:05:32.961211image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length40
Median length26
Mean length21.6
Min length14

Characters and Unicode

Total characters756
Distinct characters94
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

Unique32 ?
Unique (%)91.4%

Sample

1st row경기도 여주시 세종대왕면 광대2길 66-27, 3층
2nd row경기도 여주시 가남읍 금강그린길 84, 1층
3rd row경기도 여주시 가남읍 가남로 449
4th row경기도 여주시 명품로 360, 3동 3층 (상거동)
5th row경기도 여주시 명품로 360, 여주프리미엄아울렛 100동 2층 (상거동)
ValueCountFrequency (%)
경기도 35
18.9%
여주시 35
18.9%
가남읍 11
 
5.9%
세종로 5
 
2.7%
1층 5
 
2.7%
338 3
 
1.6%
교동 3
 
1.6%
여주남로 3
 
1.6%
2층 2
 
1.1%
명품로 2
 
1.1%
Other values (72) 81
43.8%
2023-12-12T15:05:33.435777image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
150
19.8%
여 40
 
5.3%
주 39
 
5.2%
경 37
 
4.9%
도 36
 
4.8%
기 35
 
4.6%
시 35
 
4.6%
로 27
 
3.6%
1 26
 
3.4%
3 21
 
2.8%
Other values (84) 310
41.0%

Most occurring categories

ValueCountFrequency (%)
Other Letter 445
58.9%
Space Separator 150
 
19.8%
Decimal Number 126
 
16.7%
Other Punctuation 12
 
1.6%
Open Punctuation 8
 
1.1%
Close Punctuation 8
 
1.1%
Dash Punctuation 4
 
0.5%
Uppercase Letter 3
 
0.4%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
여 40
 
9.0%
주 39
 
8.8%
경 37
 
8.3%
도 36
 
8.1%
기 35
 
7.9%
시 35
 
7.9%
로 27
 
6.1%
남 16
 
3.6%
동 15
 
3.4%
가 13
 
2.9%
Other values (67) 152
34.2%
Decimal Number
ValueCountFrequency (%)
1 26
20.6%
3 21
16.7%
2 20
15.9%
0 12
9.5%
4 11
8.7%
6 11
8.7%
8 9
 
7.1%
7 8
 
6.3%
5 6
 
4.8%
9 2
 
1.6%
Uppercase Letter
ValueCountFrequency (%)
C 2
66.7%
D 1
33.3%
Space Separator
ValueCountFrequency (%)
150
100.0%
Other Punctuation
ValueCountFrequency (%)
, 12
100.0%
Open Punctuation
ValueCountFrequency (%)
( 8
100.0%
Close Punctuation
ValueCountFrequency (%)
) 8
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 4
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 445
58.9%
Common 308
40.7%
Latin 3
 
0.4%

Most frequent character per script

Hangul
ValueCountFrequency (%)
여 40
 
9.0%
주 39
 
8.8%
경 37
 
8.3%
도 36
 
8.1%
기 35
 
7.9%
시 35
 
7.9%
로 27
 
6.1%
남 16
 
3.6%
동 15
 
3.4%
가 13
 
2.9%
Other values (67) 152
34.2%
Common
ValueCountFrequency (%)
150
48.7%
1 26
 
8.4%
3 21
 
6.8%
2 20
 
6.5%
0 12
 
3.9%
, 12
 
3.9%
4 11
 
3.6%
6 11
 
3.6%
8 9
 
2.9%
7 8
 
2.6%
Other values (5) 28
 
9.1%
Latin
ValueCountFrequency (%)
C 2
66.7%
D 1
33.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 445
58.9%
ASCII 311
41.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
150
48.2%
1 26
 
8.4%
3 21
 
6.8%
2 20
 
6.4%
0 12
 
3.9%
, 12
 
3.9%
4 11
 
3.5%
6 11
 
3.5%
8 9
 
2.9%
7 8
 
2.6%
Other values (7) 31
 
10.0%
Hangul
ValueCountFrequency (%)
여 40
 
9.0%
주 39
 
8.8%
경 37
 
8.3%
도 36
 
8.1%
기 35
 
7.9%
시 35
 
7.9%
로 27
 
6.1%
남 16
 
3.6%
동 15
 
3.4%
가 13
 
2.9%
Other values (67) 152
34.2%

소재지지번주소
Text

MISSING 

Distinct35
Distinct (%)100.0%
Missing37
Missing (%)51.4%
Memory size708.0 B
2023-12-12T15:05:33.736916image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length41
Median length33
Mean length24.371429
Min length17

Characters and Unicode

Total characters853
Distinct characters107
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

Unique35 ?
Unique (%)100.0%

Sample

1st row경기도 여주시 세종대왕면 광대리 237-2
2nd row경기도 여주시 가남읍 본두리 산 29 - 17
3rd row경기도 여주시 가남읍 양귀리 627 - 1
4th row경기도 여주시 상거동 460 - 18 3동
5th row경기도 여주시 상거동 460 - 1 여주프리미엄아울렛 100동
ValueCountFrequency (%)
경기도 35
 
15.1%
여주시 35
 
15.1%
26
 
11.2%
1 14
 
6.0%
가남읍 11
 
4.7%
산 8
 
3.4%
5 4
 
1.7%
본두리 4
 
1.7%
양귀리 3
 
1.3%
교동 3
 
1.3%
Other values (78) 89
38.4%
2023-12-12T15:05:34.126771image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
254
29.8%
주 41
 
4.8%
여 38
 
4.5%
1 37
 
4.3%
기 36
 
4.2%
경 35
 
4.1%
도 35
 
4.1%
시 35
 
4.1%
- 29
 
3.4%
동 23
 
2.7%
Other values (97) 290
34.0%

Most occurring categories

ValueCountFrequency (%)
Other Letter 435
51.0%
Space Separator 254
29.8%
Decimal Number 127
 
14.9%
Dash Punctuation 29
 
3.4%
Uppercase Letter 3
 
0.4%
Open Punctuation 2
 
0.2%
Close Punctuation 2
 
0.2%
Other Symbol 1
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
주 41
 
9.4%
여 38
 
8.7%
기 36
 
8.3%
경 35
 
8.0%
도 35
 
8.0%
시 35
 
8.0%
동 23
 
5.3%
리 22
 
5.1%
가 12
 
2.8%
읍 11
 
2.5%
Other values (80) 147
33.8%
Decimal Number
ValueCountFrequency (%)
1 37
29.1%
4 19
15.0%
6 12
 
9.4%
5 12
 
9.4%
0 11
 
8.7%
2 10
 
7.9%
3 9
 
7.1%
7 7
 
5.5%
9 6
 
4.7%
8 4
 
3.1%
Uppercase Letter
ValueCountFrequency (%)
C 2
66.7%
B 1
33.3%
Space Separator
ValueCountFrequency (%)
254
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 29
100.0%
Open Punctuation
ValueCountFrequency (%)
( 2
100.0%
Close Punctuation
ValueCountFrequency (%)
) 2
100.0%
Other Symbol
ValueCountFrequency (%)
㈜ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 436
51.1%
Common 414
48.5%
Latin 3
 
0.4%

Most frequent character per script

Hangul
ValueCountFrequency (%)
주 41
 
9.4%
여 38
 
8.7%
기 36
 
8.3%
경 35
 
8.0%
도 35
 
8.0%
시 35
 
8.0%
동 23
 
5.3%
리 22
 
5.0%
가 12
 
2.8%
읍 11
 
2.5%
Other values (81) 148
33.9%
Common
ValueCountFrequency (%)
254
61.4%
1 37
 
8.9%
- 29
 
7.0%
4 19
 
4.6%
6 12
 
2.9%
5 12
 
2.9%
0 11
 
2.7%
2 10
 
2.4%
3 9
 
2.2%
7 7
 
1.7%
Other values (4) 14
 
3.4%
Latin
ValueCountFrequency (%)
C 2
66.7%
B 1
33.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 435
51.0%
ASCII 417
48.9%
None 1
 
0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
254
60.9%
1 37
 
8.9%
- 29
 
7.0%
4 19
 
4.6%
6 12
 
2.9%
5 12
 
2.9%
0 11
 
2.6%
2 10
 
2.4%
3 9
 
2.2%
7 7
 
1.7%
Other values (6) 17
 
4.1%
Hangul
ValueCountFrequency (%)
주 41
 
9.4%
여 38
 
8.7%
기 36
 
8.3%
경 35
 
8.0%
도 35
 
8.0%
시 35
 
8.0%
동 23
 
5.3%
리 22
 
5.1%
가 12
 
2.8%
읍 11
 
2.5%
Other values (80) 147
33.8%
None
ValueCountFrequency (%)
㈜ 1
100.0%

업소전화번호
Text

MISSING 

Distinct32
Distinct (%)97.0%
Missing39
Missing (%)54.2%
Memory size708.0 B
2023-12-12T15:05:34.352741image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length13
Median length12
Mean length12
Min length11

Characters and Unicode

Total characters396
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

Unique31 ?
Unique (%)93.9%

Sample

1st row070-4617-2729
2nd row031-880-6053
3rd row031-882-5402
4th row031-880-5913
5th row031-880-1258
ValueCountFrequency (%)
031-880-5144 2
 
6.1%
031-882-5402 1
 
3.0%
031-884-9281 1
 
3.0%
031-881-6800 1
 
3.0%
031-881-1391 1
 
3.0%
02-460-7111 1
 
3.0%
031-884-9685 1
 
3.0%
031-880-7424 1
 
3.0%
031-887-9924 1
 
3.0%
070-4617-2729 1
 
3.0%
Other values (22) 22
66.7%
2023-12-12T15:05:34.795181image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
8 78
19.7%
0 68
17.2%
- 66
16.7%
1 58
14.6%
3 39
9.8%
5 18
 
4.5%
4 16
 
4.0%
2 15
 
3.8%
7 15
 
3.8%
6 14
 
3.5%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 330
83.3%
Dash Punctuation 66
 
16.7%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
8 78
23.6%
0 68
20.6%
1 58
17.6%
3 39
11.8%
5 18
 
5.5%
4 16
 
4.8%
2 15
 
4.5%
7 15
 
4.5%
6 14
 
4.2%
9 9
 
2.7%
Dash Punctuation
ValueCountFrequency (%)
- 66
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 396
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
8 78
19.7%
0 68
17.2%
- 66
16.7%
1 58
14.6%
3 39
9.8%
5 18
 
4.5%
4 16
 
4.0%
2 15
 
3.8%
7 15
 
3.8%
6 14
 
3.5%

Most occurring blocks

ValueCountFrequency (%)
ASCII 396
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
8 78
19.7%
0 68
17.2%
- 66
16.7%
1 58
14.6%
3 39
9.8%
5 18
 
4.5%
4 16
 
4.0%
2 15
 
3.8%
7 15
 
3.8%
6 14
 
3.5%

1일급식인원
Real number (ℝ)

HIGH CORRELATION  MISSING 

Distinct26
Distinct (%)74.3%
Missing37
Missing (%)51.4%
Infinite0
Infinite (%)0.0%
Mean267.02857
Minimum45
Maximum950
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size780.0 B
2023-12-12T15:05:34.953512image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum45
5-th percentile50
Q1120
median200
Q3325
95-th percentile695
Maximum950
Range905
Interquartile range (IQR)205

Descriptive statistics

Standard deviation212.31088
Coefficient of variation (CV)0.79508676
Kurtosis2.7422044
Mean267.02857
Median Absolute Deviation (MAD)82
Skewness1.6649229
Sum9346
Variance45075.911
MonotonicityNot monotonic
2023-12-12T15:05:35.099781image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=26)
ValueCountFrequency (%)
120 4
 
5.6%
110 2
 
2.8%
50 2
 
2.8%
400 2
 
2.8%
270 2
 
2.8%
200 2
 
2.8%
240 2
 
2.8%
80 1
 
1.4%
84 1
 
1.4%
500 1
 
1.4%
Other values (16) 16
22.2%
(Missing) 37
51.4%
ValueCountFrequency (%)
45 1
 
1.4%
50 2
2.8%
80 1
 
1.4%
84 1
 
1.4%
110 2
2.8%
120 4
5.6%
130 1
 
1.4%
140 1
 
1.4%
180 1
 
1.4%
190 1
 
1.4%
ValueCountFrequency (%)
950 1
1.4%
800 1
1.4%
650 1
1.4%
600 1
1.4%
500 1
1.4%
400 2
2.8%
380 1
1.4%
330 1
1.4%
320 1
1.4%
282 1
1.4%

급식인원(아침)
Real number (ℝ)

HIGH CORRELATION  MISSING  ZEROS 

Distinct14
Distinct (%)40.0%
Missing37
Missing (%)51.4%
Infinite0
Infinite (%)0.0%
Mean39.514286
Minimum0
Maximum250
Zeros14
Zeros (%)19.4%
Negative0
Negative (%)0.0%
Memory size780.0 B
2023-12-12T15:05:35.220573image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median20
Q370
95-th percentile125.4
Maximum250
Range250
Interquartile range (IQR)70

Descriptive statistics

Standard deviation53.802674
Coefficient of variation (CV)1.3616006
Kurtosis5.7775593
Mean39.514286
Median Absolute Deviation (MAD)20
Skewness2.0877906
Sum1383
Variance2894.7277
MonotonicityNot monotonic
2023-12-12T15:05:35.354830image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=14)
ValueCountFrequency (%)
0 14
 
19.4%
20 3
 
4.2%
40 3
 
4.2%
70 3
 
4.2%
80 2
 
2.8%
30 2
 
2.8%
138 1
 
1.4%
120 1
 
1.4%
90 1
 
1.4%
60 1
 
1.4%
Other values (4) 4
 
5.6%
(Missing) 37
51.4%
ValueCountFrequency (%)
0 14
19.4%
5 1
 
1.4%
10 1
 
1.4%
20 3
 
4.2%
30 2
 
2.8%
40 3
 
4.2%
60 1
 
1.4%
70 3
 
4.2%
80 2
 
2.8%
90 1
 
1.4%
ValueCountFrequency (%)
250 1
 
1.4%
138 1
 
1.4%
120 1
 
1.4%
100 1
 
1.4%
90 1
 
1.4%
80 2
2.8%
70 3
4.2%
60 1
 
1.4%
40 3
4.2%
30 2
2.8%

급식인원(점심)
Real number (ℝ)

HIGH CORRELATION  MISSING 

Distinct19
Distinct (%)54.3%
Missing37
Missing (%)51.4%
Infinite0
Infinite (%)0.0%
Mean167.14286
Minimum40
Maximum700
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size780.0 B
2023-12-12T15:05:35.476759image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum40
5-th percentile48.5
Q180
median95
Q3200
95-th percentile615
Maximum700
Range660
Interquartile range (IQR)120

Descriptive statistics

Standard deviation164.49247
Coefficient of variation (CV)0.98414299
Kurtosis4.9748073
Mean167.14286
Median Absolute Deviation (MAD)35
Skewness2.3334412
Sum5850
Variance27057.773
MonotonicityNot monotonic
2023-12-12T15:05:35.617159image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=19)
ValueCountFrequency (%)
80 7
 
9.7%
90 3
 
4.2%
70 3
 
4.2%
120 3
 
4.2%
50 2
 
2.8%
200 2
 
2.8%
210 2
 
2.8%
150 2
 
2.8%
130 1
 
1.4%
700 1
 
1.4%
Other values (9) 9
 
12.5%
(Missing) 37
51.4%
ValueCountFrequency (%)
40 1
 
1.4%
45 1
 
1.4%
50 2
 
2.8%
70 3
4.2%
80 7
9.7%
90 3
4.2%
95 1
 
1.4%
120 3
4.2%
130 1
 
1.4%
140 1
 
1.4%
ValueCountFrequency (%)
700 1
1.4%
650 1
1.4%
600 1
1.4%
300 1
1.4%
280 1
1.4%
250 1
1.4%
210 2
2.8%
200 2
2.8%
150 2
2.8%
140 1
1.4%

급식인원(저녁)
Real number (ℝ)

HIGH CORRELATION  MISSING  ZEROS 

Distinct14
Distinct (%)40.0%
Missing37
Missing (%)51.4%
Infinite0
Infinite (%)0.0%
Mean55.228571
Minimum0
Maximum200
Zeros6
Zeros (%)8.3%
Negative0
Negative (%)0.0%
Memory size780.0 B
2023-12-12T15:05:35.768963image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q112.5
median50
Q380
95-th percentile193
Maximum200
Range200
Interquartile range (IQR)67.5

Descriptive statistics

Standard deviation55.598395
Coefficient of variation (CV)1.0066962
Kurtosis1.571976
Mean55.228571
Median Absolute Deviation (MAD)30
Skewness1.3679353
Sum1933
Variance3091.1815
MonotonicityNot monotonic
2023-12-12T15:05:35.897989image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=14)
ValueCountFrequency (%)
0 6
 
8.3%
50 5
 
6.9%
30 3
 
4.2%
100 3
 
4.2%
60 3
 
4.2%
20 3
 
4.2%
40 2
 
2.8%
80 2
 
2.8%
200 2
 
2.8%
4 2
 
2.8%
Other values (4) 4
 
5.6%
(Missing) 37
51.4%
ValueCountFrequency (%)
0 6
8.3%
4 2
 
2.8%
5 1
 
1.4%
20 3
4.2%
30 3
4.2%
40 2
 
2.8%
50 5
6.9%
60 3
4.2%
80 2
 
2.8%
90 1
 
1.4%
ValueCountFrequency (%)
200 2
 
2.8%
190 1
 
1.4%
120 1
 
1.4%
100 3
4.2%
90 1
 
1.4%
80 2
 
2.8%
60 3
4.2%
50 5
6.9%
40 2
 
2.8%
30 3
4.2%

급식인원(야식)
Categorical

HIGH CORRELATION 

Distinct5
Distinct (%)6.9%
Missing0
Missing (%)0.0%
Memory size708.0 B
<NA>
37 
0
32 
60
 
1
20
 
1
100
 
1

Length

Max length4
Median length4
Mean length2.5972222
Min length1

Unique

Unique3 ?
Unique (%)4.2%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
<NA> 37
51.4%
0 32
44.4%
60 1
 
1.4%
20 1
 
1.4%
100 1
 
1.4%

Length

2023-12-12T15:05:36.056620image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T15:05:36.196660image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 37
51.4%
0 32
44.4%
60 1
 
1.4%
20 1
 
1.4%
100 1
 
1.4%

급식인원(기타)
Categorical

HIGH CORRELATION 

Distinct2
Distinct (%)2.8%
Missing0
Missing (%)0.0%
Memory size708.0 B
<NA>
37 
0
35 

Length

Max length4
Median length4
Mean length2.5416667
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
<NA> 37
51.4%
0 35
48.6%

Length

2023-12-12T15:05:36.321538image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T15:05:36.450331image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 37
51.4%
0 35
48.6%

위탁급식업소명
Text

MISSING 

Distinct33
Distinct (%)94.3%
Missing37
Missing (%)51.4%
Memory size708.0 B
2023-12-12T15:05:36.683607image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length22
Median length14
Mean length10.285714
Min length2

Characters and Unicode

Total characters360
Distinct characters121
Distinct categories7 ?
Distinct scripts3 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique32 ?
Unique (%)91.4%

Sample

1st row아이비푸드 고용테크놀러지
2nd row㈜현대그린푸드 금강CC
3rd row라미푸드
4th row㈜신세계푸드 SI물류센터
5th row㈜후레쉬케터링
ValueCountFrequency (%)
씨제이프레시웨이㈜ 3
 
5.4%
㈜신세계푸드 3
 
5.4%
직원식당 2
 
3.6%
코주부프레쉬쿡 2
 
3.6%
㈜아워홈 2
 
3.6%
지점 1
 
1.8%
이조케터링 1
 
1.8%
서비스㈜ 1
 
1.8%
이마트물류센터 1
 
1.8%
여주대학 1
 
1.8%
Other values (39) 39
69.6%
2023-12-12T15:05:37.093203image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
21
 
5.8%
㈜ 17
 
4.7%
이 16
 
4.4%
드 15
 
4.2%
푸 13
 
3.6%
원 11
 
3.1%
식 10
 
2.8%
주 10
 
2.8%
당 9
 
2.5%
스 9
 
2.5%
Other values (111) 229
63.6%

Most occurring categories

ValueCountFrequency (%)
Other Letter 311
86.4%
Space Separator 21
 
5.8%
Other Symbol 17
 
4.7%
Uppercase Letter 8
 
2.2%
Connector Punctuation 1
 
0.3%
Close Punctuation 1
 
0.3%
Open Punctuation 1
 
0.3%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
이 16
 
5.1%
드 15
 
4.8%
푸 13
 
4.2%
원 11
 
3.5%
식 10
 
3.2%
주 10
 
3.2%
당 9
 
2.9%
스 9
 
2.9%
여 8
 
2.6%
점 7
 
2.3%
Other values (103) 203
65.3%
Uppercase Letter
ValueCountFrequency (%)
C 6
75.0%
I 1
 
12.5%
S 1
 
12.5%
Space Separator
ValueCountFrequency (%)
21
100.0%
Other Symbol
ValueCountFrequency (%)
㈜ 17
100.0%
Connector Punctuation
ValueCountFrequency (%)
_ 1
100.0%
Close Punctuation
ValueCountFrequency (%)
) 1
100.0%
Open Punctuation
ValueCountFrequency (%)
( 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 328
91.1%
Common 24
 
6.7%
Latin 8
 
2.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
㈜ 17
 
5.2%
이 16
 
4.9%
드 15
 
4.6%
푸 13
 
4.0%
원 11
 
3.4%
식 10
 
3.0%
주 10
 
3.0%
당 9
 
2.7%
스 9
 
2.7%
여 8
 
2.4%
Other values (104) 210
64.0%
Common
ValueCountFrequency (%)
21
87.5%
_ 1
 
4.2%
) 1
 
4.2%
( 1
 
4.2%
Latin
ValueCountFrequency (%)
C 6
75.0%
I 1
 
12.5%
S 1
 
12.5%

Most occurring blocks

ValueCountFrequency (%)
Hangul 311
86.4%
ASCII 32
 
8.9%
None 17
 
4.7%

Most frequent character per block

ASCII
ValueCountFrequency (%)
21
65.6%
C 6
 
18.8%
_ 1
 
3.1%
) 1
 
3.1%
( 1
 
3.1%
I 1
 
3.1%
S 1
 
3.1%
None
ValueCountFrequency (%)
㈜ 17
100.0%
Hangul
ValueCountFrequency (%)
이 16
 
5.1%
드 15
 
4.8%
푸 13
 
4.2%
원 11
 
3.5%
식 10
 
3.2%
주 10
 
3.2%
당 9
 
2.9%
스 9
 
2.9%
여 8
 
2.6%
점 7
 
2.3%
Other values (103) 203
65.3%

데이터기준일자
Date

CONSTANT  MISSING 

Distinct1
Distinct (%)2.9%
Missing37
Missing (%)51.4%
Memory size708.0 B
Minimum2023-06-15 00:00:00
Maximum2023-06-15 00:00:00
2023-12-12T15:05:37.219210image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:05:37.306576image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=1)

Interactions

2023-12-12T15:05:30.852232image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:05:29.446349image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:05:29.804592image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:05:30.450383image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:05:30.944430image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:05:29.541971image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:05:30.191410image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:05:30.545700image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:05:31.082423image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:05:29.634205image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:05:30.265856image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:05:30.655077image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:05:31.191819image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:05:29.715995image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:05:30.347375image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:05:30.757189image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-12T15:05:37.389632image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
업소명소재지도로명주소소재지지번주소업소전화번호1일급식인원급식인원(아침)급식인원(점심)급식인원(저녁)급식인원(야식)위탁급식업소명
업소명1.0001.0001.0001.0001.0001.0001.0001.0001.0001.000
소재지도로명주소1.0001.0001.0001.0000.0000.0000.0000.9741.0000.974
소재지지번주소1.0001.0001.0001.0001.0001.0001.0001.0001.0001.000
업소전화번호1.0001.0001.0001.0000.7931.0000.0000.9851.0000.975
1일급식인원1.0000.0001.0000.7931.0000.7760.8590.8540.5780.965
급식인원(아침)1.0000.0001.0001.0000.7761.0000.3490.4930.4150.000
급식인원(점심)1.0000.0001.0000.0000.8590.3491.0000.5840.4390.967
급식인원(저녁)1.0000.9741.0000.9850.8540.4930.5841.0000.9280.588
급식인원(야식)1.0001.0001.0001.0000.5780.4150.4390.9281.0000.000
위탁급식업소명1.0000.9741.0000.9750.9650.0000.9670.5880.0001.000
2023-12-12T15:05:37.530784image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
급식인원(기타)시군명급식인원(야식)
급식인원(기타)1.0001.0001.000
시군명1.0001.0001.000
급식인원(야식)1.0001.0001.000
2023-12-12T15:05:37.644189image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
1일급식인원급식인원(아침)급식인원(점심)급식인원(저녁)시군명급식인원(야식)급식인원(기타)
1일급식인원1.0000.2580.9250.6081.0000.2581.000
급식인원(아침)0.2581.0000.0680.0921.0000.5131.000
급식인원(점심)0.9250.0681.0000.4761.0000.2801.000
급식인원(저녁)0.6080.0920.4761.0001.0000.5391.000
시군명1.0001.0001.0001.0001.0001.0001.000
급식인원(야식)0.2580.5130.2800.5391.0001.0001.000
급식인원(기타)1.0001.0001.0001.0001.0001.0001.000

Missing values

2023-12-12T15:05:31.340762image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-12T15:05:31.519231image/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.
2023-12-12T15:05:31.722909image/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

시군명업소명소재지도로명주소소재지지번주소업소전화번호1일급식인원급식인원(아침)급식인원(점심)급식인원(저녁)급식인원(야식)급식인원(기타)위탁급식업소명데이터기준일자
0여주시㈜고영테크놀러지 여주공장경기도 여주시 세종대왕면 광대2길 66-27, 3층경기도 여주시 세종대왕면 광대리 237-2070-4617-27291200804000아이비푸드 고용테크놀러지2023-06-15
1여주시(주)금강레저경기도 여주시 가남읍 금강그린길 84, 1층경기도 여주시 가남읍 본두리 산 29 - 17031-880-605321080805000㈜현대그린푸드 금강CC2023-06-15
2여주시(주)세정경기도 여주시 가남읍 가남로 449경기도 여주시 가남읍 양귀리 627 - 1031-882-540212020703000라미푸드2023-06-15
3여주시(주)신세계 인터내셔날경기도 여주시 명품로 360, 3동 3층 (상거동)경기도 여주시 상거동 460 - 18 3동031-880-591333002508000㈜신세계푸드 SI물류센터2023-06-15
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시군명업소명소재지도로명주소소재지지번주소업소전화번호1일급식인원급식인원(아침)급식인원(점심)급식인원(저녁)급식인원(야식)급식인원(기타)위탁급식업소명데이터기준일자
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시군명업소명소재지도로명주소소재지지번주소업소전화번호1일급식인원급식인원(아침)급식인원(점심)급식인원(저녁)급식인원(야식)급식인원(기타)위탁급식업소명데이터기준일자# duplicates
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