Overview

Dataset statistics

Number of variables18
Number of observations10000
Missing cells50474
Missing cells (%)28.0%
Duplicate rows6
Duplicate rows (%)0.1%
Total size in memory1.5 MiB
Average record size in memory156.0 B

Variable types

Text11
DateTime2
Categorical1
Numeric4

Dataset

Description공공데이터 제공 표준데이터 속성정보(허용값, 표현형식/단위 등)는 [공공데이터 제공 표준] 전문을 참고하시기 바랍니다.(공공데이터포털>정보공유>자료실)
Author지방자치단체
URLhttps://www.data.go.kr/data/15107746/standard.do

Alerts

Dataset has 6 (0.1%) duplicate rowsDuplicates
업소구분 is highly imbalanced (59.8%)Imbalance
사업자등록번호 has 5927 (59.3%) missing valuesMissing
소재지도로명주소 has 288 (2.9%) missing valuesMissing
소재지지번주소 has 5281 (52.8%) missing valuesMissing
전화번호 has 6568 (65.7%) missing valuesMissing
업소급식인원수 has 6540 (65.4%) missing valuesMissing
업소면적 has 5455 (54.5%) missing valuesMissing
자가처리량 has 6710 (67.1%) missing valuesMissing
자가재활용계획량 has 7207 (72.1%) missing valuesMissing
위탁재활용계획량 has 6498 (65.0%) missing valuesMissing
업소급식인원수 is highly skewed (γ1 = 43.66860888)Skewed
업소면적 is highly skewed (γ1 = 41.55122092)Skewed
업소객실수 is highly skewed (γ1 = 39.79424356)Skewed
업소급식인원수 has 1254 (12.5%) zerosZeros
업소면적 has 659 (6.6%) zerosZeros
업소객실수 has 9598 (96.0%) zerosZeros

Reproduction

Analysis started2024-04-29 23:37:58.829977
Analysis finished2024-04-29 23:38:04.442190
Duration5.61 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

상호명
Text

Distinct9502
Distinct (%)95.0%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2024-04-30T08:38:04.647698image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length20
Median length16
Mean length8.237
Min length1

Characters and Unicode

Total characters82370
Distinct characters995
Distinct categories14 ?
Distinct scripts4 ?
Distinct blocks7 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique9066 ?
Unique (%)90.7%

Sample

1st row도깨비를 물리친 농부네 수제갈비
2nd row양지요양병원장례식장
3rd row합천초등학교
4th row삼주외식산업(주)인천가정법원
5th row강원대 삼척캠퍼스 해솔관
ValueCountFrequency (%)
주식회사 165
 
1.3%
주)아워홈 77
 
0.6%
구내식당 40
 
0.3%
의료법인 38
 
0.3%
주)현대그린푸드 34
 
0.3%
명륜진사갈비 31
 
0.2%
주)풀무원푸드앤컬처 24
 
0.2%
주)동원홈푸드 19
 
0.1%
푸디스트(주 19
 
0.1%
주 18
 
0.1%
Other values (10783) 12411
96.4%
2024-04-30T08:38:05.056548image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
2891
 
3.5%
교 2207
 
2.7%
학 2200
 
2.7%
주 2005
 
2.4%
( 1922
 
2.3%
) 1846
 
2.2%
원 1739
 
2.1%
점 1546
 
1.9%
등 1482
 
1.8%
이 1277
 
1.6%
Other values (985) 63255
76.8%

Most occurring categories

ValueCountFrequency (%)
Other Letter 73769
89.6%
Space Separator 2891
 
3.5%
Open Punctuation 1975
 
2.4%
Close Punctuation 1882
 
2.3%
Uppercase Letter 759
 
0.9%
Decimal Number 497
 
0.6%
Other Symbol 261
 
0.3%
Lowercase Letter 194
 
0.2%
Other Punctuation 92
 
0.1%
Dash Punctuation 24
 
< 0.1%
Other values (4) 26
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
교 2207
 
3.0%
학 2200
 
3.0%
주 2005
 
2.7%
원 1739
 
2.4%
점 1546
 
2.1%
등 1482
 
2.0%
이 1277
 
1.7%
스 1269
 
1.7%
초 1112
 
1.5%
식 972
 
1.3%
Other values (902) 57960
78.6%
Uppercase Letter
ValueCountFrequency (%)
C 126
16.6%
T 75
 
9.9%
S 69
 
9.1%
D 57
 
7.5%
K 52
 
6.9%
G 46
 
6.1%
A 38
 
5.0%
B 36
 
4.7%
L 32
 
4.2%
M 30
 
4.0%
Other values (15) 198
26.1%
Lowercase Letter
ValueCountFrequency (%)
e 25
12.9%
c 25
12.9%
a 19
9.8%
n 15
 
7.7%
t 14
 
7.2%
i 13
 
6.7%
o 12
 
6.2%
h 11
 
5.7%
s 10
 
5.2%
k 6
 
3.1%
Other values (15) 44
22.7%
Decimal Number
ValueCountFrequency (%)
1 133
26.8%
2 99
19.9%
3 52
 
10.5%
9 36
 
7.2%
0 36
 
7.2%
8 35
 
7.0%
4 31
 
6.2%
5 28
 
5.6%
7 27
 
5.4%
6 20
 
4.0%
Other Punctuation
ValueCountFrequency (%)
& 47
51.1%
. 21
22.8%
, 12
 
13.0%
/ 4
 
4.3%
: 3
 
3.3%
… 2
 
2.2%
· 1
 
1.1%
@ 1
 
1.1%
* 1
 
1.1%
Math Symbol
ValueCountFrequency (%)
< 2
33.3%
> 2
33.3%
+ 2
33.3%
Open Punctuation
ValueCountFrequency (%)
( 1922
97.3%
[ 53
 
2.7%
Close Punctuation
ValueCountFrequency (%)
) 1846
98.1%
] 36
 
1.9%
Letter Number
ValueCountFrequency (%)
Ⅱ 2
66.7%
Ⅶ 1
33.3%
Space Separator
ValueCountFrequency (%)
2891
100.0%
Other Symbol
ValueCountFrequency (%)
㈜ 261
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 24
100.0%
Connector Punctuation
ValueCountFrequency (%)
_ 16
100.0%
Final Punctuation
ValueCountFrequency (%)
’ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 74025
89.9%
Common 7384
 
9.0%
Latin 956
 
1.2%
Han 5
 
< 0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
교 2207
 
3.0%
학 2200
 
3.0%
주 2005
 
2.7%
원 1739
 
2.3%
점 1546
 
2.1%
등 1482
 
2.0%
이 1277
 
1.7%
스 1269
 
1.7%
초 1112
 
1.5%
식 972
 
1.3%
Other values (900) 58216
78.6%
Latin
ValueCountFrequency (%)
C 126
 
13.2%
T 75
 
7.8%
S 69
 
7.2%
D 57
 
6.0%
K 52
 
5.4%
G 46
 
4.8%
A 38
 
4.0%
B 36
 
3.8%
L 32
 
3.3%
M 30
 
3.1%
Other values (42) 395
41.3%
Common
ValueCountFrequency (%)
2891
39.2%
( 1922
26.0%
) 1846
25.0%
1 133
 
1.8%
2 99
 
1.3%
[ 53
 
0.7%
3 52
 
0.7%
& 47
 
0.6%
9 36
 
0.5%
0 36
 
0.5%
Other values (20) 269
 
3.6%
Han
ValueCountFrequency (%)
時 2
40.0%
愛 2
40.0%
眞 1
20.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 73762
89.5%
ASCII 8333
 
10.1%
None 262
 
0.3%
CJK 5
 
< 0.1%
Punctuation 3
 
< 0.1%
Number Forms 3
 
< 0.1%
Compat Jamo 2
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
2891
34.7%
( 1922
23.1%
) 1846
22.2%
1 133
 
1.6%
C 126
 
1.5%
2 99
 
1.2%
T 75
 
0.9%
S 69
 
0.8%
D 57
 
0.7%
[ 53
 
0.6%
Other values (67) 1062
 
12.7%
Hangul
ValueCountFrequency (%)
교 2207
 
3.0%
학 2200
 
3.0%
주 2005
 
2.7%
원 1739
 
2.4%
점 1546
 
2.1%
등 1482
 
2.0%
이 1277
 
1.7%
스 1269
 
1.7%
초 1112
 
1.5%
식 972
 
1.3%
Other values (897) 57953
78.6%
None
ValueCountFrequency (%)
㈜ 261
99.6%
· 1
 
0.4%
CJK
ValueCountFrequency (%)
時 2
40.0%
愛 2
40.0%
眞 1
20.0%
Punctuation
ValueCountFrequency (%)
… 2
66.7%
’ 1
33.3%
Number Forms
ValueCountFrequency (%)
Ⅱ 2
66.7%
Ⅶ 1
33.3%
Compat Jamo
ValueCountFrequency (%)
ㅊ 1
50.0%
ㅁ 1
50.0%

사업자등록번호
Text

MISSING 

Distinct3684
Distinct (%)90.4%
Missing5927
Missing (%)59.3%
Memory size156.2 KiB
2024-04-30T08:38:05.290628image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length12
Median length12
Mean length12
Min length12

Characters and Unicode

Total characters48876
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

Unique3492 ?
Unique (%)85.7%

Sample

1st row214-92-00884
2nd row611-83-01914
3rd row126-83-00436
4th row303-83-02647
5th row126-83-00547
ValueCountFrequency (%)
603-81-11270 41
 
1.0%
214-86-08930 40
 
1.0%
711-81-01637 19
 
0.5%
104-81-39349 18
 
0.4%
215-86-65235 11
 
0.3%
101-81-30747 8
 
0.2%
656-81-02756 7
 
0.2%
101-86-76277 7
 
0.2%
108-81-15238 7
 
0.2%
403-81-61113 7
 
0.2%
Other values (3674) 3908
95.9%
2024-04-30T08:38:05.599061image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
- 8146
16.7%
0 7024
14.4%
1 5702
11.7%
2 4629
9.5%
8 4495
9.2%
3 4255
8.7%
6 3469
7.1%
4 3104
 
6.4%
5 3025
 
6.2%
7 2578
 
5.3%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 40730
83.3%
Dash Punctuation 8146
 
16.7%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 7024
17.2%
1 5702
14.0%
2 4629
11.4%
8 4495
11.0%
3 4255
10.4%
6 3469
8.5%
4 3104
7.6%
5 3025
7.4%
7 2578
 
6.3%
9 2449
 
6.0%
Dash Punctuation
ValueCountFrequency (%)
- 8146
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 48876
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
- 8146
16.7%
0 7024
14.4%
1 5702
11.7%
2 4629
9.5%
8 4495
9.2%
3 4255
8.7%
6 3469
7.1%
4 3104
 
6.4%
5 3025
 
6.2%
7 2578
 
5.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 48876
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
- 8146
16.7%
0 7024
14.4%
1 5702
11.7%
2 4629
9.5%
8 4495
9.2%
3 4255
8.7%
6 3469
7.1%
4 3104
 
6.4%
5 3025
 
6.2%
7 2578
 
5.3%

신고일자
Date

Distinct3982
Distinct (%)39.8%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
Minimum1883-04-25 00:00:00
Maximum2024-02-06 00:00:00
2024-04-30T08:38:05.727914image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-30T08:38:05.828428image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

소재지도로명주소
Text

MISSING 

Distinct9360
Distinct (%)96.4%
Missing288
Missing (%)2.9%
Memory size156.2 KiB
2024-04-30T08:38:06.115283image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length71
Median length59
Mean length26.120161
Min length13

Characters and Unicode

Total characters253679
Distinct characters736
Distinct categories13 ?
Distinct scripts3 ?
Distinct blocks5 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique9046 ?
Unique (%)93.1%

Sample

1st row경기도 과천시 새빛로 25 (문원동, 224)
2nd row경상북도 경산시 경산로 174 (옥산동)
3rd row경상남도 합천군 합천읍 죽죽길 3
4th row인천광역시 미추홀구 경원대로 881, 인천가정법원 (주안동)
5th row강원도 삼척시 중앙로 346
ValueCountFrequency (%)
경기도 3148
 
5.9%
서울특별시 988
 
1.8%
경상남도 977
 
1.8%
강원도 586
 
1.1%
1층 583
 
1.1%
서구 529
 
1.0%
인천광역시 524
 
1.0%
창원시 440
 
0.8%
강남구 428
 
0.8%
2층 425
 
0.8%
Other values (11729) 44934
83.9%
2024-04-30T08:38:06.599974image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
43936
 
17.3%
시 8918
 
3.5%
1 8482
 
3.3%
로 8456
 
3.3%
동 7745
 
3.1%
도 7463
 
2.9%
( 5940
 
2.3%
) 5939
 
2.3%
2 5738
 
2.3%
구 5330
 
2.1%
Other values (726) 145732
57.4%

Most occurring categories

ValueCountFrequency (%)
Other Letter 154867
61.0%
Space Separator 43936
 
17.3%
Decimal Number 37491
 
14.8%
Open Punctuation 5942
 
2.3%
Close Punctuation 5940
 
2.3%
Dash Punctuation 1585
 
0.6%
Other Punctuation 1544
 
0.6%
Connector Punctuation 1480
 
0.6%
Uppercase Letter 580
 
0.2%
Math Symbol 213
 
0.1%
Other values (3) 101
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
시 8918
 
5.8%
로 8456
 
5.5%
동 7745
 
5.0%
도 7463
 
4.8%
구 5330
 
3.4%
경 4840
 
3.1%
길 3685
 
2.4%
남 3681
 
2.4%
기 3540
 
2.3%
산 3307
 
2.1%
Other values (648) 97902
63.2%
Uppercase Letter
ValueCountFrequency (%)
B 101
17.4%
A 66
11.4%
C 60
10.3%
S 46
 
7.9%
T 38
 
6.6%
K 31
 
5.3%
I 25
 
4.3%
G 22
 
3.8%
E 22
 
3.8%
L 20
 
3.4%
Other values (15) 149
25.7%
Lowercase Letter
ValueCountFrequency (%)
e 12
13.2%
o 10
11.0%
t 7
 
7.7%
r 7
 
7.7%
a 7
 
7.7%
m 6
 
6.6%
s 6
 
6.6%
k 5
 
5.5%
u 5
 
5.5%
n 4
 
4.4%
Other values (10) 22
24.2%
Decimal Number
ValueCountFrequency (%)
1 8482
22.6%
2 5738
15.3%
3 4080
10.9%
5 3289
 
8.8%
4 3265
 
8.7%
0 2933
 
7.8%
6 2690
 
7.2%
7 2524
 
6.7%
8 2352
 
6.3%
9 2138
 
5.7%
Other Punctuation
ValueCountFrequency (%)
, 1475
95.5%
. 30
 
1.9%
， 16
 
1.0%
· 10
 
0.6%
& 8
 
0.5%
@ 3
 
0.2%
/ 1
 
0.1%
* 1
 
0.1%
Open Punctuation
ValueCountFrequency (%)
( 5940
> 99.9%
[ 1
 
< 0.1%
（ 1
 
< 0.1%
Math Symbol
ValueCountFrequency (%)
~ 166
77.9%
+ 46
 
21.6%
∥ 1
 
0.5%
Letter Number
ValueCountFrequency (%)
Ⅰ 2
40.0%
Ⅱ 2
40.0%
Ⅲ 1
20.0%
Close Punctuation
ValueCountFrequency (%)
) 5939
> 99.9%
] 1
 
< 0.1%
Space Separator
ValueCountFrequency (%)
43936
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 1585
100.0%
Connector Punctuation
ValueCountFrequency (%)
_ 1480
100.0%
Other Symbol
ValueCountFrequency (%)
㈜ 5
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 154872
61.1%
Common 98131
38.7%
Latin 676
 
0.3%

Most frequent character per script

Hangul
ValueCountFrequency (%)
시 8918
 
5.8%
로 8456
 
5.5%
동 7745
 
5.0%
도 7463
 
4.8%
구 5330
 
3.4%
경 4840
 
3.1%
길 3685
 
2.4%
남 3681
 
2.4%
기 3540
 
2.3%
산 3307
 
2.1%
Other values (649) 97907
63.2%
Latin
ValueCountFrequency (%)
B 101
14.9%
A 66
 
9.8%
C 60
 
8.9%
S 46
 
6.8%
T 38
 
5.6%
K 31
 
4.6%
I 25
 
3.7%
G 22
 
3.3%
E 22
 
3.3%
L 20
 
3.0%
Other values (38) 245
36.2%
Common
ValueCountFrequency (%)
43936
44.8%
1 8482
 
8.6%
( 5940
 
6.1%
) 5939
 
6.1%
2 5738
 
5.8%
3 4080
 
4.2%
5 3289
 
3.4%
4 3265
 
3.3%
0 2933
 
3.0%
6 2690
 
2.7%
Other values (19) 11839
 
12.1%

Most occurring blocks

ValueCountFrequency (%)
Hangul 154867
61.0%
ASCII 98774
38.9%
None 32
 
< 0.1%
Number Forms 5
 
< 0.1%
Math Operators 1
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
43936
44.5%
1 8482
 
8.6%
( 5940
 
6.0%
) 5939
 
6.0%
2 5738
 
5.8%
3 4080
 
4.1%
5 3289
 
3.3%
4 3265
 
3.3%
0 2933
 
3.0%
6 2690
 
2.7%
Other values (60) 12482
 
12.6%
Hangul
ValueCountFrequency (%)
시 8918
 
5.8%
로 8456
 
5.5%
동 7745
 
5.0%
도 7463
 
4.8%
구 5330
 
3.4%
경 4840
 
3.1%
길 3685
 
2.4%
남 3681
 
2.4%
기 3540
 
2.3%
산 3307
 
2.1%
Other values (648) 97902
63.2%
None
ValueCountFrequency (%)
， 16
50.0%
· 10
31.2%
㈜ 5
 
15.6%
（ 1
 
3.1%
Number Forms
ValueCountFrequency (%)
Ⅰ 2
40.0%
Ⅱ 2
40.0%
Ⅲ 1
20.0%
Math Operators
ValueCountFrequency (%)
∥ 1
100.0%

소재지지번주소
Text

MISSING 

Distinct4434
Distinct (%)94.0%
Missing5281
Missing (%)52.8%
Memory size156.2 KiB
2024-04-30T08:38:06.891217image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length53
Median length47
Mean length21.549057
Min length12

Characters and Unicode

Total characters101690
Distinct characters557
Distinct categories13 ?
Distinct scripts3 ?
Distinct blocks5 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique4210 ?
Unique (%)89.2%

Sample

1st row경상북도 경산시 옥산동 793
2nd row경상남도 합천군 합천읍 합천리 315
3rd row인천광역시 미추홀구 주안동 983 인천가정법원
4th row경기도 이천시 신둔면 수광리 262-1
5th row충청북도 충주시 용산동 453
ValueCountFrequency (%)
경기도 1659
 
7.2%
경상남도 1070
 
4.6%
창원시 409
 
1.8%
서구 389
 
1.7%
용인시 343
 
1.5%
인천광역시 324
 
1.4%
고양시 283
 
1.2%
충청남도 280
 
1.2%
수원시 243
 
1.1%
성남시 226
 
1.0%
Other values (6000) 17892
77.4%
2024-04-30T08:38:07.309775image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
18408
 
18.1%
시 4309
 
4.2%
동 4101
 
4.0%
1 3877
 
3.8%
도 3866
 
3.8%
구 3111
 
3.1%
경 3062
 
3.0%
- 2981
 
2.9%
2 2314
 
2.3%
남 2053
 
2.0%
Other values (547) 53608
52.7%

Most occurring categories

ValueCountFrequency (%)
Other Letter 61628
60.6%
Space Separator 18408
 
18.1%
Decimal Number 18159
 
17.9%
Dash Punctuation 2981
 
2.9%
Uppercase Letter 191
 
0.2%
Close Punctuation 111
 
0.1%
Open Punctuation 111
 
0.1%
Connector Punctuation 37
 
< 0.1%
Lowercase Letter 29
 
< 0.1%
Other Punctuation 18
 
< 0.1%
Other values (3) 17
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
시 4309
 
7.0%
동 4101
 
6.7%
도 3866
 
6.3%
구 3111
 
5.0%
경 3062
 
5.0%
남 2053
 
3.3%
기 1872
 
3.0%
산 1646
 
2.7%
원 1629
 
2.6%
상 1522
 
2.5%
Other values (487) 34457
55.9%
Uppercase Letter
ValueCountFrequency (%)
A 26
13.6%
C 21
 
11.0%
T 16
 
8.4%
B 16
 
8.4%
S 13
 
6.8%
K 11
 
5.8%
M 10
 
5.2%
I 9
 
4.7%
D 8
 
4.2%
O 8
 
4.2%
Other values (14) 53
27.7%
Lowercase Letter
ValueCountFrequency (%)
e 5
17.2%
o 5
17.2%
m 4
13.8%
t 4
13.8%
u 3
10.3%
n 2
 
6.9%
a 2
 
6.9%
c 1
 
3.4%
l 1
 
3.4%
i 1
 
3.4%
Decimal Number
ValueCountFrequency (%)
1 3877
21.4%
2 2314
12.7%
3 1992
11.0%
5 1679
9.2%
4 1678
9.2%
6 1532
 
8.4%
0 1366
 
7.5%
7 1343
 
7.4%
8 1284
 
7.1%
9 1094
 
6.0%
Other Punctuation
ValueCountFrequency (%)
. 12
66.7%
， 2
 
11.1%
, 2
 
11.1%
@ 1
 
5.6%
· 1
 
5.6%
Math Symbol
ValueCountFrequency (%)
~ 11
91.7%
∥ 1
 
8.3%
Letter Number
ValueCountFrequency (%)
Ⅱ 1
50.0%
Ⅲ 1
50.0%
Space Separator
ValueCountFrequency (%)
18408
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 2981
100.0%
Close Punctuation
ValueCountFrequency (%)
) 111
100.0%
Open Punctuation
ValueCountFrequency (%)
( 111
100.0%
Connector Punctuation
ValueCountFrequency (%)
_ 37
100.0%
Other Symbol
ValueCountFrequency (%)
㈜ 3
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 61631
60.6%
Common 39837
39.2%
Latin 222
 
0.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
시 4309
 
7.0%
동 4101
 
6.7%
도 3866
 
6.3%
구 3111
 
5.0%
경 3062
 
5.0%
남 2053
 
3.3%
기 1872
 
3.0%
산 1646
 
2.7%
원 1629
 
2.6%
상 1522
 
2.5%
Other values (488) 34460
55.9%
Latin
ValueCountFrequency (%)
A 26
 
11.7%
C 21
 
9.5%
T 16
 
7.2%
B 16
 
7.2%
S 13
 
5.9%
K 11
 
5.0%
M 10
 
4.5%
I 9
 
4.1%
D 8
 
3.6%
O 8
 
3.6%
Other values (27) 84
37.8%
Common
ValueCountFrequency (%)
18408
46.2%
1 3877
 
9.7%
- 2981
 
7.5%
2 2314
 
5.8%
3 1992
 
5.0%
5 1679
 
4.2%
4 1678
 
4.2%
6 1532
 
3.8%
0 1366
 
3.4%
7 1343
 
3.4%
Other values (12) 2667
 
6.7%

Most occurring blocks

ValueCountFrequency (%)
Hangul 61628
60.6%
ASCII 40053
39.4%
None 6
 
< 0.1%
Number Forms 2
 
< 0.1%
Math Operators 1
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
18408
46.0%
1 3877
 
9.7%
- 2981
 
7.4%
2 2314
 
5.8%
3 1992
 
5.0%
5 1679
 
4.2%
4 1678
 
4.2%
6 1532
 
3.8%
0 1366
 
3.4%
7 1343
 
3.4%
Other values (44) 2883
 
7.2%
Hangul
ValueCountFrequency (%)
시 4309
 
7.0%
동 4101
 
6.7%
도 3866
 
6.3%
구 3111
 
5.0%
경 3062
 
5.0%
남 2053
 
3.3%
기 1872
 
3.0%
산 1646
 
2.7%
원 1629
 
2.6%
상 1522
 
2.5%
Other values (487) 34457
55.9%
None
ValueCountFrequency (%)
㈜ 3
50.0%
， 2
33.3%
· 1
 
16.7%
Math Operators
ValueCountFrequency (%)
∥ 1
100.0%
Number Forms
ValueCountFrequency (%)
Ⅱ 1
50.0%
Ⅲ 1
50.0%

전화번호
Text

MISSING 

Distinct3168
Distinct (%)92.3%
Missing6568
Missing (%)65.7%
Memory size156.2 KiB
2024-04-30T08:38:07.549184image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length13
Median length12
Mean length11.979312
Min length9

Characters and Unicode

Total characters41113
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

Unique3058 ?
Unique (%)89.1%

Sample

1st row02-504-7233
2nd row053-859-5607
3rd row055-934-2574
4th row032-620-4223
5th row031-634-4104
ValueCountFrequency (%)
042-000-0000 86
 
2.5%
031-664-1035 45
 
1.3%
031-666-5489 6
 
0.2%
02-509-6000 4
 
0.1%
031-664-7206 4
 
0.1%
063-320-7262 4
 
0.1%
031-491-1527 4
 
0.1%
02-3392-0455 3
 
0.1%
033-741-4671 3
 
0.1%
033-811-0290 3
 
0.1%
Other values (3158) 3270
95.3%
2024-04-30T08:38:07.920883image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
- 6854
16.7%
0 6801
16.5%
3 4636
11.3%
5 3858
9.4%
1 3551
8.6%
2 3549
8.6%
6 2632
 
6.4%
7 2482
 
6.0%
4 2434
 
5.9%
8 2251
 
5.5%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 34259
83.3%
Dash Punctuation 6854
 
16.7%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 6801
19.9%
3 4636
13.5%
5 3858
11.3%
1 3551
10.4%
2 3549
10.4%
6 2632
 
7.7%
7 2482
 
7.2%
4 2434
 
7.1%
8 2251
 
6.6%
9 2065
 
6.0%
Dash Punctuation
ValueCountFrequency (%)
- 6854
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 41113
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
- 6854
16.7%
0 6801
16.5%
3 4636
11.3%
5 3858
9.4%
1 3551
8.6%
2 3549
8.6%
6 2632
 
6.4%
7 2482
 
6.0%
4 2434
 
5.9%
8 2251
 
5.5%

Most occurring blocks

ValueCountFrequency (%)
ASCII 41113
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
- 6854
16.7%
0 6801
16.5%
3 4636
11.3%
5 3858
9.4%
1 3551
8.6%
2 3549
8.6%
6 2632
 
6.4%
7 2482
 
6.0%
4 2434
 
5.9%
8 2251
 
5.5%

업소구분
Categorical

IMBALANCE 

Distinct8
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
음식점
5353 
집단급식소
4363 
호텔
 
113
대규모점포
 
73
콘도
 
66
Other values (3)
 
32

Length

Max length8
Median length3
Mean length3.8832
Min length2

Unique

Unique1 ?
Unique (%)< 0.1%

Sample

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

Common Values

ValueCountFrequency (%)
음식점 5353
53.5%
집단급식소 4363
43.6%
호텔 113
 
1.1%
대규모점포 73
 
0.7%
콘도 66
 
0.7%
농수산물도매시장 27
 
0.3%
유통센터 4
 
< 0.1%
공판장 1
 
< 0.1%

Length

2024-04-30T08:38:08.047121image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-30T08:38:08.142583image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
음식점 5353
53.5%
집단급식소 4363
43.6%
호텔 113
 
1.1%
대규모점포 73
 
0.7%
콘도 66
 
0.7%
농수산물도매시장 27
 
0.3%
유통센터 4
 
< 0.1%
공판장 1
 
< 0.1%

업소급식인원수
Real number (ℝ)

MISSING  SKEWED  ZEROS 

Distinct567
Distinct (%)16.4%
Missing6540
Missing (%)65.4%
Infinite0
Infinite (%)0.0%
Mean522.732
Minimum0
Maximum372750
Zeros1254
Zeros (%)12.5%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-04-30T08:38:08.264781image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median163
Q3470
95-th percentile1180
Maximum372750
Range372750
Interquartile range (IQR)470

Descriptive statistics

Standard deviation7350.3671
Coefficient of variation (CV)14.061445
Kurtosis2056.9324
Mean522.732
Median Absolute Deviation (MAD)163
Skewness43.668609
Sum1808652.7
Variance54027897
MonotonicityNot monotonic
2024-04-30T08:38:08.389826image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.0 1254
 
12.5%
100.0 163
 
1.6%
300.0 111
 
1.1%
200.0 111
 
1.1%
150.0 89
 
0.9%
1000.0 57
 
0.6%
500.0 56
 
0.6%
120.0 45
 
0.4%
450.0 38
 
0.4%
400.0 36
 
0.4%
Other values (557) 1500
 
15.0%
(Missing) 6540
65.4%
ValueCountFrequency (%)
0.0 1254
12.5%
2.5 1
 
< 0.1%
31.0 1
 
< 0.1%
40.0 1
 
< 0.1%
46.0 1
 
< 0.1%
48.0 1
 
< 0.1%
49.0 1
 
< 0.1%
50.0 5
 
0.1%
55.0 1
 
< 0.1%
58.0 1
 
< 0.1%
ValueCountFrequency (%)
372750.0 1
 
< 0.1%
197200.0 1
 
< 0.1%
91800.0 1
 
< 0.1%
20000.0 1
 
< 0.1%
12600.0 1
 
< 0.1%
3336.0 1
 
< 0.1%
3000.0 5
0.1%
2712.0 1
 
< 0.1%
2671.0 1
 
< 0.1%
2600.0 1
 
< 0.1%

업소면적
Real number (ℝ)

MISSING  SKEWED  ZEROS 

Distinct2260
Distinct (%)49.7%
Missing5455
Missing (%)54.5%
Infinite0
Infinite (%)0.0%
Mean580.70828
Minimum0
Maximum273097
Zeros659
Zeros (%)6.6%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-04-30T08:38:08.522048image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q1200
median270
Q3410
95-th percentile1100
Maximum273097
Range273097
Interquartile range (IQR)210

Descriptive statistics

Standard deviation5130.8699
Coefficient of variation (CV)8.8355377
Kurtosis2001.3281
Mean580.70828
Median Absolute Deviation (MAD)109
Skewness41.551221
Sum2639319.1
Variance26325826
MonotonicityNot monotonic
2024-04-30T08:38:08.659220image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.0 659
 
6.6%
200.0 91
 
0.9%
330.0 68
 
0.7%
100.0 59
 
0.6%
300.0 54
 
0.5%
150.0 42
 
0.4%
250.0 34
 
0.3%
500.0 31
 
0.3%
660.0 31
 
0.3%
400.0 28
 
0.3%
Other values (2250) 3448
34.5%
(Missing) 5455
54.5%
ValueCountFrequency (%)
0.0 659
6.6%
3.997 1
 
< 0.1%
5.0 1
 
< 0.1%
7.86 1
 
< 0.1%
12.0 1
 
< 0.1%
20.18 1
 
< 0.1%
24.0 1
 
< 0.1%
30.0 1
 
< 0.1%
30.557 1
 
< 0.1%
31.0 1
 
< 0.1%
ValueCountFrequency (%)
273097.0 1
< 0.1%
166330.0 1
< 0.1%
64204.0 1
< 0.1%
50000.0 1
< 0.1%
46036.0 1
< 0.1%
40177.25 1
< 0.1%
37418.0 1
< 0.1%
30557.0 1
< 0.1%
28202.45 1
< 0.1%
26462.0 1
< 0.1%

업소객실수
Real number (ℝ)

SKEWED  ZEROS 

Distinct200
Distinct (%)2.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean11.647279
Minimum0
Maximum11900
Zeros9598
Zeros (%)96.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-04-30T08:38:08.971820image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile0
Maximum11900
Range11900
Interquartile range (IQR)0

Descriptive statistics

Standard deviation180.09908
Coefficient of variation (CV)15.46276
Kurtosis2169.686
Mean11.647279
Median Absolute Deviation (MAD)0
Skewness39.794244
Sum116472.79
Variance32435.679
MonotonicityNot monotonic
2024-04-30T08:38:09.084182image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.0 9598
96.0%
1.0 74
 
0.7%
20.0 16
 
0.2%
50.0 13
 
0.1%
100.0 10
 
0.1%
30.0 9
 
0.1%
200.0 5
 
0.1%
40.0 5
 
0.1%
14.4 4
 
< 0.1%
21.0 4
 
< 0.1%
Other values (190) 262
 
2.6%
ValueCountFrequency (%)
0.0 9598
96.0%
1.0 74
 
0.7%
2.0 1
 
< 0.1%
2.16 1
 
< 0.1%
3.0 1
 
< 0.1%
4.32 1
 
< 0.1%
7.0 2
 
< 0.1%
7.2 2
 
< 0.1%
9.0 1
 
< 0.1%
9.6 1
 
< 0.1%
ValueCountFrequency (%)
11900.0 1
< 0.1%
6000.0 1
< 0.1%
4991.8 1
< 0.1%
4200.0 1
< 0.1%
3960.0 1
< 0.1%
3238.08 1
< 0.1%
3150.43 1
< 0.1%
2688.1 1
< 0.1%
2581.39 1
< 0.1%
2414.0 1
< 0.1%

배출량
Text

Distinct1747
Distinct (%)17.5%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2024-04-30T08:38:09.389281image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length10
Median length8
Mean length3.6476
Min length1

Characters and Unicode

Total characters36476
Distinct characters13
Distinct categories3 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1232 ?
Unique (%)12.3%

Sample

1st row12000
2nd row1440
3rd row9296
4th row7200
5th row757
ValueCountFrequency (%)
600 576
 
5.8%
0 445
 
4.5%
900 370
 
3.7%
1200 356
 
3.6%
1500 344
 
3.4%
300 318
 
3.2%
1800 248
 
2.5%
1000 241
 
2.4%
3000 233
 
2.3%
2400 188
 
1.9%
Other values (1737) 6681
66.8%
2024-04-30T08:38:09.815962image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 16880
46.3%
1 3718
 
10.2%
2 3072
 
8.4%
6 2237
 
6.1%
5 2142
 
5.9%
4 2141
 
5.9%
3 2077
 
5.7%
8 1788
 
4.9%
9 1136
 
3.1%
7 1121
 
3.1%
Other values (3) 164
 
0.4%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 36312
99.6%
Other Punctuation 162
 
0.4%
Dash Punctuation 2
 
< 0.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 16880
46.5%
1 3718
 
10.2%
2 3072
 
8.5%
6 2237
 
6.2%
5 2142
 
5.9%
4 2141
 
5.9%
3 2077
 
5.7%
8 1788
 
4.9%
9 1136
 
3.1%
7 1121
 
3.1%
Other Punctuation
ValueCountFrequency (%)
. 153
94.4%
, 9
 
5.6%
Dash Punctuation
ValueCountFrequency (%)
- 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 36476
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 16880
46.3%
1 3718
 
10.2%
2 3072
 
8.4%
6 2237
 
6.1%
5 2142
 
5.9%
4 2141
 
5.9%
3 2077
 
5.7%
8 1788
 
4.9%
9 1136
 
3.1%
7 1121
 
3.1%
Other values (3) 164
 
0.4%

Most occurring blocks

ValueCountFrequency (%)
ASCII 36476
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 16880
46.3%
1 3718
 
10.2%
2 3072
 
8.4%
6 2237
 
6.1%
5 2142
 
5.9%
4 2141
 
5.9%
3 2077
 
5.7%
8 1788
 
4.9%
9 1136
 
3.1%
7 1121
 
3.1%
Other values (3) 164
 
0.4%

자가처리량
Text

MISSING 

Distinct131
Distinct (%)4.0%
Missing6710
Missing (%)67.1%
Memory size156.2 KiB
2024-04-30T08:38:10.042024image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length7
Median length1
Mean length1.1759878
Min length1

Characters and Unicode

Total characters3869
Distinct characters12
Distinct categories3 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique86 ?
Unique (%)2.6%

Sample

1st row0
2nd row0
3rd row0
4th row-
5th row0
ValueCountFrequency (%)
0 2915
88.6%
90 42
 
1.3%
20
 
0.6%
50 19
 
0.6%
99 17
 
0.5%
70 14
 
0.4%
80 12
 
0.4%
40 12
 
0.4%
95 10
 
0.3%
120 10
 
0.3%
Other values (121) 219
 
6.7%
2024-04-30T08:38:10.373991image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 3236
83.6%
9 116
 
3.0%
1 101
 
2.6%
5 86
 
2.2%
2 71
 
1.8%
4 53
 
1.4%
7 49
 
1.3%
3 49
 
1.3%
8 44
 
1.1%
6 36
 
0.9%
Other values (2) 28
 
0.7%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 3841
99.3%
Dash Punctuation 20
 
0.5%
Other Punctuation 8
 
0.2%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 3236
84.2%
9 116
 
3.0%
1 101
 
2.6%
5 86
 
2.2%
2 71
 
1.8%
4 53
 
1.4%
7 49
 
1.3%
3 49
 
1.3%
8 44
 
1.1%
6 36
 
0.9%
Dash Punctuation
ValueCountFrequency (%)
- 20
100.0%
Other Punctuation
ValueCountFrequency (%)
. 8
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 3869
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 3236
83.6%
9 116
 
3.0%
1 101
 
2.6%
5 86
 
2.2%
2 71
 
1.8%
4 53
 
1.4%
7 49
 
1.3%
3 49
 
1.3%
8 44
 
1.1%
6 36
 
0.9%
Other values (2) 28
 
0.7%

Most occurring blocks

ValueCountFrequency (%)
ASCII 3869
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 3236
83.6%
9 116
 
3.0%
1 101
 
2.6%
5 86
 
2.2%
2 71
 
1.8%
4 53
 
1.4%
7 49
 
1.3%
3 49
 
1.3%
8 44
 
1.1%
6 36
 
0.9%
Other values (2) 28
 
0.7%

자가재활용계획량
Text

MISSING 

Distinct87
Distinct (%)3.1%
Missing7207
Missing (%)72.1%
Memory size156.2 KiB
2024-04-30T08:38:10.568715image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length6
Median length1
Mean length1.1052632
Min length1

Characters and Unicode

Total characters3087
Distinct characters13
Distinct categories3 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique55 ?
Unique (%)2.0%

Sample

1st row0
2nd row0
3rd row-
4th row0
5th row0
ValueCountFrequency (%)
0 2590
92.7%
22
 
0.8%
50 11
 
0.4%
30 10
 
0.4%
60 8
 
0.3%
150 8
 
0.3%
3 7
 
0.3%
120 6
 
0.2%
2 6
 
0.2%
100 6
 
0.2%
Other values (77) 119
 
4.3%
2024-04-30T08:38:10.881069image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 2764
89.5%
1 68
 
2.2%
2 52
 
1.7%
5 42
 
1.4%
3 38
 
1.2%
7 23
 
0.7%
4 23
 
0.7%
- 22
 
0.7%
6 20
 
0.6%
9 15
 
0.5%
Other values (3) 20
 
0.6%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 3060
99.1%
Dash Punctuation 22
 
0.7%
Other Punctuation 5
 
0.2%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 2764
90.3%
1 68
 
2.2%
2 52
 
1.7%
5 42
 
1.4%
3 38
 
1.2%
7 23
 
0.8%
4 23
 
0.8%
6 20
 
0.7%
9 15
 
0.5%
8 15
 
0.5%
Other Punctuation
ValueCountFrequency (%)
. 4
80.0%
, 1
 
20.0%
Dash Punctuation
ValueCountFrequency (%)
- 22
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 3087
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 2764
89.5%
1 68
 
2.2%
2 52
 
1.7%
5 42
 
1.4%
3 38
 
1.2%
7 23
 
0.7%
4 23
 
0.7%
- 22
 
0.7%
6 20
 
0.6%
9 15
 
0.5%
Other values (3) 20
 
0.6%

Most occurring blocks

ValueCountFrequency (%)
ASCII 3087
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 2764
89.5%
1 68
 
2.2%
2 52
 
1.7%
5 42
 
1.4%
3 38
 
1.2%
7 23
 
0.7%
4 23
 
0.7%
- 22
 
0.7%
6 20
 
0.6%
9 15
 
0.5%
Other values (3) 20
 
0.6%

위탁재활용계획량
Text

MISSING 

Distinct570
Distinct (%)16.3%
Missing6498
Missing (%)65.0%
Memory size156.2 KiB
2024-04-30T08:38:11.120539image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length7
Median length6
Mean length2.5993718
Min length1

Characters and Unicode

Total characters9103
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

Unique377 ?
Unique (%)10.8%

Sample

1st row12000
2nd row1440
3rd row9296
4th row20
5th row3
ValueCountFrequency (%)
0 857
24.5%
600 108
 
3.1%
20 84
 
2.4%
30 83
 
2.4%
1200 81
 
2.3%
50 79
 
2.3%
60 76
 
2.2%
100 74
 
2.1%
900 74
 
2.1%
300 67
 
1.9%
Other values (560) 1919
54.8%
2024-04-30T08:38:11.462698image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 4403
48.4%
1 966
 
10.6%
2 653
 
7.2%
5 566
 
6.2%
3 528
 
5.8%
6 517
 
5.7%
4 461
 
5.1%
8 368
 
4.0%
7 235
 
2.6%
9 228
 
2.5%
Other values (8) 178
 
2.0%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 8925
98.0%
Other Letter 114
 
1.3%
Other Punctuation 54
 
0.6%
Dash Punctuation 10
 
0.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 4403
49.3%
1 966
 
10.8%
2 653
 
7.3%
5 566
 
6.3%
3 528
 
5.9%
6 517
 
5.8%
4 461
 
5.2%
8 368
 
4.1%
7 235
 
2.6%
9 228
 
2.6%
Other Letter
ValueCountFrequency (%)
화 38
33.3%
사 28
24.6%
료 28
24.6%
퇴 10
 
8.8%
비 10
 
8.8%
Other Punctuation
ValueCountFrequency (%)
. 51
94.4%
, 3
 
5.6%
Dash Punctuation
ValueCountFrequency (%)
- 10
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 8989
98.7%
Hangul 114
 
1.3%

Most frequent character per script

Common
ValueCountFrequency (%)
0 4403
49.0%
1 966
 
10.7%
2 653
 
7.3%
5 566
 
6.3%
3 528
 
5.9%
6 517
 
5.8%
4 461
 
5.1%
8 368
 
4.1%
7 235
 
2.6%
9 228
 
2.5%
Other values (3) 64
 
0.7%
Hangul
ValueCountFrequency (%)
화 38
33.3%
사 28
24.6%
료 28
24.6%
퇴 10
 
8.8%
비 10
 
8.8%

Most occurring blocks

ValueCountFrequency (%)
ASCII 8989
98.7%
Hangul 114
 
1.3%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 4403
49.0%
1 966
 
10.7%
2 653
 
7.3%
5 566
 
6.3%
3 528
 
5.9%
6 517
 
5.8%
4 461
 
5.1%
8 368
 
4.1%
7 235
 
2.6%
9 228
 
2.5%
Other values (3) 64
 
0.7%
Hangul
ValueCountFrequency (%)
화 38
33.3%
사 28
24.6%
료 28
24.6%
퇴 10
 
8.8%
비 10
 
8.8%

관리기관명
Text

Distinct262
Distinct (%)2.6%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2024-04-30T08:38:11.713014image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length18
Median length15
Mean length9.641
Min length2

Characters and Unicode

Total characters96410
Distinct characters149
Distinct categories5 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique78 ?
Unique (%)0.8%

Sample

1st row경기도 과천시청
2nd row경상북도 경산시청
3rd row경상남도 합천군청
4th row인천광역시 미추홀구청
5th row삼척시청 환경과
ValueCountFrequency (%)
경기도 2773
 
13.1%
서울특별시 987
 
4.7%
경상남도 690
 
3.3%
강원도 582
 
2.8%
창원시 449
 
2.1%
강남구청 428
 
2.0%
용인시 355
 
1.7%
서구청 351
 
1.7%
인천광역시 347
 
1.6%
전라남도 343
 
1.6%
Other values (272) 13809
65.4%
2024-04-30T08:38:12.083668image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
11114
 
11.5%
청 8820
 
9.1%
시 8617
 
8.9%
도 6373
 
6.6%
경 4321
 
4.5%
구 4313
 
4.5%
기 2979
 
3.1%
남 2575
 
2.7%
광 2400
 
2.5%
서 2261
 
2.3%
Other values (139) 42637
44.2%

Most occurring categories

ValueCountFrequency (%)
Other Letter 84091
87.2%
Space Separator 11114
 
11.5%
Decimal Number 1187
 
1.2%
Close Punctuation 9
 
< 0.1%
Open Punctuation 9
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
청 8820
 
10.5%
시 8617
 
10.2%
도 6373
 
7.6%
경 4321
 
5.1%
구 4313
 
5.1%
기 2979
 
3.5%
남 2575
 
3.1%
광 2400
 
2.9%
서 2261
 
2.7%
원 2058
 
2.4%
Other values (126) 39374
46.8%
Decimal Number
ValueCountFrequency (%)
0 643
54.2%
1 109
 
9.2%
2 106
 
8.9%
5 72
 
6.1%
3 55
 
4.6%
4 54
 
4.5%
6 48
 
4.0%
9 42
 
3.5%
7 30
 
2.5%
8 28
 
2.4%
Space Separator
ValueCountFrequency (%)
11114
100.0%
Close Punctuation
ValueCountFrequency (%)
) 9
100.0%
Open Punctuation
ValueCountFrequency (%)
( 9
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 84091
87.2%
Common 12319
 
12.8%

Most frequent character per script

Hangul
ValueCountFrequency (%)
청 8820
 
10.5%
시 8617
 
10.2%
도 6373
 
7.6%
경 4321
 
5.1%
구 4313
 
5.1%
기 2979
 
3.5%
남 2575
 
3.1%
광 2400
 
2.9%
서 2261
 
2.7%
원 2058
 
2.4%
Other values (126) 39374
46.8%
Common
ValueCountFrequency (%)
11114
90.2%
0 643
 
5.2%
1 109
 
0.9%
2 106
 
0.9%
5 72
 
0.6%
3 55
 
0.4%
4 54
 
0.4%
6 48
 
0.4%
9 42
 
0.3%
7 30
 
0.2%
Other values (3) 46
 
0.4%

Most occurring blocks

ValueCountFrequency (%)
Hangul 84091
87.2%
ASCII 12319
 
12.8%

Most frequent character per block

ASCII
ValueCountFrequency (%)
11114
90.2%
0 643
 
5.2%
1 109
 
0.9%
2 106
 
0.9%
5 72
 
0.6%
3 55
 
0.4%
4 54
 
0.4%
6 48
 
0.4%
9 42
 
0.3%
7 30
 
0.2%
Other values (3) 46
 
0.4%
Hangul
ValueCountFrequency (%)
청 8820
 
10.5%
시 8617
 
10.2%
도 6373
 
7.6%
경 4321
 
5.1%
구 4313
 
5.1%
기 2979
 
3.5%
남 2575
 
3.1%
광 2400
 
2.9%
서 2261
 
2.7%
원 2058
 
2.4%
Other values (126) 39374
46.8%

데이터기준일자
Date

Distinct88
Distinct (%)0.9%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
Minimum2022-11-14 00:00:00
Maximum2024-04-02 00:00:00
2024-04-30T08:38:12.213165image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-30T08:38:12.321615image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

제공기관코드
Real number (ℝ)

Distinct138
Distinct (%)1.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean4282140.4
Minimum3070000
Maximum6520000
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-04-30T08:38:12.428739image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum3070000
5-th percentile3150000
Q13660000
median4060000
Q34810000
95-th percentile5670000
Maximum6520000
Range3450000
Interquartile range (IQR)1150000

Descriptive statistics

Standard deviation820821.76
Coefficient of variation (CV)0.19168492
Kurtosis-0.24463012
Mean4282140.4
Median Absolute Deviation (MAD)510000
Skewness0.7061858
Sum4.2821404 × 1010
Variance6.7374835 × 1011
MonotonicityNot monotonic
2024-04-30T08:38:12.551526image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
5670000 449
 
4.5%
3220000 428
 
4.3%
4050000 355
 
3.5%
3740000 325
 
3.2%
3940000 283
 
2.8%
5530000 276
 
2.8%
3780000 246
 
2.5%
6520000 242
 
2.4%
3660000 223
 
2.2%
4810000 197
 
2.0%
Other values (128) 6976
69.8%
ValueCountFrequency (%)
3070000 73
 
0.7%
3100000 94
 
0.9%
3130000 139
 
1.4%
3140000 47
 
0.5%
3150000 159
 
1.6%
3200000 47
 
0.5%
3220000 428
4.3%
3250000 5
 
0.1%
3280000 15
 
0.1%
3290000 23
 
0.2%
ValueCountFrequency (%)
6520000 242
2.4%
5700000 76
 
0.8%
5670000 449
4.5%
5600000 52
 
0.5%
5540000 112
 
1.1%
5530000 276
2.8%
5480000 4
 
< 0.1%
5470000 12
 
0.1%
5460000 9
 
0.1%
5450000 13
 
0.1%

제공기관명
Text

Distinct138
Distinct (%)1.4%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2024-04-30T08:38:12.846780image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length12
Median length11
Mean length8.2015
Min length7

Characters and Unicode

Total characters82015
Distinct characters106
Distinct categories2 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row경기도 과천시
2nd row경상북도 경산시
3rd row경상남도 합천군
4th row인천광역시 미추홀구
5th row강원도 삼척시
ValueCountFrequency (%)
경기도 3209
 
16.0%
경상남도 1157
 
5.8%
서울특별시 987
 
4.9%
서구 532
 
2.7%
인천광역시 528
 
2.6%
강원특별자치도 496
 
2.5%
강원도 474
 
2.4%
창원시 449
 
2.2%
강남구 428
 
2.1%
용인시 355
 
1.8%
Other values (122) 11385
56.9%
2024-04-30T08:38:13.236495image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
10000
 
12.2%
시 8938
 
10.9%
도 7312
 
8.9%
경 4796
 
5.8%
기 3239
 
3.9%
남 2939
 
3.6%
구 2895
 
3.5%
광 2400
 
2.9%
서 2127
 
2.6%
원 2097
 
2.6%
Other values (96) 35272
43.0%

Most occurring categories

ValueCountFrequency (%)
Other Letter 72015
87.8%
Space Separator 10000
 
12.2%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
시 8938
 
12.4%
도 7312
 
10.2%
경 4796
 
6.7%
기 3239
 
4.5%
남 2939
 
4.1%
구 2895
 
4.0%
광 2400
 
3.3%
서 2127
 
3.0%
원 2097
 
2.9%
특 1988
 
2.8%
Other values (95) 33284
46.2%
Space Separator
ValueCountFrequency (%)
10000
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 72015
87.8%
Common 10000
 
12.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
시 8938
 
12.4%
도 7312
 
10.2%
경 4796
 
6.7%
기 3239
 
4.5%
남 2939
 
4.1%
구 2895
 
4.0%
광 2400
 
3.3%
서 2127
 
3.0%
원 2097
 
2.9%
특 1988
 
2.8%
Other values (95) 33284
46.2%
Common
ValueCountFrequency (%)
10000
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 72015
87.8%
ASCII 10000
 
12.2%

Most frequent character per block

ASCII
ValueCountFrequency (%)
10000
100.0%
Hangul
ValueCountFrequency (%)
시 8938
 
12.4%
도 7312
 
10.2%
경 4796
 
6.7%
기 3239
 
4.5%
남 2939
 
4.1%
구 2895
 
4.0%
광 2400
 
3.3%
서 2127
 
3.0%
원 2097
 
2.9%
특 1988
 
2.8%
Other values (95) 33284
46.2%

Interactions

2024-04-30T08:38:03.457103image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-30T08:38:02.137952image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-30T08:38:02.581089image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-30T08:38:02.951763image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-30T08:38:03.550479image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-30T08:38:02.306340image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-30T08:38:02.686461image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-30T08:38:03.032206image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-30T08:38:03.637131image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-30T08:38:02.391627image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-30T08:38:02.775250image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-30T08:38:03.113970image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-30T08:38:03.724813image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-30T08:38:02.482908image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-30T08:38:02.854357image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-30T08:38:03.365713image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-04-30T08:38:13.334253image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
업소구분업소급식인원수업소면적업소객실수자가재활용계획량데이터기준일자제공기관코드
업소구분1.0000.0000.2230.2540.1900.4520.306
업소급식인원수0.0001.000NaN0.0000.0000.0000.070
업소면적0.223NaN1.0000.0000.8510.2080.069
업소객실수0.2540.0000.0001.0001.0000.0000.088
자가재활용계획량0.1900.0000.8511.0001.0000.8980.574
데이터기준일자0.4520.0000.2080.0000.8981.0000.978
제공기관코드0.3060.0700.0690.0880.5740.9781.000
2024-04-30T08:38:13.430370image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
업소급식인원수업소면적업소객실수제공기관코드업소구분
업소급식인원수1.000-0.3540.031-0.1720.000
업소면적-0.3541.0000.0420.0110.144
업소객실수0.0310.0421.0000.1460.138
제공기관코드-0.1720.0110.1461.0000.155
업소구분0.0000.1440.1380.1551.000

Missing values

2024-04-30T08:38:03.882006image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-04-30T08:38:04.099396image/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.
2024-04-30T08:38:04.305110image/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

상호명사업자등록번호신고일자소재지도로명주소소재지지번주소전화번호업소구분업소급식인원수업소면적업소객실수배출량자가처리량자가재활용계획량위탁재활용계획량관리기관명데이터기준일자제공기관코드제공기관명
23022도깨비를 물리친 농부네 수제갈비<NA>2017-09-26경기도 과천시 새빛로 25 (문원동, 224)<NA>02-504-7233음식점<NA>265.660.012000<NA><NA>12000경기도 과천시청2023-11-243970000경기도 과천시
17713양지요양병원장례식장214-92-008842020-01-14경상북도 경산시 경산로 174 (옥산동)경상북도 경산시 옥산동 793053-859-5607음식점<NA>100.00.01440001440경상북도 경산시청2023-12-055130000경상북도 경산시
11230합천초등학교611-83-019141997-10-10경상남도 합천군 합천읍 죽죽길 3경상남도 합천군 합천읍 합천리 315055-934-2574집단급식소621.0501.00.09296<NA><NA>9296경상남도 합천군청2023-06-215480000경상남도 합천군
14789삼주외식산업(주)인천가정법원<NA>2020-10-27인천광역시 미추홀구 경원대로 881, 인천가정법원 (주안동)인천광역시 미추홀구 주안동 983 인천가정법원032-620-4223집단급식소110.0110.00.072000020인천광역시 미추홀구청2024-01-233510500인천광역시 미추홀구
7158강원대 삼척캠퍼스 해솔관<NA>2015-01-19강원도 삼척시 중앙로 346<NA><NA>집단급식소<NA><NA>0.0757<NA><NA><NA>삼척시청 환경과2022-11-144240000강원도 삼척시
20383라라코스트<NA>2018-07-02경상북도 문경시 당교로 249<NA><NA>음식점<NA><NA>0.01500<NA><NA><NA>경상북도 문경시청2023-12-055120000경상북도 문경시
22823신둔초등학교126-83-004362015-03-27경기도 이천시 신둔면 경충대로3150번길 82-3경기도 이천시 신둔면 수광리 262-1031-634-4104집단급식소<NA><NA>0.02700<NA><NA><NA>경기도 이천시청2023-11-244070000경기도 이천시
23569댕댕클럽<NA>2019-06-25강원특별자치도 강릉시 사임당로 141<NA><NA>음식점<NA><NA>0.030<NA>3강원특별차지도 강릉시청2023-11-214201000강원특별자치도 강릉시
19275충주공업고등학교303-83-026471999-08-31충청북도 충주시 형설로 120 (용산동)충청북도 충주시 용산동 453<NA>집단급식소<NA>561.00.04185<NA><NA><NA>충청북도 충주시청2023-11-304390000충청북도 충주시
22369보리네생고깃간<NA>2014-05-01인천광역시 남동구 독곡로 52, 2층<NA><NA>음식점<NA><NA>0.0300<NA><NA><NA>인천광역시 남동구청2023-11-273530000인천광역시 남동구
상호명사업자등록번호신고일자소재지도로명주소소재지지번주소전화번호업소구분업소급식인원수업소면적업소객실수배출량자가처리량자가재활용계획량위탁재활용계획량관리기관명데이터기준일자제공기관코드제공기관명
9108주식회사 라온아띠<NA>2022-01-01전라남도 나주시 상야1길 7, (2층 209, 210호 빛가람동, 예가람타워)<NA><NA>음식점<NA><NA>0.0391.8<NA><NA><NA>전라남도 나주시청2023-05-174830000전라남도 나주시
15309우성식당<NA>1994-11-01제주특별자치도 서귀포시 대정읍 영서중로19번길 14<NA><NA>음식점<NA>274.420.018000<NA><NA><NA>제주특별자치도 서귀포시청2024-01-156520000제주특별자치도 서귀포시
14157(주)엔에프 서울과학기술대학교지점(성<NA>2023-05-18서울특별시 노원구 공릉로 232 (공릉동)<NA>070-8290-2388집단급식소<NA><NA>0.01600<NA><NA><NA>서울특별시 노원구청2023-08-033100000서울특별시 노원구
19457제일초등학교135-83-008232021-12-21경기도 용인시 처인구 양지면 중부대로2517번길 42-7_ 제일초등학교경기도 용인시 처인구 양지면 제일리 488-1 제일초등학교031-338-3794집단급식소327.0<NA>0.0166560016656경기도 용인시 처인구청2023-12-054050000경기도 용인시
12357오늘도 든든 카이스트점120-73-003272021-09-09대전광역시 유성구 대학로291(구성동 외10필지 N-11동 지상1층 C-5학생회관 D호)<NA><NA>집단급식소<NA><NA>0.022660<NA><NA><NA>대전광역시 유성구 청소행정과2023-07-143670000대전광역시 유성구
25895하늘잔치394-09-017182020-06-05광주광역시 광산구 하남대로 92, 1층광주광역시 광산구 하남동 748<NA>음식점<NA>274.00.060<NA><NA>60광주광역시 광산구청2023-11-173630000광주광역시 광산구
11566삼척시청구내식당<NA>1998-01-09강원특별자치도 삼척시 중앙로 296<NA><NA>집단급식소<NA><NA>0.0240<NA><NA><NA>강원특별자치도 삼척시청 환경과2023-08-074241000강원특별자치도 삼척시
24486북성촌126-25-220652012-05-03경기도 여주시 세종대왕면 북성산로 10경기도 여주시 세종대왕면 번도리 918-37<NA>음식점<NA>199.350.0600<NA><NA>600경기도 여주시청2023-11-155700000경기도 여주시
9376인천도담초등학교137-83-043492016-03-08인천광역시 서구 청라커낼로 217 도담초등학교 (청라동)인천광역시 서구 청라동 178-8 도담초등학교032-569-7083집단급식소960.0<NA>0.03150003150인천광역시서구2023-06-283560000인천광역시 서구
22201인천주원초등학교<NA>2004-09-20인천광역시 남동구 주안로259번길 28<NA><NA>집단급식소<NA><NA>0.01400<NA><NA><NA>인천광역시 남동구청2023-11-273530000인천광역시 남동구

Duplicate rows

Most frequently occurring

상호명사업자등록번호신고일자소재지도로명주소소재지지번주소전화번호업소구분업소급식인원수업소면적업소객실수배출량자가처리량자가재활용계획량위탁재활용계획량관리기관명데이터기준일자제공기관코드제공기관명# duplicates
0(의)라파의료재단예수요양병원<NA>2014-07-22강원도 강릉시 옥계면 현내시장길 34<NA><NA>집단급식소<NA><NA>0.01200<NA><NA><NA>강원도 강릉시2022-11-244200000강원도 강릉시2
1강릉초등학교<NA>2014-07-10강원도 강릉시 토성로 103 (홍제동)<NA><NA>집단급식소<NA><NA>0.01280<NA><NA><NA>강원도 강릉시2022-11-244200000강원도 강릉시2
2경포초등학교<NA>2014-07-14강원도 강릉시 솔올로 90 (교동)<NA><NA>집단급식소<NA><NA>0.03280<NA><NA><NA>강원도 강릉시2022-11-244200000강원도 강릉시2
3삼성웰스토리(주)KGC인삼공사원주공장893-85-001992015-07-28강원도 원주시 소초면 북원로 2955강원도 원주시 소초면 장양리 1310-33033-741-4671집단급식소<NA>400.00.03000<NA><NA>120강원도 원주시청2022-11-254191000강원특별자치도 원주시2
4샤브20<NA>2022-10-18경상남도 김해시 김해대로2272번안길 37 (봉황동)경상남도 김해시 봉황동 978<NA>음식점<NA><NA>0.01500<NA><NA><NA>경상남도 김해시청2022-11-245350000경상남도 김해시2
5풀무원푸드앤컬처 춘천시청점<NA>2020-06-17강원도 춘천시 시청길 11 춘천시청 (옥천동)<NA><NA>집단급식소<NA><NA>0.07200<NA><NA><NA>강원도 춘천시청2022-11-244180000강원도 춘천시2