Overview

Dataset statistics

Number of variables12
Number of observations27
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory2.9 KiB
Average record size in memory108.9 B

Variable types

Categorical5
Text1
Numeric6

Dataset

Description인천광역시 서구 중학교 무상급식 지원현황에 대한 데이터로 학교명, 급식일수, 급식단가, 재학생수, 지원금액(원) ​등을 제공합니다
Author인천광역시 서구
URLhttps://www.data.go.kr/data/15090932/fileData.do

Alerts

교육지원청 has constant value ""Constant
군구 has constant value ""Constant
식품비(친환경) has constant value ""Constant
데이터기준일자 has constant value ""Constant
급식일수 is highly overall correlated with 추가식품비High correlation
급식단가 is highly overall correlated with 식품비(무상) and 4 other fieldsHigh correlation
식품비(무상) is highly overall correlated with 급식단가 and 4 other fieldsHigh correlation
운영비 is highly overall correlated with 급식단가 and 4 other fieldsHigh correlation
재학생수 is highly overall correlated with 급식단가 and 4 other fieldsHigh correlation
지원금액(천원) is highly overall correlated with 급식단가 and 4 other fieldsHigh correlation
추가식품비 is highly overall correlated with 급식일수 and 5 other fieldsHigh correlation
추가식품비 is highly imbalanced (77.1%)Imbalance
학교명 has unique valuesUnique
재학생수 has unique valuesUnique
지원금액(천원) has unique valuesUnique

Reproduction

Analysis started2023-12-12 14:19:16.358469
Analysis finished2023-12-12 14:19:20.703598
Duration4.35 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

교육지원청
Categorical

CONSTANT 

Distinct1
Distinct (%)3.7%
Missing0
Missing (%)0.0%
Memory size348.0 B
서부
27 

Length

Max length2
Median length2
Mean length2
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
서부 27
100.0%

Length

2023-12-12T23:19:20.766729image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T23:19:20.851101image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
서부 27
100.0%

군구
Categorical

CONSTANT 

Distinct1
Distinct (%)3.7%
Missing0
Missing (%)0.0%
Memory size348.0 B
서구
27 

Length

Max length2
Median length2
Mean length2
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
서구 27
100.0%

Length

2023-12-12T23:19:20.940671image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T23:19:21.028055image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
서구 27
100.0%

학교명
Text

UNIQUE 

Distinct27
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size348.0 B
2023-12-12T23:19:21.244671image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length9
Median length8
Mean length6.1481481
Min length5

Characters and Unicode

Total characters166
Distinct characters47
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique27 ?
Unique (%)100.0%

Sample

1st row제물포중학교
2nd row가좌중학교
3rd row동인천여자중학교
4th row인천가좌여자중학교
5th row가정여자중학교
ValueCountFrequency (%)
제물포중학교 1
 
3.7%
원당중학교 1
 
3.7%
인천이음중학교 1
 
3.7%
인천아라중학교 1
 
3.7%
청호중학교 1
 
3.7%
인천경연중학교 1
 
3.7%
인천청람중학교 1
 
3.7%
인천해원중학교 1
 
3.7%
인천초은중학교 1
 
3.7%
인천청라중학교 1
 
3.7%
Other values (17) 17
63.0%
2023-12-12T23:19:21.617296image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
중 27
16.3%
학 27
16.3%
교 27
16.3%
인 11
 
6.6%
천 11
 
6.6%
가 4
 
2.4%
여 4
 
2.4%
자 4
 
2.4%
현 3
 
1.8%
원 3
 
1.8%
Other values (37) 45
27.1%

Most occurring categories

ValueCountFrequency (%)
Other Letter 166
100.0%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
중 27
16.3%
학 27
16.3%
교 27
16.3%
인 11
 
6.6%
천 11
 
6.6%
가 4
 
2.4%
여 4
 
2.4%
자 4
 
2.4%
현 3
 
1.8%
원 3
 
1.8%
Other values (37) 45
27.1%

Most occurring scripts

ValueCountFrequency (%)
Hangul 166
100.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
중 27
16.3%
학 27
16.3%
교 27
16.3%
인 11
 
6.6%
천 11
 
6.6%
가 4
 
2.4%
여 4
 
2.4%
자 4
 
2.4%
현 3
 
1.8%
원 3
 
1.8%
Other values (37) 45
27.1%

Most occurring blocks

ValueCountFrequency (%)
Hangul 166
100.0%

Most frequent character per block

Hangul
ValueCountFrequency (%)
중 27
16.3%
학 27
16.3%
교 27
16.3%
인 11
 
6.6%
천 11
 
6.6%
가 4
 
2.4%
여 4
 
2.4%
자 4
 
2.4%
현 3
 
1.8%
원 3
 
1.8%
Other values (37) 45
27.1%

급식일수
Real number (ℝ)

HIGH CORRELATION 

Distinct11
Distinct (%)40.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean183.7037
Minimum156
Maximum189
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size375.0 B
2023-12-12T23:19:21.753056image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum156
5-th percentile176.1
Q1183
median185
Q3186
95-th percentile188.7
Maximum189
Range33
Interquartile range (IQR)3

Descriptive statistics

Standard deviation6.2500142
Coefficient of variation (CV)0.034022255
Kurtosis15.686396
Mean183.7037
Median Absolute Deviation (MAD)1
Skewness-3.684988
Sum4960
Variance39.062678
MonotonicityNot monotonic
2023-12-12T23:19:21.877605image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=11)
ValueCountFrequency (%)
186 7
25.9%
185 5
18.5%
183 4
14.8%
187 2
 
7.4%
189 2
 
7.4%
184 2
 
7.4%
182 1
 
3.7%
181 1
 
3.7%
156 1
 
3.7%
174 1
 
3.7%
ValueCountFrequency (%)
156 1
 
3.7%
174 1
 
3.7%
181 1
 
3.7%
182 1
 
3.7%
183 4
14.8%
184 2
 
7.4%
185 5
18.5%
186 7
25.9%
187 2
 
7.4%
188 1
 
3.7%
ValueCountFrequency (%)
189 2
 
7.4%
188 1
 
3.7%
187 2
 
7.4%
186 7
25.9%
185 5
18.5%
184 2
 
7.4%
183 4
14.8%
182 1
 
3.7%
181 1
 
3.7%
174 1
 
3.7%

급식단가
Real number (ℝ)

HIGH CORRELATION 

Distinct10
Distinct (%)37.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean3712.5926
Minimum3420
Maximum4270
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size375.0 B
2023-12-12T23:19:22.014729image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum3420
5-th percentile3441
Q13500
median3630
Q33930
95-th percentile3972
Maximum4270
Range850
Interquartile range (IQR)430

Descriptive statistics

Standard deviation229.07158
Coefficient of variation (CV)0.061701244
Kurtosis-0.70720782
Mean3712.5926
Median Absolute Deviation (MAD)140
Skewness0.5158787
Sum100240
Variance52473.789
MonotonicityNot monotonic
2023-12-12T23:19:22.113042image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=10)
ValueCountFrequency (%)
3930 7
25.9%
3490 5
18.5%
3590 4
14.8%
3900 2
 
7.4%
3630 2
 
7.4%
3420 2
 
7.4%
3510 2
 
7.4%
4270 1
 
3.7%
3990 1
 
3.7%
3740 1
 
3.7%
ValueCountFrequency (%)
3420 2
 
7.4%
3490 5
18.5%
3510 2
 
7.4%
3590 4
14.8%
3630 2
 
7.4%
3740 1
 
3.7%
3900 2
 
7.4%
3930 7
25.9%
3990 1
 
3.7%
4270 1
 
3.7%
ValueCountFrequency (%)
4270 1
 
3.7%
3990 1
 
3.7%
3930 7
25.9%
3900 2
 
7.4%
3740 1
 
3.7%
3630 2
 
7.4%
3590 4
14.8%
3510 2
 
7.4%
3490 5
18.5%
3420 2
 
7.4%

식품비(무상)
Real number (ℝ)

HIGH CORRELATION 

Distinct10
Distinct (%)37.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean3018.1481
Minimum2796
Maximum3470
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size375.0 B
2023-12-12T23:19:22.225893image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum2796
5-th percentile2809.2
Q12847
median2966
Q33180
95-th percentile3221.3
Maximum3470
Range674
Interquartile range (IQR)333

Descriptive statistics

Standard deviation177.57787
Coefficient of variation (CV)0.058836698
Kurtosis-0.39912271
Mean3018.1481
Median Absolute Deviation (MAD)126
Skewness0.56561203
Sum81490
Variance31533.9
MonotonicityNot monotonic
2023-12-12T23:19:22.323457image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=10)
ValueCountFrequency (%)
3180 7
25.9%
2840 5
18.5%
2934 4
14.8%
3156 2
 
7.4%
2966 2
 
7.4%
2796 2
 
7.4%
2854 2
 
7.4%
3470 1
 
3.7%
3239 1
 
3.7%
3041 1
 
3.7%
ValueCountFrequency (%)
2796 2
 
7.4%
2840 5
18.5%
2854 2
 
7.4%
2934 4
14.8%
2966 2
 
7.4%
3041 1
 
3.7%
3156 2
 
7.4%
3180 7
25.9%
3239 1
 
3.7%
3470 1
 
3.7%
ValueCountFrequency (%)
3470 1
 
3.7%
3239 1
 
3.7%
3180 7
25.9%
3156 2
 
7.4%
3041 1
 
3.7%
2966 2
 
7.4%
2934 4
14.8%
2854 2
 
7.4%
2840 5
18.5%
2796 2
 
7.4%

식품비(친환경)
Categorical

CONSTANT 

Distinct1
Distinct (%)3.7%
Missing0
Missing (%)0.0%
Memory size348.0 B
310
27 

Length

Max length3
Median length3
Mean length3
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row310
2nd row310
3rd row310
4th row310
5th row310

Common Values

ValueCountFrequency (%)
310 27
100.0%

Length

2023-12-12T23:19:22.448066image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T23:19:22.536899image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
310 27
100.0%

추가식품비
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct2
Distinct (%)7.4%
Missing0
Missing (%)0.0%
Memory size348.0 B
120
26 
<NA>
 
1

Length

Max length4
Median length3
Mean length3.037037
Min length3

Unique

Unique1 ?
Unique (%)3.7%

Sample

1st row120
2nd row120
3rd row120
4th row120
5th row120

Common Values

ValueCountFrequency (%)
120 26
96.3%
<NA> 1
 
3.7%

Length

2023-12-12T23:19:22.634434image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T23:19:22.714823image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
120 26
96.3%
na 1
 
3.7%

운영비
Real number (ℝ)

HIGH CORRELATION 

Distinct9
Distinct (%)33.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean384.44444
Minimum314
Maximum490
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size375.0 B
2023-12-12T23:19:22.796430image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum314
5-th percentile321.8
Q1343
median354
Q3440
95-th percentile440.7
Maximum490
Range176
Interquartile range (IQR)97

Descriptive statistics

Standard deviation52.404003
Coefficient of variation (CV)0.13631099
Kurtosis-1.4733921
Mean384.44444
Median Absolute Deviation (MAD)35
Skewness0.36521395
Sum10380
Variance2746.1795
MonotonicityNot monotonic
2023-12-12T23:19:22.895296image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=9)
ValueCountFrequency (%)
440 7
25.9%
346 6
22.2%
340 5
18.5%
434 2
 
7.4%
354 2
 
7.4%
314 2
 
7.4%
490 1
 
3.7%
441 1
 
3.7%
389 1
 
3.7%
ValueCountFrequency (%)
314 2
 
7.4%
340 5
18.5%
346 6
22.2%
354 2
 
7.4%
389 1
 
3.7%
434 2
 
7.4%
440 7
25.9%
441 1
 
3.7%
490 1
 
3.7%
ValueCountFrequency (%)
490 1
 
3.7%
441 1
 
3.7%
440 7
25.9%
434 2
 
7.4%
389 1
 
3.7%
354 2
 
7.4%
346 6
22.2%
340 5
18.5%
314 2
 
7.4%

재학생수
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct27
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean653.22222
Minimum192
Maximum1381
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size375.0 B
2023-12-12T23:19:23.006680image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum192
5-th percentile281.1
Q1342
median565
Q3940.5
95-th percentile1062.9
Maximum1381
Range1189
Interquartile range (IQR)598.5

Descriptive statistics

Standard deviation332.79381
Coefficient of variation (CV)0.50946492
Kurtosis-1.1570919
Mean653.22222
Median Absolute Deviation (MAD)244
Skewness0.36053755
Sum17637
Variance110751.72
MonotonicityNot monotonic
2023-12-12T23:19:23.136870image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=27)
ValueCountFrequency (%)
414 1
 
3.7%
393 1
 
3.7%
435 1
 
3.7%
958 1
 
3.7%
850 1
 
3.7%
470 1
 
3.7%
358 1
 
3.7%
1003 1
 
3.7%
1008 1
 
3.7%
923 1
 
3.7%
Other values (17) 17
63.0%
ValueCountFrequency (%)
192 1
3.7%
264 1
3.7%
321 1
3.7%
324 1
3.7%
330 1
3.7%
333 1
3.7%
334 1
3.7%
350 1
3.7%
358 1
3.7%
393 1
3.7%
ValueCountFrequency (%)
1381 1
3.7%
1065 1
3.7%
1058 1
3.7%
1043 1
3.7%
1008 1
3.7%
1003 1
3.7%
958 1
3.7%
923 1
3.7%
897 1
3.7%
861 1
3.7%

지원금액(천원)
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct27
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean101017.89
Minimum36033
Maximum197366
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size375.0 B
2023-12-12T23:19:23.265571image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum36033
5-th percentile47495.2
Q157434
median91979
Q3141678.5
95-th percentile161250.2
Maximum197366
Range161333
Interquartile range (IQR)84244.5

Descriptive statistics

Standard deviation46823.059
Coefficient of variation (CV)0.46351254
Kurtosis-1.3372947
Mean101017.89
Median Absolute Deviation (MAD)41230
Skewness0.26735817
Sum2727483
Variance2.1923988 × 109
MonotonicityNot monotonic
2023-12-12T23:19:23.387573image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=27)
ValueCountFrequency (%)
70842 1
 
3.7%
67192 1
 
3.7%
68063 1
 
3.7%
142606 1
 
3.7%
127598 1
 
3.7%
73465 1
 
3.7%
57363 1
 
3.7%
150069 1
 
3.7%
152617 1
 
3.7%
137327 1
 
3.7%
Other values (17) 17
63.0%
ValueCountFrequency (%)
36033 1
3.7%
47437 1
3.7%
47631 1
3.7%
48153 1
3.7%
54320 1
3.7%
56979 1
3.7%
57363 1
3.7%
57505 1
3.7%
61195 1
3.7%
67192 1
3.7%
ValueCountFrequency (%)
197366 1
3.7%
161804 1
3.7%
159958 1
3.7%
152617 1
3.7%
150069 1
3.7%
146947 1
3.7%
142606 1
3.7%
140751 1
3.7%
137327 1
3.7%
133209 1
3.7%

데이터기준일자
Categorical

CONSTANT 

Distinct1
Distinct (%)3.7%
Missing0
Missing (%)0.0%
Memory size348.0 B
2023-10-25
27 

Length

Max length10
Median length10
Mean length10
Min length10

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2023-10-25
2nd row2023-10-25
3rd row2023-10-25
4th row2023-10-25
5th row2023-10-25

Common Values

ValueCountFrequency (%)
2023-10-25 27
100.0%

Length

2023-12-12T23:19:23.536556image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T23:19:23.648787image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2023-10-25 27
100.0%

Interactions

2023-12-12T23:19:19.854615image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T23:19:16.693598image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T23:19:17.704905image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T23:19:18.296054image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T23:19:18.862047image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T23:19:19.352814image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T23:19:19.965423image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T23:19:16.802395image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T23:19:17.810421image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T23:19:18.388731image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T23:19:18.948524image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T23:19:19.434450image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T23:19:20.043649image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T23:19:16.905957image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T23:19:17.895114image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T23:19:18.465776image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T23:19:19.018311image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T23:19:19.503301image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T23:19:20.148058image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T23:19:17.026104image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T23:19:17.997772image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T23:19:18.556571image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T23:19:19.096070image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T23:19:19.587804image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T23:19:20.250753image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T23:19:17.152385image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T23:19:18.103226image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T23:19:18.667024image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T23:19:19.174990image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T23:19:19.669419image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T23:19:20.352098image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T23:19:17.268406image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T23:19:18.185307image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T23:19:18.755545image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T23:19:19.258593image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T23:19:19.758597image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-12T23:19:23.713252image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
학교명급식일수급식단가식품비(무상)운영비재학생수지원금액(천원)
학교명1.0001.0001.0001.0001.0001.0001.000
급식일수1.0001.0000.0000.0000.0000.0000.000
급식단가1.0000.0001.0000.9680.9330.9350.891
식품비(무상)1.0000.0000.9681.0000.9720.9750.856
운영비1.0000.0000.9330.9721.0000.8510.874
재학생수1.0000.0000.9350.9750.8511.0000.961
지원금액(천원)1.0000.0000.8910.8560.8740.9611.000
2023-12-12T23:19:24.123463image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
급식일수급식단가식품비(무상)운영비재학생수지원금액(천원)추가식품비
급식일수1.000-0.295-0.295-0.3040.2050.2551.000
급식단가-0.2951.0001.0000.996-0.878-0.8481.000
식품비(무상)-0.2951.0001.0000.996-0.878-0.8481.000
운영비-0.3040.9960.9961.000-0.872-0.8441.000
재학생수0.205-0.878-0.878-0.8721.0000.9881.000
지원금액(천원)0.255-0.848-0.848-0.8440.9881.0001.000
추가식품비1.0001.0001.0001.0001.0001.0001.000

Missing values

2023-12-12T23:19:20.490013image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-12T23:19:20.636236image/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.

Sample

교육지원청군구학교명급식일수급식단가식품비(무상)식품비(친환경)추가식품비운영비재학생수지원금액(천원)데이터기준일자
0서부서구제물포중학교18739003156310120434414708422023-10-25
1서부서구가좌중학교18339303180310120440393671922023-10-25
2서부서구동인천여자중학교18639303180310120440330611952023-10-25
3서부서구인천가좌여자중학교18239303180310120440350575052023-10-25
4서부서구가정여자중학교18542703470310120490192360332023-10-25
5서부서구신현중학교18339903239310120441264476312023-10-25
6서부서구신현여자중학교18339303180310120440324543202023-10-25
7서부서구검단중학교189359029343101203468971407512023-10-25
8서부서구서곶중학교18637403041310120389565919792023-10-25
9서부서구백석중학교18139303180310120440321474372023-10-25
교육지원청군구학교명급식일수급식단가식품비(무상)식품비(친환경)추가식품비운영비재학생수지원금액(천원)데이터기준일자
17서부서구석남중학교18639303180310120440334569792023-10-25
18서부서구인천청라중학교1853490284031012034010581599582023-10-25
19서부서구인천초은중학교184351028543101203469231373272023-10-25
20서부서구인천해원중학교1863490284031012034010081526172023-10-25
21서부서구인천청람중학교1863490284031012034010031500692023-10-25
22서부서구인천경연중학교18834202796310120314358573632023-10-25
23서부서구청호중학교18535902934310120346470734652023-10-25
24서부서구인천아라중학교186359029343101203468501275982023-10-25
25서부서구인천이음중학교187351028543101203469581426062023-10-25
26서부서구인천루원중학교18439003156310120434435680632023-10-25