Overview

Dataset statistics

Number of variables8
Number of observations292
Missing cells101
Missing cells (%)4.3%
Duplicate rows1
Duplicate rows (%)0.3%
Total size in memory19.2 KiB
Average record size in memory67.5 B

Variable types

Numeric3
Categorical1
Text3
Boolean1

Dataset

Description인천광역시 부평구 음식물류폐기물 다량배출 사업장 현황에 대한 데이터 자료로 사업장 상호, 소재지, 사업장전화번호, 면적 등의 정보 제공합니다.
Author인천광역시 부평구
URLhttps://data.incheon.go.kr/findData/publicDataDetail?dataId=15034348&srcSe=7661IVAWM27C61E190

Alerts

신규등록(2022) has constant value ""Constant
Dataset has 1 (0.3%) duplicate rowsDuplicates
연번 has 8 (2.7%) missing valuesMissing
상호 has 8 (2.7%) missing valuesMissing
소재지 has 8 (2.7%) missing valuesMissing
사업장전화번호 has 53 (18.2%) missing valuesMissing
면적 has 8 (2.7%) missing valuesMissing
년배출예상 has 8 (2.7%) missing valuesMissing
신규등록(2022) has 8 (2.7%) missing valuesMissing

Reproduction

Analysis started2024-03-18 03:05:08.070034
Analysis finished2024-03-18 03:05:10.995478
Duration2.93 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

연번
Real number (ℝ)

MISSING 

Distinct284
Distinct (%)100.0%
Missing8
Missing (%)2.7%
Infinite0
Infinite (%)0.0%
Mean142.5
Minimum1
Maximum284
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size2.7 KiB
2024-03-18T12:05:11.052743image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile15.15
Q171.75
median142.5
Q3213.25
95-th percentile269.85
Maximum284
Range283
Interquartile range (IQR)141.5

Descriptive statistics

Standard deviation82.127949
Coefficient of variation (CV)0.57633648
Kurtosis-1.2
Mean142.5
Median Absolute Deviation (MAD)71
Skewness0
Sum40470
Variance6745
MonotonicityStrictly increasing
2024-03-18T12:05:11.164784image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
189 1
 
0.3%
195 1
 
0.3%
194 1
 
0.3%
193 1
 
0.3%
192 1
 
0.3%
191 1
 
0.3%
190 1
 
0.3%
188 1
 
0.3%
197 1
 
0.3%
187 1
 
0.3%
Other values (274) 274
93.8%
(Missing) 8
 
2.7%
ValueCountFrequency (%)
1 1
0.3%
2 1
0.3%
3 1
0.3%
4 1
0.3%
5 1
0.3%
6 1
0.3%
7 1
0.3%
8 1
0.3%
9 1
0.3%
10 1
0.3%
ValueCountFrequency (%)
284 1
0.3%
283 1
0.3%
282 1
0.3%
281 1
0.3%
280 1
0.3%
279 1
0.3%
278 1
0.3%
277 1
0.3%
276 1
0.3%
275 1
0.3%

사업장구분
Categorical

Distinct6
Distinct (%)2.1%
Missing0
Missing (%)0.0%
Memory size2.4 KiB
일반음식점
146 
집단급식소
127 
휴게음식점
 
9
<NA>
 
8
관광숙박시설
 
1

Length

Max length6
Median length5
Mean length4.9657534
Min length2

Unique

Unique2 ?
Unique (%)0.7%

Sample

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

Common Values

ValueCountFrequency (%)
일반음식점 146
50.0%
집단급식소 127
43.5%
휴게음식점 9
 
3.1%
<NA> 8
 
2.7%
관광숙박시설 1
 
0.3%
기타 1
 
0.3%

Length

2024-03-18T12:05:11.297022image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-18T12:05:11.394135image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
일반음식점 146
50.0%
집단급식소 127
43.5%
휴게음식점 9
 
3.1%
na 8
 
2.7%
관광숙박시설 1
 
0.3%
기타 1
 
0.3%

상호
Text

MISSING 

Distinct284
Distinct (%)100.0%
Missing8
Missing (%)2.7%
Memory size2.4 KiB
2024-03-18T12:05:11.582873image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length22
Median length18
Mean length7.3274648
Min length2

Characters and Unicode

Total characters2081
Distinct characters364
Distinct categories8 ?
Distinct scripts3 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique284 ?
Unique (%)100.0%

Sample

1st row인천일신초등학교
2nd row부평공업고등학교
3rd row덕수갈비
4th row부일여자중학교
5th row부평여자고등학교
ValueCountFrequency (%)
부평점 7
 
2.1%
주식회사 4
 
1.2%
명륜진사갈비 3
 
0.9%
주)동원홈푸드 3
 
0.9%
푸드 3
 
0.9%
부평시장역점 2
 
0.6%
행복후레쉬 2
 
0.6%
부평구청점 2
 
0.6%
어사출또 2
 
0.6%
피제리아3657 1
 
0.3%
Other values (311) 311
91.5%
2024-03-18T12:05:11.924025image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
교 86
 
4.1%
학 85
 
4.1%
부 80
 
3.8%
인 64
 
3.1%
등 61
 
2.9%
평 57
 
2.7%
천 57
 
2.7%
56
 
2.7%
점 44
 
2.1%
초 43
 
2.1%
Other values (354) 1448
69.6%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1942
93.3%
Space Separator 56
 
2.7%
Close Punctuation 24
 
1.2%
Open Punctuation 24
 
1.2%
Decimal Number 17
 
0.8%
Uppercase Letter 15
 
0.7%
Lowercase Letter 2
 
0.1%
Other Symbol 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
교 86
 
4.4%
학 85
 
4.4%
부 80
 
4.1%
인 64
 
3.3%
등 61
 
3.1%
평 57
 
2.9%
천 57
 
2.9%
점 44
 
2.3%
초 43
 
2.2%
산 39
 
2.0%
Other values (330) 1326
68.3%
Decimal Number
ValueCountFrequency (%)
0 3
17.6%
1 3
17.6%
3 3
17.6%
4 2
11.8%
2 1
 
5.9%
8 1
 
5.9%
9 1
 
5.9%
7 1
 
5.9%
5 1
 
5.9%
6 1
 
5.9%
Uppercase Letter
ValueCountFrequency (%)
T 4
26.7%
D 2
13.3%
K 2
13.3%
S 2
13.3%
I 2
13.3%
P 1
 
6.7%
R 1
 
6.7%
V 1
 
6.7%
Lowercase Letter
ValueCountFrequency (%)
h 1
50.0%
e 1
50.0%
Space Separator
ValueCountFrequency (%)
56
100.0%
Close Punctuation
ValueCountFrequency (%)
) 24
100.0%
Open Punctuation
ValueCountFrequency (%)
( 24
100.0%
Other Symbol
ValueCountFrequency (%)
㈜ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1943
93.4%
Common 121
 
5.8%
Latin 17
 
0.8%

Most frequent character per script

Hangul
ValueCountFrequency (%)
교 86
 
4.4%
학 85
 
4.4%
부 80
 
4.1%
인 64
 
3.3%
등 61
 
3.1%
평 57
 
2.9%
천 57
 
2.9%
점 44
 
2.3%
초 43
 
2.2%
산 39
 
2.0%
Other values (331) 1327
68.3%
Common
ValueCountFrequency (%)
56
46.3%
) 24
19.8%
( 24
19.8%
0 3
 
2.5%
1 3
 
2.5%
3 3
 
2.5%
4 2
 
1.7%
2 1
 
0.8%
8 1
 
0.8%
9 1
 
0.8%
Other values (3) 3
 
2.5%
Latin
ValueCountFrequency (%)
T 4
23.5%
D 2
11.8%
K 2
11.8%
S 2
11.8%
I 2
11.8%
P 1
 
5.9%
R 1
 
5.9%
V 1
 
5.9%
h 1
 
5.9%
e 1
 
5.9%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1942
93.3%
ASCII 138
 
6.6%
None 1
 
< 0.1%

Most frequent character per block

Hangul
ValueCountFrequency (%)
교 86
 
4.4%
학 85
 
4.4%
부 80
 
4.1%
인 64
 
3.3%
등 61
 
3.1%
평 57
 
2.9%
천 57
 
2.9%
점 44
 
2.3%
초 43
 
2.2%
산 39
 
2.0%
Other values (330) 1326
68.3%
ASCII
ValueCountFrequency (%)
56
40.6%
) 24
17.4%
( 24
17.4%
T 4
 
2.9%
0 3
 
2.2%
1 3
 
2.2%
3 3
 
2.2%
D 2
 
1.4%
K 2
 
1.4%
S 2
 
1.4%
Other values (13) 15
 
10.9%
None
ValueCountFrequency (%)
㈜ 1
100.0%

소재지
Text

MISSING 

Distinct232
Distinct (%)81.7%
Missing8
Missing (%)2.7%
Memory size2.4 KiB
2024-03-18T12:05:12.118473image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length45
Median length42.5
Mean length26.327465
Min length21

Characters and Unicode

Total characters7477
Distinct characters148
Distinct categories11 ?
Distinct scripts3 ?
Distinct blocks4 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique182 ?
Unique (%)64.1%

Sample

1st row인천광역시 부평구 항동로75번길 36 (일신동)
2nd row인천광역시 부평구 주부토로 194 (갈산동)
3rd row인천광역시 부평구 마장로 402 (청천동)
4th row인천광역시 부평구 동수로 8 (부평동)
5th row인천광역시 부평구 부흥로243번길 44 (부평동)
ValueCountFrequency (%)
부평구 284
19.2%
인천광역시 283
19.1%
부평동 89
 
6.0%
산곡동 42
 
2.8%
십정동 36
 
2.4%
삼산동 30
 
2.0%
청천동 29
 
2.0%
부개동 28
 
1.9%
경원대로 17
 
1.1%
부평대로 15
 
1.0%
Other values (319) 627
42.4%
2024-03-18T12:05:12.417308image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1219
 
16.3%
부 481
 
6.4%
평 427
 
5.7%
천 336
 
4.5%
동 306
 
4.1%
시 298
 
4.0%
인 297
 
4.0%
구 288
 
3.9%
광 286
 
3.8%
로 286
 
3.8%
Other values (138) 3253
43.5%

Most occurring categories

ValueCountFrequency (%)
Other Letter 4593
61.4%
Space Separator 1219
 
16.3%
Decimal Number 1039
 
13.9%
Open Punctuation 284
 
3.8%
Close Punctuation 284
 
3.8%
Other Punctuation 29
 
0.4%
Dash Punctuation 15
 
0.2%
Uppercase Letter 5
 
0.1%
Math Symbol 4
 
0.1%
Connector Punctuation 4
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
부 481
 
10.5%
평 427
 
9.3%
천 336
 
7.3%
동 306
 
6.7%
시 298
 
6.5%
인 297
 
6.5%
구 288
 
6.3%
광 286
 
6.2%
로 286
 
6.2%
역 283
 
6.2%
Other values (116) 1305
28.4%
Decimal Number
ValueCountFrequency (%)
1 225
21.7%
3 143
13.8%
2 137
13.2%
4 126
12.1%
0 83
 
8.0%
9 77
 
7.4%
5 70
 
6.7%
6 66
 
6.4%
8 60
 
5.8%
7 52
 
5.0%
Uppercase Letter
ValueCountFrequency (%)
A 2
40.0%
C 2
40.0%
B 1
20.0%
Other Punctuation
ValueCountFrequency (%)
, 28
96.6%
＆ 1
 
3.4%
Space Separator
ValueCountFrequency (%)
1219
100.0%
Open Punctuation
ValueCountFrequency (%)
( 284
100.0%
Close Punctuation
ValueCountFrequency (%)
) 284
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 15
100.0%
Math Symbol
ValueCountFrequency (%)
~ 4
100.0%
Connector Punctuation
ValueCountFrequency (%)
_ 4
100.0%
Letter Number
ValueCountFrequency (%)
Ⅱ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 4593
61.4%
Common 2878
38.5%
Latin 6
 
0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
부 481
 
10.5%
평 427
 
9.3%
천 336
 
7.3%
동 306
 
6.7%
시 298
 
6.5%
인 297
 
6.5%
구 288
 
6.3%
광 286
 
6.2%
로 286
 
6.2%
역 283
 
6.2%
Other values (116) 1305
28.4%
Common
ValueCountFrequency (%)
1219
42.4%
( 284
 
9.9%
) 284
 
9.9%
1 225
 
7.8%
3 143
 
5.0%
2 137
 
4.8%
4 126
 
4.4%
0 83
 
2.9%
9 77
 
2.7%
5 70
 
2.4%
Other values (8) 230
 
8.0%
Latin
ValueCountFrequency (%)
A 2
33.3%
C 2
33.3%
B 1
16.7%
Ⅱ 1
16.7%

Most occurring blocks

ValueCountFrequency (%)
Hangul 4593
61.4%
ASCII 2882
38.5%
None 1
 
< 0.1%
Number Forms 1
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1219
42.3%
( 284
 
9.9%
) 284
 
9.9%
1 225
 
7.8%
3 143
 
5.0%
2 137
 
4.8%
4 126
 
4.4%
0 83
 
2.9%
9 77
 
2.7%
5 70
 
2.4%
Other values (10) 234
 
8.1%
Hangul
ValueCountFrequency (%)
부 481
 
10.5%
평 427
 
9.3%
천 336
 
7.3%
동 306
 
6.7%
시 298
 
6.5%
인 297
 
6.5%
구 288
 
6.3%
광 286
 
6.2%
로 286
 
6.2%
역 283
 
6.2%
Other values (116) 1305
28.4%
None
ValueCountFrequency (%)
＆ 1
100.0%
Number Forms
ValueCountFrequency (%)
Ⅱ 1
100.0%

사업장전화번호
Text

MISSING 

Distinct238
Distinct (%)99.6%
Missing53
Missing (%)18.2%
Memory size2.4 KiB
2024-03-18T12:05:12.617282image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length13
Median length12
Mean length12.020921
Min length9

Characters and Unicode

Total characters2873
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

Unique237 ?
Unique (%)99.2%

Sample

1st row032-503-9603
2nd row032-526-0731
3rd row032-522-9691
4th row032-523-6053
5th row032-526-6432
ValueCountFrequency (%)
032-525-6692 2
 
0.8%
032-428-3820 1
 
0.4%
032-330-8752 1
 
0.4%
032-503-9603 1
 
0.4%
032-507-5800 1
 
0.4%
032-521-9876 1
 
0.4%
032-516-6007 1
 
0.4%
032-500-4003 1
 
0.4%
032-519-4155 1
 
0.4%
032-510-01485 1
 
0.4%
Other values (228) 228
95.4%
2024-03-18T12:05:12.995571image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
- 477
16.6%
0 455
15.8%
2 437
15.2%
3 401
14.0%
5 297
10.3%
1 180
 
6.3%
6 149
 
5.2%
8 135
 
4.7%
7 126
 
4.4%
4 109
 
3.8%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 2396
83.4%
Dash Punctuation 477
 
16.6%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 455
19.0%
2 437
18.2%
3 401
16.7%
5 297
12.4%
1 180
 
7.5%
6 149
 
6.2%
8 135
 
5.6%
7 126
 
5.3%
4 109
 
4.5%
9 107
 
4.5%
Dash Punctuation
ValueCountFrequency (%)
- 477
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 2873
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
- 477
16.6%
0 455
15.8%
2 437
15.2%
3 401
14.0%
5 297
10.3%
1 180
 
6.3%
6 149
 
5.2%
8 135
 
4.7%
7 126
 
4.4%
4 109
 
3.8%

Most occurring blocks

ValueCountFrequency (%)
ASCII 2873
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
- 477
16.6%
0 455
15.8%
2 437
15.2%
3 401
14.0%
5 297
10.3%
1 180
 
6.3%
6 149
 
5.2%
8 135
 
4.7%
7 126
 
4.4%
4 109
 
3.8%

면적
Real number (ℝ)

MISSING 

Distinct225
Distinct (%)79.2%
Missing8
Missing (%)2.7%
Infinite0
Infinite (%)0.0%
Mean454.85158
Minimum100
Maximum2250.6
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size2.7 KiB
2024-03-18T12:05:13.117538image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum100
5-th percentile150.75
Q1231.75
median335
Q3565.0625
95-th percentile1060
Maximum2250.6
Range2150.6
Interquartile range (IQR)333.3125

Descriptive statistics

Standard deviation329.70003
Coefficient of variation (CV)0.7248519
Kurtosis6.2062376
Mean454.85158
Median Absolute Deviation (MAD)121.05
Skewness2.1465408
Sum129177.85
Variance108702.11
MonotonicityNot monotonic
2024-03-18T12:05:13.233722image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
320.0 6
 
2.1%
200.0 6
 
2.1%
300.0 5
 
1.7%
100.0 5
 
1.7%
400.0 4
 
1.4%
120.0 4
 
1.4%
500.0 4
 
1.4%
330.0 3
 
1.0%
150.0 3
 
1.0%
190.0 3
 
1.0%
Other values (215) 241
82.5%
(Missing) 8
 
2.7%
ValueCountFrequency (%)
100.0 5
1.7%
108.0 1
 
0.3%
120.0 4
1.4%
140.0 2
 
0.7%
150.0 3
1.0%
155.0 1
 
0.3%
160.0 3
1.0%
170.0 1
 
0.3%
190.0 3
1.0%
200.0 6
2.1%
ValueCountFrequency (%)
2250.6 1
0.3%
2070.0 1
0.3%
1870.0 1
0.3%
1652.84 1
0.3%
1496.93 1
0.3%
1440.0 1
0.3%
1336.0 1
0.3%
1320.0 1
0.3%
1250.0 1
0.3%
1190.0 1
0.3%

년배출예상
Real number (ℝ)

MISSING 

Distinct276
Distinct (%)97.2%
Missing8
Missing (%)2.7%
Infinite0
Infinite (%)0.0%
Mean17587.37
Minimum200
Maximum65520
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size2.7 KiB
2024-03-18T12:05:13.362316image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum200
5-th percentile2371.25
Q17436.25
median14324.5
Q323826.5
95-th percentile45523.15
Maximum65520
Range65320
Interquartile range (IQR)16390.25

Descriptive statistics

Standard deviation13450.262
Coefficient of variation (CV)0.76476823
Kurtosis1.664211
Mean17587.37
Median Absolute Deviation (MAD)7827
Skewness1.2986833
Sum4994813
Variance1.8090954 × 108
MonotonicityNot monotonic
2024-03-18T12:05:13.470947image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
18577 2
 
0.7%
6270 2
 
0.7%
32550 2
 
0.7%
15930 2
 
0.7%
21413 2
 
0.7%
3400 2
 
0.7%
36000 2
 
0.7%
5330 2
 
0.7%
14900 1
 
0.3%
9510 1
 
0.3%
Other values (266) 266
91.1%
(Missing) 8
 
2.7%
ValueCountFrequency (%)
200 1
0.3%
330 1
0.3%
520 1
0.3%
800 1
0.3%
1000 1
0.3%
1110 1
0.3%
1270 1
0.3%
1437 1
0.3%
1680 1
0.3%
1800 1
0.3%
ValueCountFrequency (%)
65520 1
0.3%
63300 1
0.3%
63209 1
0.3%
60095 1
0.3%
59917 1
0.3%
58612 1
0.3%
57060 1
0.3%
55170 1
0.3%
53328 1
0.3%
52165 1
0.3%

신규등록(2022)
Boolean

CONSTANT  MISSING 

Distinct1
Distinct (%)0.4%
Missing8
Missing (%)2.7%
Memory size716.0 B
False
284 
(Missing)
 
8
ValueCountFrequency (%)
False 284
97.3%
(Missing) 8
 
2.7%
2024-03-18T12:05:13.554890image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Interactions

2024-03-18T12:05:10.413439image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-18T12:05:09.893936image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-18T12:05:10.201270image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-18T12:05:10.485943image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-18T12:05:10.023070image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-18T12:05:10.277369image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-18T12:05:10.558625image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-18T12:05:10.100011image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-18T12:05:10.343139image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-03-18T12:05:13.608949image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연번사업장구분면적년배출예상
연번1.0000.5690.2030.248
사업장구분0.5691.0000.0000.000
면적0.2030.0001.0000.759
년배출예상0.2480.0000.7591.000
2024-03-18T12:05:13.704607image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연번면적년배출예상사업장구분
연번1.000-0.231-0.1400.268
면적-0.2311.0000.4990.000
년배출예상-0.1400.4991.0000.000
사업장구분0.2680.0000.0001.000

Missing values

2024-03-18T12:05:10.679884image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-03-18T12:05:10.808876image/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.
2024-03-18T12:05:10.918274image/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

연번사업장구분상호소재지사업장전화번호면적년배출예상신규등록(2022)
01집단급식소인천일신초등학교인천광역시 부평구 항동로75번길 36 (일신동)032-503-9603471.09030N
12집단급식소부평공업고등학교인천광역시 부평구 주부토로 194 (갈산동)032-526-0731500.018015N
23일반음식점덕수갈비인천광역시 부평구 마장로 402 (청천동)032-522-9691456.116630N
34집단급식소부일여자중학교인천광역시 부평구 동수로 8 (부평동)032-523-6053307.012064N
45집단급식소부평여자고등학교인천광역시 부평구 부흥로243번길 44 (부평동)032-526-6432987.027138N
56집단급식소한길안과병원인천광역시 부평구 부평대로 35 (부평동)032-503-3322205.019860N
67집단급식소부평여자중학교인천광역시 부평구 부평문화로 193-1 (부개동)032-515-5813533.018577N
78일반음식점신선설농탕인천광역시 부평구 장제로 206 (부평동)032-514-3966407.6812050N
89집단급식소산곡초등학교인천광역시 부평구 길주로354번길 39 (산곡동)032-628-0510300.014258N
910집단급식소새봄여성병원인천광역시 부평구 마장로 316 (산곡동)032-521-7200120.034060N
연번사업장구분상호소재지사업장전화번호면적년배출예상신규등록(2022)
282283집단급식소이강한방병원인천광역시 부평구 굴포로 104 (삼산동)032-330-2011100.07365N
283284집단급식소연세백퍼센트병원인천광역시 부평구 경원대로 1109 (십정동)1533-1017300.05377N
284<NA><NA><NA><NA><NA><NA><NA><NA>
285<NA><NA><NA><NA><NA><NA><NA><NA>
286<NA><NA><NA><NA><NA><NA><NA><NA>
287<NA><NA><NA><NA><NA><NA><NA><NA>
288<NA><NA><NA><NA><NA><NA><NA><NA>
289<NA><NA><NA><NA><NA><NA><NA><NA>
290<NA><NA><NA><NA><NA><NA><NA><NA>
291<NA><NA><NA><NA><NA><NA><NA><NA>

Duplicate rows

Most frequently occurring

연번사업장구분상호소재지사업장전화번호면적년배출예상신규등록(2022)# duplicates
0<NA><NA><NA><NA><NA><NA><NA><NA>8