Overview

Dataset statistics

Number of variables10
Number of observations287
Missing cells294
Missing cells (%)10.2%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory24.0 KiB
Average record size in memory85.5 B

Variable types

Categorical2
Text3
Numeric5

Dataset

Description대구광역시 북구_음식물폐기물다량배출사업장_20240116
Author대구광역시 북구
URLhttp://data.daegu.go.kr/open/data/dataView.do?dataSetId=15036297&dataSetDetailId=150362971b842193cf4cb_202001291525&provdMethod=FILE

Alerts

위도 is highly overall correlated with 경도High correlation
경도 is highly overall correlated with 위도High correlation
급식인원수 is highly overall correlated with 사업장구분High correlation
사업장구분 is highly overall correlated with 급식인원수High correlation
사업장전화번호 has 7 (2.4%) missing valuesMissing
규모 has 105 (36.6%) missing valuesMissing
급식인원수 has 182 (63.4%) missing valuesMissing

Reproduction

Analysis started2024-03-13 13:47:09.912130
Analysis finished2024-03-13 13:47:13.259042
Duration3.35 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

사업장구분
Categorical

HIGH CORRELATION 

Distinct3
Distinct (%)1.0%
Missing0
Missing (%)0.0%
Memory size2.4 KiB
일반음식점
178 
집단급식소
105 
휴게음식점
 
4

Length

Max length5
Median length5
Mean length5
Min length5

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
일반음식점 178
62.0%
집단급식소 105
36.6%
휴게음식점 4
 
1.4%

Length

2024-03-13T22:47:13.323516image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-13T22:47:13.414221image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
일반음식점 178
62.0%
집단급식소 105
36.6%
휴게음식점 4
 
1.4%

상호
Text

Distinct285
Distinct (%)99.3%
Missing0
Missing (%)0.0%
Memory size2.4 KiB
2024-03-13T22:47:13.645108image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length23
Median length20
Mean length7.5679443
Min length1

Characters and Unicode

Total characters2172
Distinct characters357
Distinct categories9 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique283 ?
Unique (%)98.6%

Sample

1st row동해식당(동해복어)
2nd row(맥)참숯불식육식당
3rd row갈비명가황우리
4th row롯데리아동서변점
5th row맨하탄
ValueCountFrequency (%)
침산점 7
 
2.0%
칠곡점 5
 
1.4%
대구칠곡점 4
 
1.1%
샤브향 3
 
0.9%
주)동우이앤씨 3
 
0.9%
복현점 3
 
0.9%
전원숯불 3
 
0.9%
라라코스트 3
 
0.9%
태전점 3
 
0.9%
벽강물회 2
 
0.6%
Other values (308) 313
89.7%
2024-03-13T22:47:14.025188image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
점 80
 
3.7%
대 71
 
3.3%
학 70
 
3.2%
교 64
 
2.9%
62
 
2.9%
구 57
 
2.6%
원 47
 
2.2%
) 45
 
2.1%
( 45
 
2.1%
등 42
 
1.9%
Other values (347) 1589
73.2%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1981
91.2%
Space Separator 62
 
2.9%
Close Punctuation 45
 
2.1%
Open Punctuation 45
 
2.1%
Uppercase Letter 19
 
0.9%
Decimal Number 15
 
0.7%
Lowercase Letter 3
 
0.1%
Connector Punctuation 1
 
< 0.1%
Other Punctuation 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
점 80
 
4.0%
대 71
 
3.6%
학 70
 
3.5%
교 64
 
3.2%
구 57
 
2.9%
원 47
 
2.4%
등 42
 
2.1%
칠 37
 
1.9%
초 36
 
1.8%
산 35
 
1.8%
Other values (321) 1442
72.8%
Uppercase Letter
ValueCountFrequency (%)
T 4
21.1%
A 3
15.8%
D 3
15.8%
S 2
10.5%
M 2
10.5%
L 1
 
5.3%
B 1
 
5.3%
C 1
 
5.3%
F 1
 
5.3%
K 1
 
5.3%
Decimal Number
ValueCountFrequency (%)
3 5
33.3%
0 2
 
13.3%
2 2
 
13.3%
1 2
 
13.3%
7 1
 
6.7%
8 1
 
6.7%
6 1
 
6.7%
9 1
 
6.7%
Lowercase Letter
ValueCountFrequency (%)
g 1
33.3%
n 1
33.3%
i 1
33.3%
Space Separator
ValueCountFrequency (%)
62
100.0%
Close Punctuation
ValueCountFrequency (%)
) 45
100.0%
Open Punctuation
ValueCountFrequency (%)
( 45
100.0%
Connector Punctuation
ValueCountFrequency (%)
_ 1
100.0%
Other Punctuation
ValueCountFrequency (%)
/ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1981
91.2%
Common 169
 
7.8%
Latin 22
 
1.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
점 80
 
4.0%
대 71
 
3.6%
학 70
 
3.5%
교 64
 
3.2%
구 57
 
2.9%
원 47
 
2.4%
등 42
 
2.1%
칠 37
 
1.9%
초 36
 
1.8%
산 35
 
1.8%
Other values (321) 1442
72.8%
Common
ValueCountFrequency (%)
62
36.7%
) 45
26.6%
( 45
26.6%
3 5
 
3.0%
0 2
 
1.2%
2 2
 
1.2%
1 2
 
1.2%
7 1
 
0.6%
_ 1
 
0.6%
8 1
 
0.6%
Other values (3) 3
 
1.8%
Latin
ValueCountFrequency (%)
T 4
18.2%
A 3
13.6%
D 3
13.6%
S 2
9.1%
M 2
9.1%
g 1
 
4.5%
n 1
 
4.5%
i 1
 
4.5%
L 1
 
4.5%
B 1
 
4.5%
Other values (3) 3
13.6%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1981
91.2%
ASCII 191
 
8.8%

Most frequent character per block

Hangul
ValueCountFrequency (%)
점 80
 
4.0%
대 71
 
3.6%
학 70
 
3.5%
교 64
 
3.2%
구 57
 
2.9%
원 47
 
2.4%
등 42
 
2.1%
칠 37
 
1.9%
초 36
 
1.8%
산 35
 
1.8%
Other values (321) 1442
72.8%
ASCII
ValueCountFrequency (%)
62
32.5%
) 45
23.6%
( 45
23.6%
3 5
 
2.6%
T 4
 
2.1%
A 3
 
1.6%
D 3
 
1.6%
S 2
 
1.0%
0 2
 
1.0%
2 2
 
1.0%
Other values (16) 18
 
9.4%

사업장도로명주소
Text

Distinct279
Distinct (%)97.2%
Missing0
Missing (%)0.0%
Memory size2.4 KiB
2024-03-13T22:47:14.403001image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length44
Median length40
Mean length25.756098
Min length20

Characters and Unicode

Total characters7392
Distinct characters160
Distinct categories9 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique272 ?
Unique (%)94.8%

Sample

1st row대구광역시 북구 검단로 8-5 (복현동)
2nd row대구광역시 북구 유통단지로8길 70 (산격동)
3rd row대구광역시 북구 칠곡중앙대로 373_ B동 (태전동)
4th row대구광역시 북구 호국로 219_ 124_ 202호 (서변동_대성골든프라자1차)
5th row대구광역시 북구 구암로60길 54 (구암동)
ValueCountFrequency (%)
대구광역시 287
 
18.4%
북구 287
 
18.4%
산격동 33
 
2.1%
침산동 33
 
2.1%
동천동 31
 
2.0%
태전동 27
 
1.7%
2층 24
 
1.5%
1층 22
 
1.4%
칠곡중앙대로 21
 
1.3%
구암동 18
 
1.2%
Other values (367) 773
49.7%
2024-03-13T22:47:14.907219image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1273
17.2%
구 622
 
8.4%
동 400
 
5.4%
대 366
 
5.0%
북 312
 
4.2%
시 292
 
4.0%
역 288
 
3.9%
광 287
 
3.9%
) 287
 
3.9%
( 287
 
3.9%
Other values (150) 2978
40.3%

Most occurring categories

ValueCountFrequency (%)
Other Letter 4365
59.1%
Space Separator 1273
 
17.2%
Decimal Number 1028
 
13.9%
Close Punctuation 287
 
3.9%
Open Punctuation 287
 
3.9%
Connector Punctuation 93
 
1.3%
Dash Punctuation 45
 
0.6%
Uppercase Letter 11
 
0.1%
Math Symbol 3
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
구 622
14.2%
동 400
 
9.2%
대 366
 
8.4%
북 312
 
7.1%
시 292
 
6.7%
역 288
 
6.6%
광 287
 
6.6%
로 285
 
6.5%
산 108
 
2.5%
길 88
 
2.0%
Other values (130) 1317
30.2%
Decimal Number
ValueCountFrequency (%)
1 252
24.5%
2 175
17.0%
3 109
10.6%
0 98
 
9.5%
6 82
 
8.0%
5 80
 
7.8%
4 70
 
6.8%
8 63
 
6.1%
7 54
 
5.3%
9 45
 
4.4%
Uppercase Letter
ValueCountFrequency (%)
A 5
45.5%
B 4
36.4%
K 1
 
9.1%
T 1
 
9.1%
Space Separator
ValueCountFrequency (%)
1273
100.0%
Close Punctuation
ValueCountFrequency (%)
) 287
100.0%
Open Punctuation
ValueCountFrequency (%)
( 287
100.0%
Connector Punctuation
ValueCountFrequency (%)
_ 93
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 45
100.0%
Math Symbol
ValueCountFrequency (%)
~ 3
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 4365
59.1%
Common 3016
40.8%
Latin 11
 
0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
구 622
14.2%
동 400
 
9.2%
대 366
 
8.4%
북 312
 
7.1%
시 292
 
6.7%
역 288
 
6.6%
광 287
 
6.6%
로 285
 
6.5%
산 108
 
2.5%
길 88
 
2.0%
Other values (130) 1317
30.2%
Common
ValueCountFrequency (%)
1273
42.2%
) 287
 
9.5%
( 287
 
9.5%
1 252
 
8.4%
2 175
 
5.8%
3 109
 
3.6%
0 98
 
3.2%
_ 93
 
3.1%
6 82
 
2.7%
5 80
 
2.7%
Other values (6) 280
 
9.3%
Latin
ValueCountFrequency (%)
A 5
45.5%
B 4
36.4%
K 1
 
9.1%
T 1
 
9.1%

Most occurring blocks

ValueCountFrequency (%)
Hangul 4365
59.1%
ASCII 3027
40.9%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1273
42.1%
) 287
 
9.5%
( 287
 
9.5%
1 252
 
8.3%
2 175
 
5.8%
3 109
 
3.6%
0 98
 
3.2%
_ 93
 
3.1%
6 82
 
2.7%
5 80
 
2.6%
Other values (10) 291
 
9.6%
Hangul
ValueCountFrequency (%)
구 622
14.2%
동 400
 
9.2%
대 366
 
8.4%
북 312
 
7.1%
시 292
 
6.7%
역 288
 
6.6%
광 287
 
6.6%
로 285
 
6.5%
산 108
 
2.5%
길 88
 
2.0%
Other values (130) 1317
30.2%

위도
Real number (ℝ)

HIGH CORRELATION 

Distinct259
Distinct (%)90.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean45.924353
Minimum35.875259
Maximum128.61493
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size2.7 KiB
2024-03-13T22:47:15.043951image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum35.875259
5-th percentile35.883632
Q135.893671
median35.922686
Q335.943359
95-th percentile128.58169
Maximum128.61493
Range92.739667
Interquartile range (IQR)0.049688505

Descriptive statistics

Standard deviation28.811486
Coefficient of variation (CV)0.62736836
Kurtosis4.4776152
Mean45.924353
Median Absolute Deviation (MAD)0.0243289
Skewness2.5389864
Sum13180.289
Variance830.10171
MonotonicityNot monotonic
2024-03-13T22:47:15.178264image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
35.88368682 4
 
1.4%
35.90261817 4
 
1.4%
128.6145155 3
 
1.0%
128.5652838 3
 
1.0%
35.8890485 3
 
1.0%
35.90437518 3
 
1.0%
35.93516439 2
 
0.7%
35.91962417 2
 
0.7%
35.89119167 2
 
0.7%
35.94288169 2
 
0.7%
Other values (249) 259
90.2%
ValueCountFrequency (%)
35.87525907 1
0.3%
35.8762827 1
0.3%
35.87742336 1
0.3%
35.87750126 1
0.3%
35.87822397 1
0.3%
35.88034857 1
0.3%
35.88060728 1
0.3%
35.88101826 1
0.3%
35.88208925 1
0.3%
35.88233908 1
0.3%
ValueCountFrequency (%)
128.6149256 1
 
0.3%
128.6145155 3
1.0%
128.6130712 2
0.7%
128.6096639 1
 
0.3%
128.6077645 1
 
0.3%
128.5988211 1
 
0.3%
128.5940459 1
 
0.3%
128.5903412 1
 
0.3%
128.5896897 1
 
0.3%
128.5860604 1
 
0.3%

경도
Real number (ℝ)

HIGH CORRELATION 

Distinct259
Distinct (%)90.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean118.5684
Minimum35.878157
Maximum128.63028
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size2.7 KiB
2024-03-13T22:47:15.340380image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum35.878157
5-th percentile35.901614
Q1128.54928
median128.56628
Q3128.59548
95-th percentile128.61765
Maximum128.63028
Range92.752121
Interquartile range (IQR)0.04619465

Descriptive statistics

Standard deviation28.813353
Coefficient of variation (CV)0.24301039
Kurtosis4.4776125
Mean118.5684
Median Absolute Deviation (MAD)0.0213758
Skewness-2.5389859
Sum34029.131
Variance830.20932
MonotonicityNot monotonic
2024-03-13T22:47:15.479445image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
128.5959754 4
 
1.4%
128.5400701 4
 
1.4%
35.88901082 3
 
1.0%
35.95614888 3
 
1.0%
128.5858427 3
 
1.0%
128.6104706 3
 
1.0%
128.5405847 2
 
0.7%
128.546368 2
 
0.7%
128.5906126 2
 
0.7%
128.5592888 2
 
0.7%
Other values (249) 259
90.2%
ValueCountFrequency (%)
35.8781573 1
 
0.3%
35.88186609 1
 
0.3%
35.88427998 1
 
0.3%
35.88456651 1
 
0.3%
35.88892477 1
 
0.3%
35.88900014 1
 
0.3%
35.88901082 3
1.0%
35.89147899 1
 
0.3%
35.89828975 1
 
0.3%
35.8990494 1
 
0.3%
ValueCountFrequency (%)
128.6302786 1
0.3%
128.6278381 1
0.3%
128.6262583 1
0.3%
128.6262001 1
0.3%
128.6241341 1
0.3%
128.6239255 1
0.3%
128.6236426 1
0.3%
128.6230705 1
0.3%
128.622853 1
0.3%
128.622791 1
0.3%

사업장전화번호
Text

MISSING 

Distinct269
Distinct (%)96.1%
Missing7
Missing (%)2.4%
Memory size2.4 KiB
2024-03-13T22:47:15.693991image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length14
Median length12
Mean length11.832143
Min length1

Characters and Unicode

Total characters3313
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

Unique262 ?
Unique (%)93.6%

Sample

1st row053-383-7066
2nd row053-382-9277
3rd row053-326-7700
4th row053-952-5113
5th row053 321 3119
ValueCountFrequency (%)
053-327-2082 3
 
1.1%
053-326-8400 2
 
0.7%
053-327-3233 2
 
0.7%
053-356-1900 2
 
0.7%
070-7017-6864 2
 
0.7%
053-321-2274 2
 
0.7%
053-350-2148 1
 
0.4%
053-313-7337 1
 
0.4%
053-951-2014 1
 
0.4%
070-7766-9460 1
 
0.4%
Other values (260) 260
93.9%
2024-03-13T22:47:16.087463image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
3 688
20.8%
- 548
16.5%
0 491
14.8%
5 449
13.6%
2 275
 
8.3%
1 187
 
5.6%
7 150
 
4.5%
8 145
 
4.4%
6 135
 
4.1%
9 120
 
3.6%
Other values (2) 125
 
3.8%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 2758
83.2%
Dash Punctuation 548
 
16.5%
Space Separator 7
 
0.2%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
3 688
24.9%
0 491
17.8%
5 449
16.3%
2 275
 
10.0%
1 187
 
6.8%
7 150
 
5.4%
8 145
 
5.3%
6 135
 
4.9%
9 120
 
4.4%
4 118
 
4.3%
Dash Punctuation
ValueCountFrequency (%)
- 548
100.0%
Space Separator
ValueCountFrequency (%)
7
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 3313
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
3 688
20.8%
- 548
16.5%
0 491
14.8%
5 449
13.6%
2 275
 
8.3%
1 187
 
5.6%
7 150
 
4.5%
8 145
 
4.4%
6 135
 
4.1%
9 120
 
3.6%
Other values (2) 125
 
3.8%

Most occurring blocks

ValueCountFrequency (%)
ASCII 3313
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
3 688
20.8%
- 548
16.5%
0 491
14.8%
5 449
13.6%
2 275
 
8.3%
1 187
 
5.6%
7 150
 
4.5%
8 145
 
4.4%
6 135
 
4.1%
9 120
 
3.6%
Other values (2) 125
 
3.8%

규모
Real number (ℝ)

MISSING 

Distinct169
Distinct (%)92.9%
Missing105
Missing (%)36.6%
Infinite0
Infinite (%)0.0%
Mean349.58956
Minimum200
Maximum1193.3
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size2.7 KiB
2024-03-13T22:47:16.233495image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum200
5-th percentile203.007
Q1245.85
median288.405
Q3398.41
95-th percentile710.215
Maximum1193.3
Range993.3
Interquartile range (IQR)152.56

Descriptive statistics

Standard deviation166.87209
Coefficient of variation (CV)0.47733717
Kurtosis5.9307541
Mean349.58956
Median Absolute Deviation (MAD)68.05
Skewness2.1937432
Sum63625.3
Variance27846.295
MonotonicityNot monotonic
2024-03-13T22:47:16.377203image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
200.0 5
 
1.7%
264.0 2
 
0.7%
213.4 2
 
0.7%
429.0 2
 
0.7%
393.0 2
 
0.7%
463.49 2
 
0.7%
300.0 2
 
0.7%
228.0 2
 
0.7%
207.0 2
 
0.7%
234.0 2
 
0.7%
Other values (159) 159
55.4%
(Missing) 105
36.6%
ValueCountFrequency (%)
200.0 5
1.7%
201.0 1
 
0.3%
201.64 1
 
0.3%
202.0 1
 
0.3%
202.5 1
 
0.3%
203.0 1
 
0.3%
203.14 1
 
0.3%
204.18 1
 
0.3%
205.8 1
 
0.3%
207.0 2
 
0.7%
ValueCountFrequency (%)
1193.3 1
0.3%
1066.0 1
0.3%
947.16 1
0.3%
864.6 1
0.3%
800.67 1
0.3%
780.75 1
0.3%
780.7 1
0.3%
764.4 1
0.3%
721.04 1
0.3%
711.7 1
0.3%

급식인원수
Real number (ℝ)

HIGH CORRELATION  MISSING 

Distinct63
Distinct (%)60.0%
Missing182
Missing (%)63.4%
Infinite0
Infinite (%)0.0%
Mean535.95238
Minimum100
Maximum2000
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size2.7 KiB
2024-03-13T22:47:16.562250image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum100
5-th percentile120
Q1200
median400
Q3750
95-th percentile1244
Maximum2000
Range1900
Interquartile range (IQR)550

Descriptive statistics

Standard deviation408.47044
Coefficient of variation (CV)0.76213943
Kurtosis0.70315671
Mean535.95238
Median Absolute Deviation (MAD)250
Skewness1.0978579
Sum56275
Variance166848.1
MonotonicityNot monotonic
2024-03-13T22:47:16.719316image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
200 8
 
2.8%
150 7
 
2.4%
400 6
 
2.1%
100 4
 
1.4%
120 4
 
1.4%
300 3
 
1.0%
750 3
 
1.0%
250 3
 
1.0%
700 3
 
1.0%
1000 2
 
0.7%
Other values (53) 62
 
21.6%
(Missing) 182
63.4%
ValueCountFrequency (%)
100 4
1.4%
110 1
 
0.3%
120 4
1.4%
130 1
 
0.3%
150 7
2.4%
180 1
 
0.3%
187 1
 
0.3%
195 1
 
0.3%
200 8
2.8%
212 1
 
0.3%
ValueCountFrequency (%)
2000 1
0.3%
1630 1
0.3%
1450 1
0.3%
1350 1
0.3%
1308 1
0.3%
1250 1
0.3%
1220 1
0.3%
1212 1
0.3%
1200 2
0.7%
1190 1
0.3%

월배출예상
Real number (ℝ)

Distinct61
Distinct (%)21.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1765.3937
Minimum60
Maximum15000
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size2.7 KiB
2024-03-13T22:47:16.866590image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum60
5-th percentile330
Q1900
median1500
Q32100
95-th percentile4320
Maximum15000
Range14940
Interquartile range (IQR)1200

Descriptive statistics

Standard deviation1703.6044
Coefficient of variation (CV)0.96499967
Kurtosis24.765348
Mean1765.3937
Median Absolute Deviation (MAD)600
Skewness4.092545
Sum506668
Variance2902267.8
MonotonicityNot monotonic
2024-03-13T22:47:16.993574image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1500 34
 
11.8%
1200 25
 
8.7%
900 21
 
7.3%
3000 20
 
7.0%
1000 16
 
5.6%
600 15
 
5.2%
2000 14
 
4.9%
1800 12
 
4.2%
2400 10
 
3.5%
450 9
 
3.1%
Other values (51) 111
38.7%
ValueCountFrequency (%)
60 1
 
0.3%
150 1
 
0.3%
200 1
 
0.3%
240 1
 
0.3%
248 1
 
0.3%
270 1
 
0.3%
300 9
3.1%
400 6
2.1%
450 9
3.1%
500 8
2.8%
ValueCountFrequency (%)
15000 1
0.3%
14400 1
0.3%
9360 1
0.3%
9000 1
0.3%
7500 1
0.3%
6900 1
0.3%
6000 1
0.3%
5500 1
0.3%
5400 2
0.7%
5000 1
0.3%

위탁업체상호
Categorical

Distinct34
Distinct (%)11.8%
Missing0
Missing (%)0.0%
Memory size2.4 KiB
(주)앞선환경
90 
제일산업
75 
(주)오케이산업
25 
주)앞선환경
24 
10 
Other values (29)
63 

Length

Max length9
Median length8
Mean length5.7421603
Min length1

Unique

Unique15 ?
Unique (%)5.2%

Sample

1st row주)앞선환경
2nd row(주)앞선환경
3rd row박화숙축사
4th row샛별농장
5th row주)앞선환경

Common Values

ValueCountFrequency (%)
(주)앞선환경 90
31.4%
제일산업 75
26.1%
(주)오케이산업 25
 
8.7%
주)앞선환경 24
 
8.4%
10
 
3.5%
(주)현대그린텍 8
 
2.8%
영남바이오주식회사 4
 
1.4%
이상화축사 4
 
1.4%
송백농장 4
 
1.4%
은채농장 4
 
1.4%
Other values (24) 39
13.6%

Length

2024-03-13T22:47:17.464901image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
주)앞선환경 114
40.3%
제일산업 75
26.5%
주)오케이산업 25
 
8.8%
주)현대그린텍 8
 
2.8%
영남바이오주식회사 4
 
1.4%
이상화축사 4
 
1.4%
송백농장 4
 
1.4%
은채농장 4
 
1.4%
농장 4
 
1.4%
박태복 4
 
1.4%
Other values (23) 37
 
13.1%

Interactions

2024-03-13T22:47:12.336970image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T22:47:10.471162image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T22:47:10.903074image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T22:47:11.343492image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T22:47:11.820751image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T22:47:12.423945image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T22:47:10.554486image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T22:47:10.988102image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T22:47:11.441827image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T22:47:11.900801image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T22:47:12.534001image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T22:47:10.642622image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T22:47:11.072757image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T22:47:11.533094image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T22:47:11.992074image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T22:47:12.613450image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T22:47:10.720488image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T22:47:11.150970image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T22:47:11.625940image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T22:47:12.110734image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T22:47:12.714668image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T22:47:10.817144image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T22:47:11.246144image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T22:47:11.713940image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T22:47:12.238062image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-03-13T22:47:17.559402image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
사업장구분위도경도규모급식인원수월배출예상위탁업체상호
사업장구분1.0000.0000.0000.000NaN0.2140.000
위도0.0001.0001.0000.3610.3230.4260.000
경도0.0001.0001.0000.3610.3230.4260.000
규모0.0000.3610.3611.000NaN0.6250.584
급식인원수NaN0.3230.323NaN1.0000.7110.520
월배출예상0.2140.4260.4260.6250.7111.0000.432
위탁업체상호0.0000.0000.0000.5840.5200.4321.000
2024-03-13T22:47:17.672250image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
위탁업체상호사업장구분
위탁업체상호1.0000.000
사업장구분0.0001.000
2024-03-13T22:47:17.755823image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
위도경도규모급식인원수월배출예상사업장구분위탁업체상호
위도1.000-0.6360.0020.1690.1440.0000.000
경도-0.6361.000-0.1220.022-0.1100.0000.000
규모0.002-0.1221.000NaN0.2230.0000.243
급식인원수0.1690.022NaN1.0000.3751.0000.219
월배출예상0.144-0.1100.2230.3751.0000.1370.173
사업장구분0.0000.0000.0001.0000.1371.0000.000
위탁업체상호0.0000.0000.2430.2190.1730.0001.000

Missing values

2024-03-13T22:47:12.855153image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-03-13T22:47:13.019832image/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.
2024-03-13T22:47:13.179236image/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

사업장구분상호사업장도로명주소위도경도사업장전화번호규모급식인원수월배출예상위탁업체상호
0일반음식점동해식당(동해복어)대구광역시 북구 검단로 8-5 (복현동)35.898724128.615821053-383-7066234.0<NA>3000주)앞선환경
1일반음식점(맥)참숯불식육식당대구광역시 북구 유통단지로8길 70 (산격동)35.905208128.612383053-382-9277635.6<NA>500(주)앞선환경
2일반음식점갈비명가황우리대구광역시 북구 칠곡중앙대로 373_ B동 (태전동)128.54748235.929129053-326-7700721.04<NA>3600박화숙축사
3일반음식점롯데리아동서변점대구광역시 북구 호국로 219_ 124_ 202호 (서변동_대성골든프라자1차)128.59882135.921375053-952-5113251.95<NA>150샛별농장
4일반음식점맨하탄대구광역시 북구 구암로60길 54 (구암동)35.939284128.569264053 321 3119208.0<NA>450주)앞선환경
5일반음식점3바다낙지해물대구광역시 북구 구암로60길 58 (구암동)35.939467128.569581053-322-1187246.0<NA>800(주)앞선환경
6일반음식점원할머니보쌈 대구칠곡점대구광역시 북구 동천로 128-17 (동천동)35.942841128.562647053-325-5353203.0<NA>1200(주)오케이산업
7일반음식점엘파소하우스웨딩대구광역시 북구 유통단지로14길 22 (산격동)35.905216128.610365053-601-3030416.0<NA>1500(주)오케이산업
8일반음식점감포생밀복대구광역시 북구 침산남로7길 2-1 (노원동1가)35.889173128.5798053-353-0038408.0<NA>1000주)앞선환경
9일반음식점예손가손칼국수대구광역시 북구 옥산로 62 (고성동3가)35.884682128.582361053-354-9090213.0<NA>2500은채농장
사업장구분상호사업장도로명주소위도경도사업장전화번호규모급식인원수월배출예상위탁업체상호
277집단급식소칠곡중학교대구광역시 북구 칠곡중앙대로 583 (읍내동)35.948176128.550746053-233-6480<NA>4001500제일산업
278집단급식소침산제이병원대구광역시 북구 침산남로 94_ 다빈치 타워 (침산동)128.5860635.889053-353-4900<NA>1503000
279집단급식소(주)기운찬 (엔유씨 전자구내식당)대구광역시 북구 노원로 280_ 10층 (침산동)128.59034135.900137070-8288-4104<NA>2402400(주)오케이산업
280집단급식소(주)동우이앤씨 매천고등학교대구광역시 북구 매전로 70 (태전동)35.911594128.547237053-327-2082<NA>7503100원일환경(주)
281집단급식소관천초등학교대구광역시 북구 구암로22길 17 (태전동)35.930571128.55204053-321-8886<NA>400800(주)앞선환경
282집단급식소관천중학교대구광역시 북구 구암로22길 7 (태전동)35.931164128.552613053-323-6326<NA>5502100제일산업
283휴게음식점롯데리아구암점대구광역시 북구 학정로 440 (구암동)35.943766128.564253053-323-8585230.0<NA>1200주)앞선환경
284휴게음식점한국맥도날드(유)대구태전점대구광역시 북구 칠곡중앙대로 303 (태전동)35.922766128.546509070-7017-6864350.96<NA>1000주)앞선환경
285휴게음식점한국맥도날드(유)대구침산DT대구광역시 북구 침산로 120 (침산동)35.886913128.591756070-7017-6864546.42<NA>300제일산업
286휴게음식점버거킹대구산격DT점대구광역시 북구 검단로 29 (산격동)35.900557128.615214070-7462-6745249.51<NA>300제일산업