Overview

Dataset statistics

Number of variables16
Number of observations8989
Missing cells33610
Missing cells (%)23.4%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory1.1 MiB
Average record size in memory134.0 B

Variable types

Text7
DateTime1
Categorical2
Numeric6

Dataset

Description음식물 폐기물 다량배출업소 현황(제공표준)
Author경기도
URLhttps://data.gg.go.kr/portal/data/service/selectServicePage.do?&infId=F031UWGYSHGERA2JXNX728777317&infSeq=1

Alerts

업소급식인원수 is highly overall correlated with 업소면적(N/㎡)High correlation
업소면적(N/㎡) is highly overall correlated with 업소급식인원수High correlation
업소객실수 is highly overall correlated with 업소구분High correlation
업소구분 is highly overall correlated with 업소객실수High correlation
업소구분 is highly imbalanced (59.1%)Imbalance
소재지도로명주소 has 95 (1.1%) missing valuesMissing
소재지지번주소 has 139 (1.5%) missing valuesMissing
전화번호 has 5482 (61.0%) missing valuesMissing
업소급식인원수 has 5318 (59.2%) missing valuesMissing
업소면적(N/㎡) has 4727 (52.6%) missing valuesMissing
자가처리량(Kg/일) has 5579 (62.1%) missing valuesMissing
자가재활용계획량(Kg/월) has 6278 (69.8%) missing valuesMissing
위탁재활용계획량(Kg/월) has 5992 (66.7%) missing valuesMissing
업소급식인원수 is highly skewed (γ1 = 36.42145165)Skewed
업소면적(N/㎡) is highly skewed (γ1 = 65.25719572)Skewed
업소객실수 is highly skewed (γ1 = 31.26809805)Skewed
배출량(Kg/월) is highly skewed (γ1 = 46.97761043)Skewed
자가처리량(Kg/일) is highly skewed (γ1 = 58.20524892)Skewed
업소급식인원수 has 1225 (13.6%) zerosZeros
업소면적(N/㎡) has 845 (9.4%) zerosZeros
업소객실수 has 8965 (99.7%) zerosZeros
배출량(Kg/월) has 429 (4.8%) zerosZeros
자가처리량(Kg/일) has 3113 (34.6%) zerosZeros
자가재활용계획량(Kg/월) has 2640 (29.4%) zerosZeros

Reproduction

Analysis started2024-05-10 20:57:51.504259
Analysis finished2024-05-10 20:58:08.509032
Duration17 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

상호명
Text

Distinct8685
Distinct (%)96.6%
Missing0
Missing (%)0.0%
Memory size70.4 KiB
2024-05-10T20:58:08.889489image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length27
Median length22
Mean length8.3480921
Min length1

Characters and Unicode

Total characters75041
Distinct characters935
Distinct categories12 ?
Distinct scripts4 ?
Distinct blocks5 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique8458 ?
Unique (%)94.1%

Sample

1st row(㈜에스디인터내셔날
2nd row(경복궁)개성손만두
3rd row(복)동광원
4th row(사)우리들행복나눔세자매도시락사업단
5th row(사)워치타워성서책자협회
ValueCountFrequency (%)
주식회사 215
 
1.9%
주)아워홈 79
 
0.7%
명륜진사갈비 38
 
0.3%
주)동원홈푸드 36
 
0.3%
의료법인 36
 
0.3%
주)현대그린푸드 29
 
0.3%
씨제이프레시웨이(주 26
 
0.2%
주)풀무원푸드앤컬처 24
 
0.2%
구내식당 24
 
0.2%
삼성웰스토리(주 23
 
0.2%
Other values (9572) 10992
95.4%
2024-05-10T20:58:09.933639image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
2534
 
3.4%
( 2127
 
2.8%
주 2048
 
2.7%
) 2036
 
2.7%
교 1984
 
2.6%
학 1880
 
2.5%
원 1591
 
2.1%
점 1424
 
1.9%
이 1361
 
1.8%
등 1280
 
1.7%
Other values (925) 56776
75.7%

Most occurring categories

ValueCountFrequency (%)
Other Letter 66198
88.2%
Space Separator 2534
 
3.4%
Open Punctuation 2265
 
3.0%
Close Punctuation 2134
 
2.8%
Uppercase Letter 766
 
1.0%
Decimal Number 442
 
0.6%
Lowercase Letter 338
 
0.5%
Other Symbol 192
 
0.3%
Other Punctuation 127
 
0.2%
Dash Punctuation 25
 
< 0.1%
Other values (2) 20
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
주 2048
 
3.1%
교 1984
 
3.0%
학 1880
 
2.8%
원 1591
 
2.4%
점 1424
 
2.2%
이 1361
 
2.1%
등 1280
 
1.9%
스 1151
 
1.7%
초 994
 
1.5%
리 935
 
1.4%
Other values (848) 51550
77.9%
Uppercase Letter
ValueCountFrequency (%)
C 126
16.4%
S 78
10.2%
T 72
 
9.4%
D 65
 
8.5%
K 55
 
7.2%
G 50
 
6.5%
L 36
 
4.7%
A 36
 
4.7%
M 29
 
3.8%
B 28
 
3.7%
Other values (16) 191
24.9%
Lowercase Letter
ValueCountFrequency (%)
a 58
17.2%
m 47
13.9%
p 46
13.6%
c 27
 
8.0%
e 18
 
5.3%
i 17
 
5.0%
s 15
 
4.4%
t 14
 
4.1%
h 14
 
4.1%
o 13
 
3.8%
Other values (14) 69
20.4%
Decimal Number
ValueCountFrequency (%)
1 109
24.7%
2 90
20.4%
3 40
 
9.0%
0 39
 
8.8%
8 31
 
7.0%
9 31
 
7.0%
7 29
 
6.6%
4 29
 
6.6%
5 25
 
5.7%
6 19
 
4.3%
Other Punctuation
ValueCountFrequency (%)
; 49
38.6%
& 43
33.9%
. 19
 
15.0%
: 6
 
4.7%
/ 5
 
3.9%
, 3
 
2.4%
： 1
 
0.8%
@ 1
 
0.8%
Open Punctuation
ValueCountFrequency (%)
( 2127
93.9%
[ 138
 
6.1%
Close Punctuation
ValueCountFrequency (%)
) 2036
95.4%
] 98
 
4.6%
Space Separator
ValueCountFrequency (%)
2534
100.0%
Other Symbol
ValueCountFrequency (%)
㈜ 192
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 25
100.0%
Connector Punctuation
ValueCountFrequency (%)
_ 19
100.0%
Letter Number
ValueCountFrequency (%)
Ⅱ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 66386
88.5%
Common 7546
 
10.1%
Latin 1105
 
1.5%
Han 4
 
< 0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
주 2048
 
3.1%
교 1984
 
3.0%
학 1880
 
2.8%
원 1591
 
2.4%
점 1424
 
2.1%
이 1361
 
2.1%
등 1280
 
1.9%
스 1151
 
1.7%
초 994
 
1.5%
리 935
 
1.4%
Other values (845) 51738
77.9%
Latin
ValueCountFrequency (%)
C 126
 
11.4%
S 78
 
7.1%
T 72
 
6.5%
D 65
 
5.9%
a 58
 
5.2%
K 55
 
5.0%
G 50
 
4.5%
m 47
 
4.3%
p 46
 
4.2%
L 36
 
3.3%
Other values (41) 472
42.7%
Common
ValueCountFrequency (%)
2534
33.6%
( 2127
28.2%
) 2036
27.0%
[ 138
 
1.8%
1 109
 
1.4%
] 98
 
1.3%
2 90
 
1.2%
; 49
 
0.6%
& 43
 
0.6%
3 40
 
0.5%
Other values (15) 282
 
3.7%
Han
ValueCountFrequency (%)
前 1
25.0%
眞 1
25.0%
時 1
25.0%
辛 1
25.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 66194
88.2%
ASCII 8649
 
11.5%
None 193
 
0.3%
CJK 4
 
< 0.1%
Number Forms 1
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
2534
29.3%
( 2127
24.6%
) 2036
23.5%
[ 138
 
1.6%
C 126
 
1.5%
1 109
 
1.3%
] 98
 
1.1%
2 90
 
1.0%
S 78
 
0.9%
T 72
 
0.8%
Other values (64) 1241
14.3%
Hangul
ValueCountFrequency (%)
주 2048
 
3.1%
교 1984
 
3.0%
학 1880
 
2.8%
원 1591
 
2.4%
점 1424
 
2.2%
이 1361
 
2.1%
등 1280
 
1.9%
스 1151
 
1.7%
초 994
 
1.5%
리 935
 
1.4%
Other values (844) 51546
77.9%
None
ValueCountFrequency (%)
㈜ 192
99.5%
： 1
 
0.5%
CJK
ValueCountFrequency (%)
前 1
25.0%
眞 1
25.0%
時 1
25.0%
辛 1
25.0%
Number Forms
ValueCountFrequency (%)
Ⅱ 1
100.0%

사업자등록번호
Text

Distinct4108
Distinct (%)45.7%
Missing0
Missing (%)0.0%
Memory size70.4 KiB
2024-05-10T20:58:10.403699image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length12
Median length12
Mean length6.6584715
Min length1

Characters and Unicode

Total characters59853
Distinct characters12
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique3862 ?
Unique (%)43.0%

Sample

1st rowN
2nd row651-17-00994
3rd rowN
4th rowN
5th rowN
ValueCountFrequency (%)
n 4365
48.6%
603-81-11270 49
 
0.5%
214-86-08930 28
 
0.3%
711-81-01637 28
 
0.3%
104-81-39349 18
 
0.2%
101-86-76277 15
 
0.2%
215-86-65235 15
 
0.2%
656-81-02756 15
 
0.2%
134-06-10803 11
 
0.1%
134-81-37774 9
 
0.1%
Other values (4098) 4436
49.3%
2024-05-10T20:58:11.260338image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
- 9248
15.5%
1 7253
12.1%
0 7202
12.0%
2 5409
9.0%
8 5280
8.8%
3 4933
8.2%
N 4365
7.3%
4 3633
 
6.1%
5 3381
 
5.6%
6 3345
 
5.6%
Other values (2) 5804
9.7%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 46240
77.3%
Dash Punctuation 9248
 
15.5%
Uppercase Letter 4365
 
7.3%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 7253
15.7%
0 7202
15.6%
2 5409
11.7%
8 5280
11.4%
3 4933
10.7%
4 3633
7.9%
5 3381
7.3%
6 3345
7.2%
7 3026
6.5%
9 2778
 
6.0%
Dash Punctuation
ValueCountFrequency (%)
- 9248
100.0%
Uppercase Letter
ValueCountFrequency (%)
N 4365
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 55488
92.7%
Latin 4365
 
7.3%

Most frequent character per script

Common
ValueCountFrequency (%)
- 9248
16.7%
1 7253
13.1%
0 7202
13.0%
2 5409
9.7%
8 5280
9.5%
3 4933
8.9%
4 3633
 
6.5%
5 3381
 
6.1%
6 3345
 
6.0%
7 3026
 
5.5%
Latin
ValueCountFrequency (%)
N 4365
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 59853
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
- 9248
15.5%
1 7253
12.1%
0 7202
12.0%
2 5409
9.0%
8 5280
8.8%
3 4933
8.2%
N 4365
7.3%
4 3633
 
6.1%
5 3381
 
5.6%
6 3345
 
5.6%
Other values (2) 5804
9.7%

신고일자
Date

Distinct3192
Distinct (%)35.5%
Missing0
Missing (%)0.0%
Memory size70.4 KiB
Minimum1900-12-31 00:00:00
Maximum2024-01-26 00:00:00
2024-05-10T20:58:11.678575image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-10T20:58:12.124955image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

소재지도로명주소
Text

MISSING 

Distinct8419
Distinct (%)94.7%
Missing95
Missing (%)1.1%
Memory size70.4 KiB
2024-05-10T20:58:12.942230image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length71
Median length59
Mean length27.67821
Min length13

Characters and Unicode

Total characters246170
Distinct characters692
Distinct categories13 ?
Distinct scripts4 ?
Distinct blocks6 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique8021 ?
Unique (%)90.2%

Sample

1st row경기도 남양주시 송산로 138
2nd row경기도 용인시 기흥구 청명산로 125_ 1층 (영덕동)
3rd row경기도 수원시 팔달구 팔달로173번길 25-5 (화서동)
4th row경기도 평택시 지제로 170, 1동 1층 102~106호
5th row경기도 안성시 공도읍 신두만곡로 73
ValueCountFrequency (%)
경기도 8895
 
16.7%
용인시 905
 
1.7%
수원시 882
 
1.7%
고양시 819
 
1.5%
1층 742
 
1.4%
안산시 734
 
1.4%
화성시 712
 
1.3%
성남시 659
 
1.2%
단원구 572
 
1.1%
분당구 442
 
0.8%
Other values (9077) 38044
71.2%
2024-05-10T20:58:14.211435image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
44640
 
18.1%
기 9641
 
3.9%
경 9425
 
3.8%
도 9191
 
3.7%
시 8879
 
3.6%
1 8557
 
3.5%
로 8263
 
3.4%
동 7880
 
3.2%
) 6341
 
2.6%
( 6341
 
2.6%
Other values (682) 127012
51.6%

Most occurring categories

ValueCountFrequency (%)
Other Letter 145359
59.0%
Space Separator 44640
 
18.1%
Decimal Number 37138
 
15.1%
Close Punctuation 6341
 
2.6%
Open Punctuation 6341
 
2.6%
Connector Punctuation 2232
 
0.9%
Dash Punctuation 1693
 
0.7%
Other Punctuation 1411
 
0.6%
Uppercase Letter 678
 
0.3%
Math Symbol 225
 
0.1%
Other values (3) 112
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
기 9641
 
6.6%
경 9425
 
6.5%
도 9191
 
6.3%
시 8879
 
6.1%
로 8263
 
5.7%
동 7880
 
5.4%
구 4748
 
3.3%
길 2880
 
2.0%
산 2730
 
1.9%
원 2655
 
1.8%
Other values (613) 79067
54.4%
Uppercase Letter
ValueCountFrequency (%)
B 130
19.2%
A 114
16.8%
C 64
 
9.4%
T 42
 
6.2%
S 35
 
5.2%
K 33
 
4.9%
I 30
 
4.4%
R 26
 
3.8%
D 22
 
3.2%
L 22
 
3.2%
Other values (16) 160
23.6%
Lowercase Letter
ValueCountFrequency (%)
m 14
13.9%
a 13
12.9%
c 10
9.9%
p 9
8.9%
o 8
7.9%
e 8
7.9%
b 6
 
5.9%
u 5
 
5.0%
i 5
 
5.0%
t 5
 
5.0%
Other values (7) 18
17.8%
Decimal Number
ValueCountFrequency (%)
1 8557
23.0%
2 5868
15.8%
3 3870
10.4%
0 3137
 
8.4%
4 3097
 
8.3%
5 3070
 
8.3%
6 2620
 
7.1%
7 2565
 
6.9%
8 2244
 
6.0%
9 2110
 
5.7%
Other Punctuation
ValueCountFrequency (%)
, 1367
96.9%
. 28
 
2.0%
& 8
 
0.6%
; 8
 
0.6%
Math Symbol
ValueCountFrequency (%)
~ 223
99.1%
∥ 1
 
0.4%
∼ 1
 
0.4%
Letter Number
ValueCountFrequency (%)
Ⅱ 3
37.5%
Ⅰ 3
37.5%
Ⅲ 2
25.0%
Space Separator
ValueCountFrequency (%)
44640
100.0%
Close Punctuation
ValueCountFrequency (%)
) 6341
100.0%
Open Punctuation
ValueCountFrequency (%)
( 6341
100.0%
Connector Punctuation
ValueCountFrequency (%)
_ 2232
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 1693
100.0%
Other Symbol
ValueCountFrequency (%)
㈜ 3
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 145361
59.0%
Common 100021
40.6%
Latin 787
 
0.3%
Han 1
 
< 0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
기 9641
 
6.6%
경 9425
 
6.5%
도 9191
 
6.3%
시 8879
 
6.1%
로 8263
 
5.7%
동 7880
 
5.4%
구 4748
 
3.3%
길 2880
 
2.0%
산 2730
 
1.9%
원 2655
 
1.8%
Other values (613) 79069
54.4%
Latin
ValueCountFrequency (%)
B 130
16.5%
A 114
14.5%
C 64
 
8.1%
T 42
 
5.3%
S 35
 
4.4%
K 33
 
4.2%
I 30
 
3.8%
R 26
 
3.3%
D 22
 
2.8%
L 22
 
2.8%
Other values (36) 269
34.2%
Common
ValueCountFrequency (%)
44640
44.6%
1 8557
 
8.6%
) 6341
 
6.3%
( 6341
 
6.3%
2 5868
 
5.9%
3 3870
 
3.9%
0 3137
 
3.1%
4 3097
 
3.1%
5 3070
 
3.1%
6 2620
 
2.6%
Other values (12) 12480
 
12.5%
Han
ValueCountFrequency (%)
家 1
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 145358
59.0%
ASCII 100798
40.9%
Number Forms 8
 
< 0.1%
None 3
 
< 0.1%
Math Operators 2
 
< 0.1%
CJK 1
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
44640
44.3%
1 8557
 
8.5%
) 6341
 
6.3%
( 6341
 
6.3%
2 5868
 
5.8%
3 3870
 
3.8%
0 3137
 
3.1%
4 3097
 
3.1%
5 3070
 
3.0%
6 2620
 
2.6%
Other values (53) 13257
 
13.2%
Hangul
ValueCountFrequency (%)
기 9641
 
6.6%
경 9425
 
6.5%
도 9191
 
6.3%
시 8879
 
6.1%
로 8263
 
5.7%
동 7880
 
5.4%
구 4748
 
3.3%
길 2880
 
2.0%
산 2730
 
1.9%
원 2655
 
1.8%
Other values (612) 79066
54.4%
Number Forms
ValueCountFrequency (%)
Ⅱ 3
37.5%
Ⅰ 3
37.5%
Ⅲ 2
25.0%
None
ValueCountFrequency (%)
㈜ 3
100.0%
CJK
ValueCountFrequency (%)
家 1
100.0%
Math Operators
ValueCountFrequency (%)
∥ 1
50.0%
∼ 1
50.0%

소재지지번주소
Text

MISSING 

Distinct8117
Distinct (%)91.7%
Missing139
Missing (%)1.5%
Memory size70.4 KiB
2024-05-10T20:58:14.956861image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length72
Median length50
Mean length22.769605
Min length11

Characters and Unicode

Total characters201511
Distinct characters621
Distinct categories13 ?
Distinct scripts4 ?
Distinct blocks6 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique7603 ?
Unique (%)85.9%

Sample

1st row경기도 남양주시 별내동 86-5번지
2nd row경기도 용인시 기흥구 영덕동 130-12
3rd row경기도 수원시 팔달구 화서동 41-4
4th row경기도 평택시 지제동 302-6번지 1동 1층 102~106호
5th row경기도 안성시 공도읍 양기리 377번지
ValueCountFrequency (%)
경기도 8851
 
19.4%
용인시 909
 
2.0%
수원시 866
 
1.9%
고양시 822
 
1.8%
안산시 741
 
1.6%
화성시 705
 
1.5%
성남시 646
 
1.4%
단원구 579
 
1.3%
분당구 430
 
0.9%
기흥구 416
 
0.9%
Other values (9500) 30610
67.2%
2024-05-10T20:58:16.137282image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
36728
 
18.2%
기 9401
 
4.7%
도 9093
 
4.5%
경 8928
 
4.4%
시 8649
 
4.3%
동 7900
 
3.9%
1 7613
 
3.8%
- 5730
 
2.8%
지 4846
 
2.4%
2 4845
 
2.4%
Other values (611) 97778
48.5%

Most occurring categories

ValueCountFrequency (%)
Other Letter 121492
60.3%
Space Separator 36728
 
18.2%
Decimal Number 36264
 
18.0%
Dash Punctuation 5730
 
2.8%
Uppercase Letter 506
 
0.3%
Other Punctuation 192
 
0.1%
Close Punctuation 170
 
0.1%
Open Punctuation 170
 
0.1%
Math Symbol 96
 
< 0.1%
Connector Punctuation 91
 
< 0.1%
Other values (3) 72
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
기 9401
 
7.7%
도 9093
 
7.5%
경 8928
 
7.3%
시 8649
 
7.1%
동 7900
 
6.5%
지 4846
 
4.0%
구 4578
 
3.8%
번 4067
 
3.3%
리 2442
 
2.0%
산 2412
 
2.0%
Other values (544) 59176
48.7%
Uppercase Letter
ValueCountFrequency (%)
A 85
16.8%
B 70
13.8%
C 43
 
8.5%
T 35
 
6.9%
S 28
 
5.5%
K 24
 
4.7%
I 23
 
4.5%
L 21
 
4.2%
M 19
 
3.8%
D 19
 
3.8%
Other values (16) 139
27.5%
Lowercase Letter
ValueCountFrequency (%)
c 9
14.3%
m 9
14.3%
a 7
11.1%
t 6
9.5%
o 5
7.9%
i 4
 
6.3%
e 4
 
6.3%
l 3
 
4.8%
u 3
 
4.8%
b 3
 
4.8%
Other values (6) 10
15.9%
Decimal Number
ValueCountFrequency (%)
1 7613
21.0%
2 4845
13.4%
3 3800
10.5%
4 3276
9.0%
5 3229
8.9%
6 3063
8.4%
7 2807
 
7.7%
0 2803
 
7.7%
8 2523
 
7.0%
9 2305
 
6.4%
Other Punctuation
ValueCountFrequency (%)
, 159
82.8%
. 20
 
10.4%
& 8
 
4.2%
; 5
 
2.6%
Letter Number
ValueCountFrequency (%)
Ⅱ 3
37.5%
Ⅰ 3
37.5%
Ⅲ 2
25.0%
Math Symbol
ValueCountFrequency (%)
~ 95
99.0%
∥ 1
 
1.0%
Space Separator
ValueCountFrequency (%)
36728
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 5730
100.0%
Close Punctuation
ValueCountFrequency (%)
) 170
100.0%
Open Punctuation
ValueCountFrequency (%)
( 170
100.0%
Connector Punctuation
ValueCountFrequency (%)
_ 91
100.0%
Other Symbol
ValueCountFrequency (%)
㈜ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 121492
60.3%
Common 79441
39.4%
Latin 577
 
0.3%
Han 1
 
< 0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
기 9401
 
7.7%
도 9093
 
7.5%
경 8928
 
7.3%
시 8649
 
7.1%
동 7900
 
6.5%
지 4846
 
4.0%
구 4578
 
3.8%
번 4067
 
3.3%
리 2442
 
2.0%
산 2412
 
2.0%
Other values (544) 59176
48.7%
Latin
ValueCountFrequency (%)
A 85
14.7%
B 70
 
12.1%
C 43
 
7.5%
T 35
 
6.1%
S 28
 
4.9%
K 24
 
4.2%
I 23
 
4.0%
L 21
 
3.6%
M 19
 
3.3%
D 19
 
3.3%
Other values (35) 210
36.4%
Common
ValueCountFrequency (%)
36728
46.2%
1 7613
 
9.6%
- 5730
 
7.2%
2 4845
 
6.1%
3 3800
 
4.8%
4 3276
 
4.1%
5 3229
 
4.1%
6 3063
 
3.9%
7 2807
 
3.5%
0 2803
 
3.5%
Other values (11) 5547
 
7.0%
Han
ValueCountFrequency (%)
家 1
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 121491
60.3%
ASCII 80009
39.7%
Number Forms 8
 
< 0.1%
CJK 1
 
< 0.1%
Math Operators 1
 
< 0.1%
None 1
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
36728
45.9%
1 7613
 
9.5%
- 5730
 
7.2%
2 4845
 
6.1%
3 3800
 
4.7%
4 3276
 
4.1%
5 3229
 
4.0%
6 3063
 
3.8%
7 2807
 
3.5%
0 2803
 
3.5%
Other values (52) 6115
 
7.6%
Hangul
ValueCountFrequency (%)
기 9401
 
7.7%
도 9093
 
7.5%
경 8928
 
7.3%
시 8649
 
7.1%
동 7900
 
6.5%
지 4846
 
4.0%
구 4578
 
3.8%
번 4067
 
3.3%
리 2442
 
2.0%
산 2412
 
2.0%
Other values (543) 59175
48.7%
Number Forms
ValueCountFrequency (%)
Ⅱ 3
37.5%
Ⅰ 3
37.5%
Ⅲ 2
25.0%
CJK
ValueCountFrequency (%)
家 1
100.0%
Math Operators
ValueCountFrequency (%)
∥ 1
100.0%
None
ValueCountFrequency (%)
㈜ 1
100.0%

전화번호
Text

MISSING 

Distinct3229
Distinct (%)92.1%
Missing5482
Missing (%)61.0%
Memory size70.4 KiB
2024-05-10T20:58:16.900989image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length13
Median length12
Mean length12.030796
Min length9

Characters and Unicode

Total characters42192
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

Unique3131 ?
Unique (%)89.3%

Sample

1st row031-205-2500
2nd row031-273-2756
3rd row031-405-4691
4th row070-7209-0563
5th row031-659-7730
ValueCountFrequency (%)
031-664-1035 106
 
3.0%
031-666-5489 17
 
0.5%
031-664-7206 8
 
0.2%
031-667-7788 7
 
0.2%
02-509-6000 6
 
0.2%
031-663-8975 6
 
0.2%
031-667-9064 5
 
0.1%
031-667-7744 5
 
0.1%
031-651-5222 5
 
0.1%
031-527-3216 5
 
0.1%
Other values (3219) 3337
95.2%
2024-05-10T20:58:18.123720image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
- 7005
16.6%
0 6421
15.2%
3 5724
13.6%
1 5473
13.0%
2 2788
 
6.6%
6 2648
 
6.3%
9 2602
 
6.2%
5 2551
 
6.0%
7 2431
 
5.8%
8 2351
 
5.6%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 35187
83.4%
Dash Punctuation 7005
 
16.6%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 6421
18.2%
3 5724
16.3%
1 5473
15.6%
2 2788
7.9%
6 2648
7.5%
9 2602
7.4%
5 2551
 
7.2%
7 2431
 
6.9%
8 2351
 
6.7%
4 2198
 
6.2%
Dash Punctuation
ValueCountFrequency (%)
- 7005
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 42192
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
- 7005
16.6%
0 6421
15.2%
3 5724
13.6%
1 5473
13.0%
2 2788
 
6.6%
6 2648
 
6.3%
9 2602
 
6.2%
5 2551
 
6.0%
7 2431
 
5.8%
8 2351
 
5.6%

Most occurring blocks

ValueCountFrequency (%)
ASCII 42192
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
- 7005
16.6%
0 6421
15.2%
3 5724
13.6%
1 5473
13.0%
2 2788
 
6.6%
6 2648
 
6.3%
9 2602
 
6.2%
5 2551
 
6.0%
7 2431
 
5.8%
8 2351
 
5.6%

업소구분
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct6
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size70.4 KiB
음식점
4980 
집단급식소
3944 
대규모점포
 
32
호텔
 
22
콘도
 
6

Length

Max length8
Median length3
Mean length3.884303
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
음식점 4980
55.4%
집단급식소 3944
43.9%
대규모점포 32
 
0.4%
호텔 22
 
0.2%
콘도 6
 
0.1%
농수산물도매시장 5
 
0.1%

Length

2024-05-10T20:58:18.567541image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-10T20:58:18.931019image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
음식점 4980
55.4%
집단급식소 3944
43.9%
대규모점포 32
 
0.4%
호텔 22
 
0.2%
콘도 6
 
0.1%
농수산물도매시장 5
 
0.1%

업소급식인원수
Real number (ℝ)

HIGH CORRELATION  MISSING  SKEWED  ZEROS 

Distinct547
Distinct (%)14.9%
Missing5318
Missing (%)59.2%
Infinite0
Infinite (%)0.0%
Mean502.74503
Minimum0
Maximum197200
Zeros1225
Zeros (%)13.6%
Negative0
Negative (%)0.0%
Memory size79.1 KiB
2024-05-10T20:58:19.326277image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median200
Q3550
95-th percentile1268.5
Maximum197200
Range197200
Interquartile range (IQR)550

Descriptive statistics

Standard deviation4460.4663
Coefficient of variation (CV)8.8722235
Kurtosis1429.2103
Mean502.74503
Median Absolute Deviation (MAD)200
Skewness36.421452
Sum1845577
Variance19895759
MonotonicityNot monotonic
2024-05-10T20:58:19.794568image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 1225
 
13.6%
200 145
 
1.6%
100 124
 
1.4%
150 91
 
1.0%
300 86
 
1.0%
120 59
 
0.7%
750 56
 
0.6%
250 51
 
0.6%
450 51
 
0.6%
500 50
 
0.6%
Other values (537) 1733
 
19.3%
(Missing) 5318
59.2%
ValueCountFrequency (%)
0 1225
13.6%
40 1
 
< 0.1%
55 1
 
< 0.1%
60 4
 
< 0.1%
65 1
 
< 0.1%
70 1
 
< 0.1%
74 1
 
< 0.1%
75 3
 
< 0.1%
77 1
 
< 0.1%
80 3
 
< 0.1%
ValueCountFrequency (%)
197200 1
 
< 0.1%
150473 1
 
< 0.1%
91800 1
 
< 0.1%
47450 1
 
< 0.1%
20000 1
 
< 0.1%
6000 1
 
< 0.1%
5000 1
 
< 0.1%
3450 1
 
< 0.1%
3400 1
 
< 0.1%
3000 7
0.1%

업소면적(N/㎡)
Real number (ℝ)

HIGH CORRELATION  MISSING  SKEWED  ZEROS 

Distinct2083
Distinct (%)48.9%
Missing4727
Missing (%)52.6%
Infinite0
Infinite (%)0.0%
Mean2200.5641
Minimum0
Maximum7494851
Zeros845
Zeros (%)9.4%
Negative0
Negative (%)0.0%
Memory size79.1 KiB
2024-05-10T20:58:20.253476image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q1200.52
median261.98
Q3386.2675
95-th percentile973.057
Maximum7494851
Range7494851
Interquartile range (IQR)185.7475

Descriptive statistics

Standard deviation114812.79
Coefficient of variation (CV)52.174254
Kurtosis4259.6593
Mean2200.5641
Median Absolute Deviation (MAD)94.02
Skewness65.257196
Sum9378804.1
Variance1.3181976 × 1010
MonotonicityNot monotonic
2024-05-10T20:58:20.675652image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.0 845
 
9.4%
200.0 73
 
0.8%
300.0 35
 
0.4%
231.0 30
 
0.3%
230.0 28
 
0.3%
330.0 24
 
0.3%
264.0 23
 
0.3%
250.0 20
 
0.2%
297.0 18
 
0.2%
700.0 17
 
0.2%
Other values (2073) 3149
35.0%
(Missing) 4727
52.6%
ValueCountFrequency (%)
0.0 845
9.4%
1.272 1
 
< 0.1%
10.0 1
 
< 0.1%
49.02 1
 
< 0.1%
60.0 2
 
< 0.1%
62.0 1
 
< 0.1%
80.0 1
 
< 0.1%
99.0 2
 
< 0.1%
99.17 1
 
< 0.1%
100.0 13
 
0.1%
ValueCountFrequency (%)
7494851.0 1
< 0.1%
54737.81 1
< 0.1%
50316.37 1
< 0.1%
40177.25 1
< 0.1%
38285.17 1
< 0.1%
37418.0 1
< 0.1%
33281.0 1
< 0.1%
28985.96 1
< 0.1%
22347.29 1
< 0.1%
22168.0 1
< 0.1%

업소객실수
Real number (ℝ)

HIGH CORRELATION  SKEWED  ZEROS 

Distinct21
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.27500278
Minimum0
Maximum288
Zeros8965
Zeros (%)99.7%
Negative0
Negative (%)0.0%
Memory size79.1 KiB
2024-05-10T20:58:21.018794image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile0
Maximum288
Range288
Interquartile range (IQR)0

Descriptive statistics

Standard deviation6.4824932
Coefficient of variation (CV)23.572464
Kurtosis1142.3506
Mean0.27500278
Median Absolute Deviation (MAD)0
Skewness31.268098
Sum2472
Variance42.022718
MonotonicityNot monotonic
2024-05-10T20:58:21.341155image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=21)
ValueCountFrequency (%)
0 8965
99.7%
100 3
 
< 0.1%
47 2
 
< 0.1%
70 2
 
< 0.1%
64 1
 
< 0.1%
57 1
 
< 0.1%
288 1
 
< 0.1%
45 1
 
< 0.1%
124 1
 
< 0.1%
167 1
 
< 0.1%
Other values (11) 11
 
0.1%
ValueCountFrequency (%)
0 8965
99.7%
34 1
 
< 0.1%
39 1
 
< 0.1%
41 1
 
< 0.1%
45 1
 
< 0.1%
47 2
 
< 0.1%
52 1
 
< 0.1%
55 1
 
< 0.1%
57 1
 
< 0.1%
64 1
 
< 0.1%
ValueCountFrequency (%)
288 1
 
< 0.1%
287 1
 
< 0.1%
202 1
 
< 0.1%
176 1
 
< 0.1%
167 1
 
< 0.1%
145 1
 
< 0.1%
124 1
 
< 0.1%
100 3
< 0.1%
91 1
 
< 0.1%
71 1
 
< 0.1%

배출량(Kg/월)
Real number (ℝ)

SKEWED  ZEROS 

Distinct1528
Distinct (%)17.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean8022.7814
Minimum0
Maximum4320000
Zeros429
Zeros (%)4.8%
Negative0
Negative (%)0.0%
Memory size79.1 KiB
2024-05-10T20:58:21.753454image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile10.8
Q1600
median1600
Q34230
95-th percentile32064
Maximum4320000
Range4320000
Interquartile range (IQR)3630

Descriptive statistics

Standard deviation68969.789
Coefficient of variation (CV)8.5967429
Kurtosis2533.7522
Mean8022.7814
Median Absolute Deviation (MAD)1150
Skewness46.97761
Sum72116782
Variance4.7568318 × 109
MonotonicityNot monotonic
2024-05-10T20:58:22.628313image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
600.0 682
 
7.6%
0.0 429
 
4.8%
1500.0 343
 
3.8%
900.0 308
 
3.4%
1200.0 306
 
3.4%
3000.0 247
 
2.7%
1000.0 237
 
2.6%
1800.0 233
 
2.6%
2400.0 197
 
2.2%
2000.0 195
 
2.2%
Other values (1518) 5812
64.7%
ValueCountFrequency (%)
0.0 429
4.8%
1.0 2
 
< 0.1%
2.0 1
 
< 0.1%
3.0 6
 
0.1%
5.0 4
 
< 0.1%
6.0 1
 
< 0.1%
10.0 7
 
0.1%
12.0 1
 
< 0.1%
15.0 2
 
< 0.1%
20.0 8
 
0.1%
ValueCountFrequency (%)
4320000.0 1
< 0.1%
3240000.0 1
< 0.1%
2750016.0 1
< 0.1%
1387000.0 1
< 0.1%
613200.0 1
< 0.1%
600000.0 1
< 0.1%
547500.0 1
< 0.1%
480000.0 2
< 0.1%
448800.0 1
< 0.1%
445800.0 1
< 0.1%

자가처리량(Kg/일)
Real number (ℝ)

MISSING  SKEWED  ZEROS 

Distinct79
Distinct (%)2.3%
Missing5579
Missing (%)62.1%
Infinite0
Infinite (%)0.0%
Mean1165.6691
Minimum0
Maximum3240000
Zeros3113
Zeros (%)34.6%
Negative0
Negative (%)0.0%
Memory size79.1 KiB
2024-05-10T20:58:23.188412image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile90
Maximum3240000
Range3240000
Interquartile range (IQR)0

Descriptive statistics

Standard deviation55541.063
Coefficient of variation (CV)47.647365
Kurtosis3395.0938
Mean1165.6691
Median Absolute Deviation (MAD)0
Skewness58.205249
Sum3974931.8
Variance3.0848097 × 109
MonotonicityNot monotonic
2024-05-10T20:58:23.731282image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.0 3113
34.6%
90.0 63
 
0.7%
50.0 20
 
0.2%
80.0 19
 
0.2%
99.0 15
 
0.2%
40.0 13
 
0.1%
60.0 12
 
0.1%
70.0 12
 
0.1%
150.0 10
 
0.1%
100.0 9
 
0.1%
Other values (69) 124
 
1.4%
(Missing) 5579
62.1%
ValueCountFrequency (%)
0.0 3113
34.6%
1.0 1
 
< 0.1%
2.0 1
 
< 0.1%
5.0 1
 
< 0.1%
12.0 1
 
< 0.1%
16.0 2
 
< 0.1%
20.0 6
 
0.1%
22.0 1
 
< 0.1%
25.0 1
 
< 0.1%
29.0 1
 
< 0.1%
ValueCountFrequency (%)
3240000.0 1
 
< 0.1%
54000.0 1
 
< 0.1%
53976.0 1
 
< 0.1%
53280.0 1
 
< 0.1%
41975.0 1
 
< 0.1%
39600.0 1
 
< 0.1%
38640.0 1
 
< 0.1%
35100.0 1
 
< 0.1%
32400.0 3
< 0.1%
32040.0 1
 
< 0.1%

자가재활용계획량(Kg/월)
Real number (ℝ)

MISSING  ZEROS 

Distinct47
Distinct (%)1.7%
Missing6278
Missing (%)69.8%
Infinite0
Infinite (%)0.0%
Mean30.539358
Minimum0
Maximum7000
Zeros2640
Zeros (%)29.4%
Negative0
Negative (%)0.0%
Memory size79.1 KiB
2024-05-10T20:58:24.233345image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile0
Maximum7000
Range7000
Interquartile range (IQR)0

Descriptive statistics

Standard deviation305.974
Coefficient of variation (CV)10.019006
Kurtosis236.78915
Mean30.539358
Median Absolute Deviation (MAD)0
Skewness14.071673
Sum82792.2
Variance93620.091
MonotonicityNot monotonic
2024-05-10T20:58:24.657359image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=47)
ValueCountFrequency (%)
0.0 2640
29.4%
2700.0 5
 
0.1%
600.0 4
 
< 0.1%
30.0 4
 
< 0.1%
1500.0 3
 
< 0.1%
12.0 2
 
< 0.1%
2000.0 2
 
< 0.1%
90.0 2
 
< 0.1%
150.0 2
 
< 0.1%
300.0 2
 
< 0.1%
Other values (37) 45
 
0.5%
(Missing) 6278
69.8%
ValueCountFrequency (%)
0.0 2640
29.4%
5.0 1
 
< 0.1%
5.2 1
 
< 0.1%
7.0 1
 
< 0.1%
10.0 1
 
< 0.1%
12.0 2
 
< 0.1%
24.0 1
 
< 0.1%
25.0 1
 
< 0.1%
27.0 1
 
< 0.1%
30.0 4
 
< 0.1%
ValueCountFrequency (%)
7000.0 1
 
< 0.1%
6300.0 1
 
< 0.1%
4500.0 2
 
< 0.1%
4250.0 1
 
< 0.1%
3360.0 1
 
< 0.1%
3150.0 1
 
< 0.1%
3000.0 1
 
< 0.1%
2700.0 5
0.1%
2400.0 1
 
< 0.1%
2000.0 2
 
< 0.1%

위탁재활용계획량(Kg/월)
Text

MISSING 

Distinct542
Distinct (%)18.1%
Missing5992
Missing (%)66.7%
Memory size70.4 KiB
2024-05-10T20:58:25.295848image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length7
Median length6
Mean length2.7223891
Min length1

Characters and Unicode

Total characters8159
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

Unique346 ?
Unique (%)11.5%

Sample

1st row80
2nd row0
3rd row1500
4th row282
5th row1
ValueCountFrequency (%)
0 713
23.8%
600 113
 
3.8%
1200 85
 
2.8%
900 72
 
2.4%
1500 63
 
2.1%
30 60
 
2.0%
50 60
 
2.0%
40 54
 
1.8%
3000 53
 
1.8%
300 44
 
1.5%
Other values (532) 1680
56.1%
2024-05-10T20:58:26.259392image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 4033
49.4%
1 803
 
9.8%
2 603
 
7.4%
5 540
 
6.6%
6 457
 
5.6%
3 442
 
5.4%
4 433
 
5.3%
8 358
 
4.4%
9 234
 
2.9%
7 210
 
2.6%
Other values (2) 46
 
0.6%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 8113
99.4%
Other Punctuation 45
 
0.6%
Dash Punctuation 1
 
< 0.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 4033
49.7%
1 803
 
9.9%
2 603
 
7.4%
5 540
 
6.7%
6 457
 
5.6%
3 442
 
5.4%
4 433
 
5.3%
8 358
 
4.4%
9 234
 
2.9%
7 210
 
2.6%
Other Punctuation
ValueCountFrequency (%)
. 45
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 8159
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 4033
49.4%
1 803
 
9.8%
2 603
 
7.4%
5 540
 
6.6%
6 457
 
5.6%
3 442
 
5.4%
4 433
 
5.3%
8 358
 
4.4%
9 234
 
2.9%
7 210
 
2.6%
Other values (2) 46
 
0.6%

Most occurring blocks

ValueCountFrequency (%)
ASCII 8159
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 4033
49.4%
1 803
 
9.8%
2 603
 
7.4%
5 540
 
6.6%
6 457
 
5.6%
3 442
 
5.4%
4 433
 
5.3%
8 358
 
4.4%
9 234
 
2.9%
7 210
 
2.6%
Other values (2) 46
 
0.6%

관리기관명
Text

Distinct250
Distinct (%)2.8%
Missing0
Missing (%)0.0%
Memory size70.4 KiB
2024-05-10T20:58:26.782934image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length18
Median length13
Mean length9.628546
Min length1

Characters and Unicode

Total characters86551
Distinct characters74
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique135 ?
Unique (%)1.5%

Sample

1st row경기도 남양주시청
2nd row경기도 용인시 기흥구청
3rd row600
4th row경기도 평택시청
5th row경기도 안성시
ValueCountFrequency (%)
경기도 7793
37.1%
용인시 912
 
4.3%
고양시 822
 
3.9%
안산시 741
 
3.5%
화성시 712
 
3.4%
성남시 659
 
3.1%
단원구청 579
 
2.8%
환경위생과 579
 
2.8%
기흥구청 415
 
2.0%
남양주시청 403
 
1.9%
Other values (249) 7369
35.1%
2024-05-10T20:58:27.764027image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
11995
13.9%
경 8652
 
10.0%
기 8208
 
9.5%
도 7793
 
9.0%
시 7771
 
9.0%
청 6418
 
7.4%
구 2621
 
3.0%
양 1883
 
2.2%
0 1724
 
2.0%
성 1683
 
1.9%
Other values (64) 27803
32.1%

Most occurring categories

ValueCountFrequency (%)
Other Letter 71313
82.4%
Space Separator 11995
 
13.9%
Decimal Number 3243
 
3.7%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
경 8652
 
12.1%
기 8208
 
11.5%
도 7793
 
10.9%
시 7771
 
10.9%
청 6418
 
9.0%
구 2621
 
3.7%
양 1883
 
2.6%
성 1683
 
2.4%
산 1473
 
2.1%
안 1357
 
1.9%
Other values (53) 23454
32.9%
Decimal Number
ValueCountFrequency (%)
0 1724
53.2%
1 306
 
9.4%
2 275
 
8.5%
5 212
 
6.5%
6 163
 
5.0%
3 150
 
4.6%
4 150
 
4.6%
9 100
 
3.1%
8 92
 
2.8%
7 71
 
2.2%
Space Separator
ValueCountFrequency (%)
11995
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 71313
82.4%
Common 15238
 
17.6%

Most frequent character per script

Hangul
ValueCountFrequency (%)
경 8652
 
12.1%
기 8208
 
11.5%
도 7793
 
10.9%
시 7771
 
10.9%
청 6418
 
9.0%
구 2621
 
3.7%
양 1883
 
2.6%
성 1683
 
2.4%
산 1473
 
2.1%
안 1357
 
1.9%
Other values (53) 23454
32.9%
Common
ValueCountFrequency (%)
11995
78.7%
0 1724
 
11.3%
1 306
 
2.0%
2 275
 
1.8%
5 212
 
1.4%
6 163
 
1.1%
3 150
 
1.0%
4 150
 
1.0%
9 100
 
0.7%
8 92
 
0.6%

Most occurring blocks

ValueCountFrequency (%)
Hangul 71313
82.4%
ASCII 15238
 
17.6%

Most frequent character per block

ASCII
ValueCountFrequency (%)
11995
78.7%
0 1724
 
11.3%
1 306
 
2.0%
2 275
 
1.8%
5 212
 
1.4%
6 163
 
1.1%
3 150
 
1.0%
4 150
 
1.0%
9 100
 
0.7%
8 92
 
0.6%
Hangul
ValueCountFrequency (%)
경 8652
 
12.1%
기 8208
 
11.5%
도 7793
 
10.9%
시 7771
 
10.9%
청 6418
 
9.0%
구 2621
 
3.7%
양 1883
 
2.6%
성 1683
 
2.4%
산 1473
 
2.1%
안 1357
 
1.9%
Other values (53) 23454
32.9%

데이터기준일자
Categorical

Distinct23
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size70.4 KiB
2023-11-24
1295 
2023-12-05
912 
2022-12-16
822 
2022-12-12
741 
2023-08-04
712 
Other values (18)
4507 

Length

Max length10
Median length10
Mean length10
Min length10

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2023-05-17
2nd row2023-12-05
3rd row2023-11-24
4th row2023-02-15
5th row2023-12-23

Common Values

ValueCountFrequency (%)
2023-11-24 1295
14.4%
2023-12-05 912
 
10.1%
2022-12-16 822
 
9.1%
2022-12-12 741
 
8.2%
2023-08-04 712
 
7.9%
2023-11-14 659
 
7.3%
2023-05-17 403
 
4.5%
2023-11-13 378
 
4.2%
2023-12-23 312
 
3.5%
2023-06-12 304
 
3.4%
Other values (13) 2451
27.3%

Length

2024-05-10T20:58:28.151786image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
2023-11-24 1295
14.4%
2023-12-05 912
 
10.1%
2022-12-16 822
 
9.1%
2022-12-12 741
 
8.2%
2023-08-04 712
 
7.9%
2023-11-14 659
 
7.3%
2023-05-17 403
 
4.5%
2023-11-13 378
 
4.2%
2023-12-23 312
 
3.5%
2023-06-12 304
 
3.4%
Other values (13) 2451
27.3%

Interactions

2024-05-10T20:58:05.112771image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-10T20:57:56.116251image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-10T20:57:57.669284image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-10T20:57:59.297396image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-10T20:58:00.876027image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-10T20:58:02.954261image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-10T20:58:05.390225image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-10T20:57:56.406485image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-10T20:57:57.942037image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-10T20:57:59.581620image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-10T20:58:01.247607image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-10T20:58:03.531061image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-10T20:58:05.685563image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-10T20:57:56.649415image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-10T20:57:58.251470image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-10T20:57:59.858787image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-10T20:58:01.695201image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-10T20:58:03.868426image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-10T20:58:05.937658image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-10T20:57:56.890830image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-10T20:57:58.485865image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-10T20:58:00.096521image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-10T20:58:01.933291image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-10T20:58:04.150023image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-10T20:58:06.396453image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-10T20:57:57.129503image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-10T20:57:58.750350image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-10T20:58:00.316540image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-10T20:58:02.204303image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-10T20:58:04.466017image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-10T20:58:06.661657image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-10T20:57:57.426097image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-10T20:57:59.010432image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-10T20:58:00.594929image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-10T20:58:02.526815image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-10T20:58:04.794272image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-05-10T20:58:28.394083image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
업소구분업소급식인원수업소면적(N/㎡)업소객실수배출량(Kg/월)자가처리량(Kg/일)자가재활용계획량(Kg/월)데이터기준일자
업소구분1.0000.2900.0000.7740.3110.0000.0000.235
업소급식인원수0.2901.000NaN0.0000.0000.000NaN0.186
업소면적(N/㎡)0.000NaN1.0000.0000.000NaN0.0000.000
업소객실수0.7740.0000.0001.0000.0000.0000.0000.105
배출량(Kg/월)0.3110.0000.0000.0001.0001.0000.0000.050
자가처리량(Kg/일)0.0000.000NaN0.0001.0001.0000.0000.000
자가재활용계획량(Kg/월)0.000NaN0.0000.0000.0000.0001.0000.193
데이터기준일자0.2350.1860.0000.1050.0500.0000.1931.000
2024-05-10T20:58:28.672864image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
데이터기준일자업소구분
데이터기준일자1.0000.108
업소구분0.1081.000
2024-05-10T20:58:28.932406image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
업소급식인원수업소면적(N/㎡)업소객실수배출량(Kg/월)자가처리량(Kg/일)자가재활용계획량(Kg/월)업소구분데이터기준일자
업소급식인원수1.000-0.733-0.0220.3440.020-0.0650.2010.090
업소면적(N/㎡)-0.7331.000-0.0370.0350.033-0.0380.0000.000
업소객실수-0.022-0.0371.000-0.0050.010-0.0060.5190.041
배출량(Kg/월)0.3440.035-0.0051.0000.101-0.0340.1170.023
자가처리량(Kg/일)0.0200.0330.0100.1011.0000.3730.0000.000
자가재활용계획량(Kg/월)-0.065-0.038-0.006-0.0340.3731.0000.0000.065
업소구분0.2010.0000.5190.1170.0000.0001.0000.108
데이터기준일자0.0900.0000.0410.0230.0000.0650.1081.000

Missing values

2024-05-10T20:58:07.094680image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-05-10T20:58:07.653043image/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.
2024-05-10T20:58:08.192656image/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

상호명사업자등록번호신고일자소재지도로명주소소재지지번주소전화번호업소구분업소급식인원수업소면적(N/㎡)업소객실수배출량(Kg/월)자가처리량(Kg/일)자가재활용계획량(Kg/월)위탁재활용계획량(Kg/월)관리기관명데이터기준일자
0(㈜에스디인터내셔날N2020-02-05경기도 남양주시 송산로 138경기도 남양주시 별내동 86-5번지<NA>음식점<NA>229.880390.0<NA><NA><NA>경기도 남양주시청2023-05-17
1(경복궁)개성손만두651-17-009942020-07-10경기도 용인시 기흥구 청명산로 125_ 1층 (영덕동)경기도 용인시 기흥구 영덕동 130-12031-205-2500음식점<NA>246.004800.00.0<NA><NA>경기도 용인시 기흥구청2023-12-05
2(복)동광원N2015-02-16경기도 수원시 팔달구 팔달로173번길 25-5 (화서동)경기도 수원시 팔달구 화서동 41-4<NA>집단급식소<NA><NA>0600.0<NA><NA><NA>6002023-11-24
3(사)우리들행복나눔세자매도시락사업단N1900-12-31경기도 평택시 지제로 170, 1동 1층 102~106호경기도 평택시 지제동 302-6번지 1동 1층 102~106호<NA>음식점<NA>150.000.0<NA><NA><NA>경기도 평택시청2023-02-15
4(사)워치타워성서책자협회N2013-07-25경기도 안성시 공도읍 신두만곡로 73경기도 안성시 공도읍 양기리 377번지<NA>집단급식소<NA><NA>06000.0<NA><NA><NA>경기도 안성시2023-12-23
5(사)청심복지재단N2011-07-22경기도 가평군 설악면 미사리로 191-16경기도 가평군 설악면 송산리 711-1<NA>집단급식소<NA><NA>02340.0<NA><NA><NA>경기도 가평군청 자원순환과2024-02-20
6(사)한국장애인케어협회복음요양병원N2017-03-14경기도 화성시 효행로265번길 16 (기안동)경기도 화성시 기안동 353번지<NA>집단급식소<NA><NA>0600.0<NA><NA><NA>경기도 화성시 동부출장소2023-08-04
7(유)살살녹소212-86-136832020-07-06경기도 용인시 기흥구 석현로12번길 44 (영덕동)경기도 용인시 기흥구 영덕동 1052-2031-273-2756음식점<NA>360.0039852.090.0<NA><NA>경기도 용인시 기흥구청2023-12-05
8(유)서수원 살살녹소N2020-01-21경기도 수원시 권선구 금호로 146 1층 (탑동)경기도 수원시 권선구 탑동 161 1층<NA>음식점<NA><NA>02700.0<NA><NA><NA>27002023-11-24
9(유)아웃백스테이크하우스수원영통점N2017-03-16경기도 수원시 영통구 봉영로 1613 지하1층 (영통동 영통하우스토리)경기도 수원시 영통구 영통동 958-3번지 영통하우스토리 지하1층<NA>음식점<NA><NA>03000.0<NA><NA><NA>30002023-11-24
상호명사업자등록번호신고일자소재지도로명주소소재지지번주소전화번호업소구분업소급식인원수업소면적(N/㎡)업소객실수배출량(Kg/월)자가처리량(Kg/일)자가재활용계획량(Kg/월)위탁재활용계획량(Kg/월)관리기관명데이터기준일자
8979흥천초등학교126-83-018142016-03-11경기도 여주시 흥천면 효자로 155 (흥천초등학교)경기도 여주시 흥천면 효지리 377-3<NA>집단급식소100<NA>0900.0<NA><NA>900경기도 여주시청2023-11-15
8980희가원771-01-015302020-08-01경기도 용인시 수지구 도마치로89번길 4-4 (성복동)경기도 용인시 수지구 성복동 359-10031-263-7766음식점<NA>128.0010800.00.00.00경기도 용인시 수지구청2023-12-05
8981희락보리516-62-005182021-12-24경기도 용인시 처인구 포곡읍 포곡로234번길 10경기도 용인시 처인구 포곡읍 둔전리 84-37<NA>음식점<NA>279.0021600.00.00.021600경기도 용인시 처인구청2023-12-05
8982희래등N2014-01-28경기도 안양시 동안구 경수대로 588 (호계동)경기도 안양시 동안구 호계동 985-5번지<NA>음식점0950.6402333.0<NA><NA><NA>안양시청2023-06-12
8983희망대초등학교129-92-719462013-04-12경기도 성남시 중원구 성남대로 1133 (성남동)경기도 성남시 중원구 성남동 4169 메트로칸빌딩 538호<NA>집단급식소<NA>100.001200.00.00.00경기도 성남시2023-11-14
8984희망찬병원N2009-09-10경기도 화성시 병점중앙로 174 (진안동)경기도 화성시 진안동 868-9번지<NA>집단급식소<NA><NA>01000.0<NA><NA><NA>경기도 화성시 동부출장소2023-08-04
8985희망찬의료소비자생협(우리부모요양병원)N2014-10-13경기도 수원시 영통구 영통로200번길 50 (망포동)경기도 수원시 영통구 망포동 345-1 망포동병원<NA>집단급식소<NA><NA>0600.0<NA><NA><NA>6002023-11-24
8986희성초등학교N2012-05-08경기도 안양시 동안구 학의로 86 (비산동)경기도 안양시 동안구 비산동 1101-1번지<NA>집단급식소10000.00809.166666<NA><NA><NA>안양시청2023-06-12
8987희언유치원129-31-456752013-04-29경기도 성남시 분당구 양현로310번길 7 (야탑동)경기도 성남시 분당구 야탑동 347<NA>음식점<NA>210.350840.00.00.010080경기도 성남시2023-11-14
8988히든패쓰N2022-01-01경기도 오산시 대호로 156-14(궐동)경기도 오산시 궐동 489-9번지<NA>음식점<NA><NA>0300.0<NA><NA><NA>경기도 오산시청2022-11-30