Overview

Dataset statistics

Number of variables15
Number of observations25
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory3.4 KiB
Average record size in memory138.3 B

Variable types

Text1
Categorical1
Numeric13

Dataset

Description년도별 국립박물관문화재단이 운영하는 편의시설(박물관상품관 및 식음료점) 월별 이용객 현황 (상호, 매장명, 1월, 2월, 3월, 4월, 5월, 6월, 7월, 8월, 9월, 10월, 11월, 12월 이용객 수 등)
URLhttps://www.data.go.kr/data/3069290/fileData.do

Alerts

1월 is highly overall correlated with 2월 and 11 other fieldsHigh correlation
2월 is highly overall correlated with 1월 and 11 other fieldsHigh correlation
3월 is highly overall correlated with 1월 and 11 other fieldsHigh correlation
4월 is highly overall correlated with 1월 and 11 other fieldsHigh correlation
5월 is highly overall correlated with 1월 and 11 other fieldsHigh correlation
6월 is highly overall correlated with 1월 and 11 other fieldsHigh correlation
7월 is highly overall correlated with 1월 and 11 other fieldsHigh correlation
8월 is highly overall correlated with 1월 and 11 other fieldsHigh correlation
9월 is highly overall correlated with 1월 and 11 other fieldsHigh correlation
10월 is highly overall correlated with 1월 and 12 other fieldsHigh correlation
11월 is highly overall correlated with 1월 and 11 other fieldsHigh correlation
12월 is highly overall correlated with 1월 and 11 other fieldsHigh correlation
is highly overall correlated with 1월 and 11 other fieldsHigh correlation
매장명 is highly overall correlated with 10월High correlation
has unique valuesUnique
1월 has 3 (12.0%) zerosZeros
2월 has 2 (8.0%) zerosZeros
3월 has 2 (8.0%) zerosZeros
4월 has 3 (12.0%) zerosZeros
5월 has 2 (8.0%) zerosZeros
6월 has 2 (8.0%) zerosZeros
7월 has 3 (12.0%) zerosZeros
8월 has 3 (12.0%) zerosZeros
9월 has 5 (20.0%) zerosZeros
10월 has 3 (12.0%) zerosZeros
11월 has 3 (12.0%) zerosZeros
12월 has 2 (8.0%) zerosZeros

Reproduction

Analysis started2023-12-11 23:17:06.261135
Analysis finished2023-12-11 23:17:24.850865
Duration18.59 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

상호
Text

Distinct20
Distinct (%)80.0%
Missing0
Missing (%)0.0%
Memory size332.0 B
2023-12-12T08:17:24.997875image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length17
Median length15
Mean length10.96
Min length4

Characters and Unicode

Total characters274
Distinct characters65
Distinct categories6 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique18 ?
Unique (%)72.0%

Sample

1st row국립박물관문화재단
2nd row국립박물관문화재단
3rd row국립박물관문화재단
4th row국립박물관문화재단
5th row국립박물관문화재단
ValueCountFrequency (%)
국립박물관문화재단 16
40.0%
경주지점 2
 
5.0%
식당 1
 
2.5%
경천사탑 1
 
2.5%
야미당 1
 
2.5%
외부식당 1
 
2.5%
극장'용'카페 1
 
2.5%
으뜸홀카페 1
 
2.5%
사유 1
 
2.5%
전통찻집 1
 
2.5%
Other values (14) 14
35.0%
2023-12-12T08:17:25.331156image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
22
 
8.0%
17
 
6.2%
17
 
6.2%
17
 
6.2%
16
 
5.8%
16
 
5.8%
16
 
5.8%
16
 
5.8%
16
 
5.8%
16
 
5.8%
Other values (55) 105
38.3%

Most occurring categories

ValueCountFrequency (%)
Other Letter 243
88.7%
Space Separator 22
 
8.0%
Uppercase Letter 3
 
1.1%
Open Punctuation 2
 
0.7%
Close Punctuation 2
 
0.7%
Other Punctuation 2
 
0.7%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
17
 
7.0%
17
 
7.0%
17
 
7.0%
16
 
6.6%
16
 
6.6%
16
 
6.6%
16
 
6.6%
16
 
6.6%
16
 
6.6%
11
 
4.5%
Other values (50) 85
35.0%
Space Separator
ValueCountFrequency (%)
22
100.0%
Uppercase Letter
ValueCountFrequency (%)
I 3
100.0%
Open Punctuation
ValueCountFrequency (%)
( 2
100.0%
Close Punctuation
ValueCountFrequency (%)
) 2
100.0%
Other Punctuation
ValueCountFrequency (%)
' 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 243
88.7%
Common 28
 
10.2%
Latin 3
 
1.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
17
 
7.0%
17
 
7.0%
17
 
7.0%
16
 
6.6%
16
 
6.6%
16
 
6.6%
16
 
6.6%
16
 
6.6%
16
 
6.6%
11
 
4.5%
Other values (50) 85
35.0%
Common
ValueCountFrequency (%)
22
78.6%
( 2
 
7.1%
) 2
 
7.1%
' 2
 
7.1%
Latin
ValueCountFrequency (%)
I 3
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 243
88.7%
ASCII 31
 
11.3%

Most frequent character per block

ASCII
ValueCountFrequency (%)
22
71.0%
I 3
 
9.7%
( 2
 
6.5%
) 2
 
6.5%
' 2
 
6.5%
Hangul
ValueCountFrequency (%)
17
 
7.0%
17
 
7.0%
17
 
7.0%
16
 
6.6%
16
 
6.6%
16
 
6.6%
16
 
6.6%
16
 
6.6%
16
 
6.6%
11
 
4.5%
Other values (50) 85
35.0%

매장명
Categorical

HIGH CORRELATION 

Distinct9
Distinct (%)36.0%
Missing0
Missing (%)0.0%
Memory size332.0 B
박물관상품관
식음료점
박물관상품관1
박물관상품관2
어린이박물관 박물관상품관
Other values (4)

Length

Max length13
Median length12
Mean length6.44
Min length4

Unique

Unique7 ?
Unique (%)28.0%

Sample

1st row박물관상품관1
2nd row박물관상품관2
3rd row어린이박물관 박물관상품관
4th row기획전시실 박물관상품관
5th row특별전시실 박물관상품관

Common Values

ValueCountFrequency (%)
박물관상품관 9
36.0%
식음료점 9
36.0%
박물관상품관1 1
 
4.0%
박물관상품관2 1
 
4.0%
어린이박물관 박물관상품관 1
 
4.0%
기획전시실 박물관상품관 1
 
4.0%
특별전시실 박물관상품관 1
 
4.0%
박물관상품관(내부) 1
 
4.0%
박물관상품관(외부) 1
 
4.0%

Length

2023-12-12T08:17:25.477488image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T08:17:25.623240image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
박물관상품관 12
42.9%
식음료점 9
32.1%
박물관상품관1 1
 
3.6%
박물관상품관2 1
 
3.6%
어린이박물관 1
 
3.6%
기획전시실 1
 
3.6%
특별전시실 1
 
3.6%
박물관상품관(내부 1
 
3.6%
박물관상품관(외부 1
 
3.6%

1월
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct23
Distinct (%)92.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2492.92
Minimum0
Maximum21876
Zeros3
Zeros (%)12.0%
Negative0
Negative (%)0.0%
Memory size357.0 B
2023-12-12T08:17:25.787907image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q1372
median1065
Q32428
95-th percentile7207.2
Maximum21876
Range21876
Interquartile range (IQR)2056

Descriptive statistics

Standard deviation4489.0858
Coefficient of variation (CV)1.800734
Kurtosis15.33674
Mean2492.92
Median Absolute Deviation (MAD)768
Skewness3.6727975
Sum62323
Variance20151891
MonotonicityNot monotonic
2023-12-12T08:17:25.929763image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=23)
ValueCountFrequency (%)
0 3
 
12.0%
7664 1
 
4.0%
4469 1
 
4.0%
1816 1
 
4.0%
720 1
 
4.0%
4955 1
 
4.0%
2615 1
 
4.0%
5380 1
 
4.0%
2428 1
 
4.0%
21876 1
 
4.0%
Other values (13) 13
52.0%
ValueCountFrequency (%)
0 3
12.0%
279 1
 
4.0%
297 1
 
4.0%
368 1
 
4.0%
372 1
 
4.0%
399 1
 
4.0%
564 1
 
4.0%
594 1
 
4.0%
630 1
 
4.0%
720 1
 
4.0%
ValueCountFrequency (%)
21876 1
4.0%
7664 1
4.0%
5380 1
4.0%
4955 1
4.0%
4469 1
4.0%
2615 1
4.0%
2428 1
4.0%
1944 1
4.0%
1816 1
4.0%
1516 1
4.0%

2월
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct24
Distinct (%)96.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2103.56
Minimum0
Maximum18016
Zeros2
Zeros (%)8.0%
Negative0
Negative (%)0.0%
Memory size357.0 B
2023-12-12T08:17:26.067993image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile22.8
Q1308
median960
Q32199
95-th percentile5633.8
Maximum18016
Range18016
Interquartile range (IQR)1891

Descriptive statistics

Standard deviation3674.4777
Coefficient of variation (CV)1.7467901
Kurtosis15.531014
Mean2103.56
Median Absolute Deviation (MAD)736
Skewness3.6817839
Sum52589
Variance13501786
MonotonicityNot monotonic
2023-12-12T08:17:26.203907image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=24)
ValueCountFrequency (%)
0 2
 
8.0%
5975 1
 
4.0%
960 1
 
4.0%
1292 1
 
4.0%
414 1
 
4.0%
4269 1
 
4.0%
2199 1
 
4.0%
4216 1
 
4.0%
2420 1
 
4.0%
18016 1
 
4.0%
Other values (14) 14
56.0%
ValueCountFrequency (%)
0 2
8.0%
114 1
4.0%
143 1
4.0%
273 1
4.0%
287 1
4.0%
308 1
4.0%
396 1
4.0%
414 1
4.0%
521 1
4.0%
529 1
4.0%
ValueCountFrequency (%)
18016 1
4.0%
5975 1
4.0%
4269 1
4.0%
4216 1
4.0%
3713 1
4.0%
2420 1
4.0%
2199 1
4.0%
2158 1
4.0%
1696 1
4.0%
1292 1
4.0%

3월
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct24
Distinct (%)96.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1473.32
Minimum0
Maximum11055
Zeros2
Zeros (%)8.0%
Negative0
Negative (%)0.0%
Memory size357.0 B
2023-12-12T08:17:26.337636image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0.4
Q1316
median652
Q31579
95-th percentile3987.6
Maximum11055
Range11055
Interquartile range (IQR)1263

Descriptive statistics

Standard deviation2321.5187
Coefficient of variation (CV)1.5757057
Kurtosis12.324958
Mean1473.32
Median Absolute Deviation (MAD)459
Skewness3.2232351
Sum36833
Variance5389449.1
MonotonicityNot monotonic
2023-12-12T08:17:26.459541image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=24)
ValueCountFrequency (%)
0 2
 
8.0%
4038 1
 
4.0%
652 1
 
4.0%
1208 1
 
4.0%
150 1
 
4.0%
2755 1
 
4.0%
1579 1
 
4.0%
3037 1
 
4.0%
3786 1
 
4.0%
11055 1
 
4.0%
Other values (14) 14
56.0%
ValueCountFrequency (%)
0 2
8.0%
2 1
4.0%
150 1
4.0%
193 1
4.0%
216 1
4.0%
316 1
4.0%
324 1
4.0%
375 1
4.0%
386 1
4.0%
463 1
4.0%
ValueCountFrequency (%)
11055 1
4.0%
4038 1
4.0%
3786 1
4.0%
3037 1
4.0%
2755 1
4.0%
2355 1
4.0%
1579 1
4.0%
1208 1
4.0%
929 1
4.0%
898 1
4.0%

4월
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct23
Distinct (%)92.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1934.72
Minimum0
Maximum11998
Zeros3
Zeros (%)12.0%
Negative0
Negative (%)0.0%
Memory size357.0 B
2023-12-12T08:17:26.613550image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q1313
median923
Q32526
95-th percentile6361
Maximum11998
Range11998
Interquartile range (IQR)2213

Descriptive statistics

Standard deviation2693.2721
Coefficient of variation (CV)1.3920733
Kurtosis7.7592876
Mean1934.72
Median Absolute Deviation (MAD)842
Skewness2.5722392
Sum48368
Variance7253714.5
MonotonicityNot monotonic
2023-12-12T08:17:26.756518image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=23)
ValueCountFrequency (%)
0 3
 
12.0%
4617 1
 
4.0%
394 1
 
4.0%
928 1
 
4.0%
3969 1
 
4.0%
81 1
 
4.0%
2526 1
 
4.0%
1414 1
 
4.0%
3454 1
 
4.0%
6797 1
 
4.0%
Other values (13) 13
52.0%
ValueCountFrequency (%)
0 3
12.0%
81 1
 
4.0%
242 1
 
4.0%
245 1
 
4.0%
313 1
 
4.0%
394 1
 
4.0%
455 1
 
4.0%
659 1
 
4.0%
832 1
 
4.0%
916 1
 
4.0%
ValueCountFrequency (%)
11998 1
4.0%
6797 1
4.0%
4617 1
4.0%
3969 1
4.0%
3454 1
4.0%
2697 1
4.0%
2526 1
4.0%
1951 1
4.0%
1937 1
4.0%
1414 1
4.0%

5월
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct24
Distinct (%)96.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean3722
Minimum0
Maximum23409
Zeros2
Zeros (%)8.0%
Negative0
Negative (%)0.0%
Memory size357.0 B
2023-12-12T08:17:26.898967image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile70.4
Q1678
median1651
Q35071
95-th percentile9758.8
Maximum23409
Range23409
Interquartile range (IQR)4393

Descriptive statistics

Standard deviation5001.5595
Coefficient of variation (CV)1.3437828
Kurtosis9.7448753
Mean3722
Median Absolute Deviation (MAD)1359
Skewness2.7898063
Sum93050
Variance25015597
MonotonicityNot monotonic
2023-12-12T08:17:27.031214image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=24)
ValueCountFrequency (%)
0 2
 
8.0%
8698 1
 
4.0%
1651 1
 
4.0%
5071 1
 
4.0%
3272 1
 
4.0%
501 1
 
4.0%
4859 1
 
4.0%
2565 1
 
4.0%
6726 1
 
4.0%
10024 1
 
4.0%
Other values (14) 14
56.0%
ValueCountFrequency (%)
0 2
8.0%
352 1
4.0%
405 1
4.0%
457 1
4.0%
501 1
4.0%
678 1
4.0%
687 1
4.0%
1115 1
4.0%
1120 1
4.0%
1159 1
4.0%
ValueCountFrequency (%)
23409 1
4.0%
10024 1
4.0%
8698 1
4.0%
7247 1
4.0%
6726 1
4.0%
5349 1
4.0%
5071 1
4.0%
4859 1
4.0%
3272 1
4.0%
3148 1
4.0%

6월
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct24
Distinct (%)96.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean3774.6
Minimum0
Maximum27013
Zeros2
Zeros (%)8.0%
Negative0
Negative (%)0.0%
Memory size357.0 B
2023-12-12T08:17:27.152244image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile75.2
Q1588
median1593
Q35776
95-th percentile8838.8
Maximum27013
Range27013
Interquartile range (IQR)5188

Descriptive statistics

Standard deviation5578.4907
Coefficient of variation (CV)1.4779025
Kurtosis12.848319
Mean3774.6
Median Absolute Deviation (MAD)1197
Skewness3.2447881
Sum94365
Variance31119558
MonotonicityNot monotonic
2023-12-12T08:17:27.283357image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=24)
ValueCountFrequency (%)
0 2
 
8.0%
9082 1
 
4.0%
1593 1
 
4.0%
7866 1
 
4.0%
2579 1
 
4.0%
796 1
 
4.0%
5440 1
 
4.0%
2790 1
 
4.0%
6684 1
 
4.0%
7067 1
 
4.0%
Other values (14) 14
56.0%
ValueCountFrequency (%)
0 2
8.0%
376 1
4.0%
454 1
4.0%
482 1
4.0%
506 1
4.0%
588 1
4.0%
796 1
4.0%
904 1
4.0%
948 1
4.0%
1203 1
4.0%
ValueCountFrequency (%)
27013 1
4.0%
9082 1
4.0%
7866 1
4.0%
7067 1
4.0%
6684 1
4.0%
5826 1
4.0%
5776 1
4.0%
5440 1
4.0%
3201 1
4.0%
2790 1
4.0%

7월
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct23
Distinct (%)92.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean4731
Minimum0
Maximum38935
Zeros3
Zeros (%)12.0%
Negative0
Negative (%)0.0%
Memory size357.0 B
2023-12-12T08:17:27.415366image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q1706
median1544
Q35915
95-th percentile11676.2
Maximum38935
Range38935
Interquartile range (IQR)5209

Descriptive statistics

Standard deviation7912.7534
Coefficient of variation (CV)1.6725329
Kurtosis15.378983
Mean4731
Median Absolute Deviation (MAD)1544
Skewness3.6303092
Sum118275
Variance62611666
MonotonicityNot monotonic
2023-12-12T08:17:27.595585image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=23)
ValueCountFrequency (%)
0 3
 
12.0%
12312 1
 
4.0%
763 1
 
4.0%
9133 1
 
4.0%
3745 1
 
4.0%
1154 1
 
4.0%
7689 1
 
4.0%
3778 1
 
4.0%
8303 1
 
4.0%
5915 1
 
4.0%
Other values (13) 13
52.0%
ValueCountFrequency (%)
0 3
12.0%
429 1
 
4.0%
501 1
 
4.0%
668 1
 
4.0%
706 1
 
4.0%
763 1
 
4.0%
809 1
 
4.0%
865 1
 
4.0%
1154 1
 
4.0%
1526 1
 
4.0%
ValueCountFrequency (%)
38935 1
4.0%
12312 1
4.0%
9133 1
4.0%
8303 1
4.0%
7689 1
4.0%
7434 1
4.0%
5915 1
4.0%
5685 1
4.0%
4333 1
4.0%
3778 1
4.0%

8월
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct23
Distinct (%)92.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean5518.8
Minimum0
Maximum46705
Zeros3
Zeros (%)12.0%
Negative0
Negative (%)0.0%
Memory size357.0 B
2023-12-12T08:17:27.742663image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q1886
median1910
Q37018
95-th percentile13751.2
Maximum46705
Range46705
Interquartile range (IQR)6132

Descriptive statistics

Standard deviation9437.612
Coefficient of variation (CV)1.7100841
Kurtosis16.096788
Mean5518.8
Median Absolute Deviation (MAD)1910
Skewness3.738818
Sum137970
Variance89068520
MonotonicityNot monotonic
2023-12-12T08:17:27.864574image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=23)
ValueCountFrequency (%)
0 3
 
12.0%
14561 1
 
4.0%
810 1
 
4.0%
10512 1
 
4.0%
4035 1
 
4.0%
1382 1
 
4.0%
8150 1
 
4.0%
4104 1
 
4.0%
8891 1
 
4.0%
7018 1
 
4.0%
Other values (13) 13
52.0%
ValueCountFrequency (%)
0 3
12.0%
477 1
 
4.0%
641 1
 
4.0%
810 1
 
4.0%
886 1
 
4.0%
955 1
 
4.0%
1075 1
 
4.0%
1153 1
 
4.0%
1382 1
 
4.0%
1672 1
 
4.0%
ValueCountFrequency (%)
46705 1
4.0%
14561 1
4.0%
10512 1
4.0%
8891 1
4.0%
8815 1
4.0%
8150 1
4.0%
7018 1
4.0%
6018 1
4.0%
5828 1
4.0%
4104 1
4.0%

9월
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct21
Distinct (%)84.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean3166.8
Minimum0
Maximum23607
Zeros5
Zeros (%)20.0%
Negative0
Negative (%)0.0%
Memory size357.0 B
2023-12-12T08:17:27.994586image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q1258
median928
Q34213
95-th percentile11209.8
Maximum23607
Range23607
Interquartile range (IQR)3955

Descriptive statistics

Standard deviation5218.0515
Coefficient of variation (CV)1.6477364
Kurtosis9.7547946
Mean3166.8
Median Absolute Deviation (MAD)928
Skewness2.8883046
Sum79170
Variance27228062
MonotonicityNot monotonic
2023-12-12T08:17:28.116721image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=21)
ValueCountFrequency (%)
0 5
20.0%
7785 1
 
4.0%
130 1
 
4.0%
12066 1
 
4.0%
2001 1
 
4.0%
258 1
 
4.0%
4213 1
 
4.0%
2328 1
 
4.0%
4781 1
 
4.0%
4867 1
 
4.0%
Other values (11) 11
44.0%
ValueCountFrequency (%)
0 5
20.0%
130 1
 
4.0%
258 1
 
4.0%
294 1
 
4.0%
361 1
 
4.0%
520 1
 
4.0%
522 1
 
4.0%
672 1
 
4.0%
928 1
 
4.0%
1030 1
 
4.0%
ValueCountFrequency (%)
23607 1
4.0%
12066 1
4.0%
7785 1
4.0%
6599 1
4.0%
4867 1
4.0%
4781 1
4.0%
4213 1
4.0%
3794 1
4.0%
2414 1
4.0%
2328 1
4.0%

10월
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct23
Distinct (%)92.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean4186.08
Minimum0
Maximum34838
Zeros3
Zeros (%)12.0%
Negative0
Negative (%)0.0%
Memory size357.0 B
2023-12-12T08:17:28.229278image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q1481
median2221
Q35833
95-th percentile10047
Maximum34838
Range34838
Interquartile range (IQR)5352

Descriptive statistics

Standard deviation7047.6855
Coefficient of variation (CV)1.6836003
Kurtosis15.830059
Mean4186.08
Median Absolute Deviation (MAD)1982
Skewness3.6927696
Sum104652
Variance49669871
MonotonicityNot monotonic
2023-12-12T08:17:28.355993image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=23)
ValueCountFrequency (%)
0 3
 
12.0%
10476 1
 
4.0%
239 1
 
4.0%
6333 1
 
4.0%
3108 1
 
4.0%
817 1
 
4.0%
5598 1
 
4.0%
2614 1
 
4.0%
5833 1
 
4.0%
6714 1
 
4.0%
Other values (13) 13
52.0%
ValueCountFrequency (%)
0 3
12.0%
10 1
 
4.0%
239 1
 
4.0%
348 1
 
4.0%
481 1
 
4.0%
817 1
 
4.0%
1142 1
 
4.0%
1168 1
 
4.0%
1210 1
 
4.0%
1374 1
 
4.0%
ValueCountFrequency (%)
34838 1
4.0%
10476 1
4.0%
8331 1
4.0%
6740 1
4.0%
6714 1
4.0%
6333 1
4.0%
5833 1
4.0%
5598 1
4.0%
3108 1
4.0%
2664 1
4.0%

11월
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct23
Distinct (%)92.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean4103.08
Minimum0
Maximum36491
Zeros3
Zeros (%)12.0%
Negative0
Negative (%)0.0%
Memory size357.0 B
2023-12-12T08:17:28.478487image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q1435
median1475
Q35605
95-th percentile9882
Maximum36491
Range36491
Interquartile range (IQR)5170

Descriptive statistics

Standard deviation7376.5101
Coefficient of variation (CV)1.7977983
Kurtosis16.556049
Mean4103.08
Median Absolute Deviation (MAD)1435
Skewness3.806834
Sum102577
Variance54412901
MonotonicityNot monotonic
2023-12-12T08:17:28.595203image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=23)
ValueCountFrequency (%)
0 3
 
12.0%
9274 1
 
4.0%
132 1
 
4.0%
10034 1
 
4.0%
2910 1
 
4.0%
801 1
 
4.0%
5605 1
 
4.0%
2891 1
 
4.0%
6663 1
 
4.0%
6816 1
 
4.0%
Other values (13) 13
52.0%
ValueCountFrequency (%)
0 3
12.0%
132 1
 
4.0%
324 1
 
4.0%
362 1
 
4.0%
435 1
 
4.0%
716 1
 
4.0%
766 1
 
4.0%
801 1
 
4.0%
1033 1
 
4.0%
1143 1
 
4.0%
ValueCountFrequency (%)
36491 1
4.0%
10034 1
4.0%
9274 1
4.0%
6816 1
4.0%
6663 1
4.0%
5822 1
4.0%
5605 1
4.0%
3688 1
4.0%
3516 1
4.0%
2910 1
4.0%

12월
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct24
Distinct (%)96.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean4112.64
Minimum0
Maximum38777
Zeros2
Zeros (%)8.0%
Negative0
Negative (%)0.0%
Memory size357.0 B
2023-12-12T08:17:28.729210image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile26.8
Q1480
median1718
Q33472
95-th percentile9701.2
Maximum38777
Range38777
Interquartile range (IQR)2992

Descriptive statistics

Standard deviation7764.5985
Coefficient of variation (CV)1.887984
Kurtosis17.90642
Mean4112.64
Median Absolute Deviation (MAD)1330
Skewness4.0093604
Sum102816
Variance60288990
MonotonicityNot monotonic
2023-12-12T08:17:28.889517image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=24)
ValueCountFrequency (%)
0 2
 
8.0%
10040 1
 
4.0%
480 1
 
4.0%
8346 1
 
4.0%
2647 1
 
4.0%
1777 1
 
4.0%
6540 1
 
4.0%
3472 1
 
4.0%
8333 1
 
4.0%
3313 1
 
4.0%
Other values (14) 14
56.0%
ValueCountFrequency (%)
0 2
8.0%
134 1
4.0%
388 1
4.0%
397 1
4.0%
448 1
4.0%
480 1
4.0%
573 1
4.0%
649 1
4.0%
1102 1
4.0%
1279 1
4.0%
ValueCountFrequency (%)
38777 1
4.0%
10040 1
4.0%
8346 1
4.0%
8333 1
4.0%
6540 1
4.0%
4624 1
4.0%
3472 1
4.0%
3313 1
4.0%
3281 1
4.0%
2837 1
4.0%


Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct25
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean41319.52
Minimum442
Maximum332720
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size357.0 B
2023-12-12T08:17:29.025076image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum442
5-th percentile4222.4
Q18343
median14370
Q362599
95-th percentile98077.8
Maximum332720
Range332278
Interquartile range (IQR)54256

Descriptive statistics

Standard deviation67030.551
Coefficient of variation (CV)1.622249
Kurtosis15.797642
Mean41319.52
Median Absolute Deviation (MAD)10263
Skewness3.6963631
Sum1032988
Variance4.4930947 × 109
MonotonicityNot monotonic
2023-12-12T08:17:29.173725image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=25)
ValueCountFrequency (%)
104522 1
 
4.0%
65984 1
 
4.0%
70289 1
 
4.0%
32582 1
 
4.0%
8851 1
 
4.0%
62599 1
 
4.0%
32349 1
 
4.0%
72301 1
 
4.0%
67165 1
 
4.0%
8343 1
 
4.0%
Other values (15) 15
60.0%
ValueCountFrequency (%)
442 1
4.0%
4107 1
4.0%
4684 1
4.0%
6055 1
4.0%
6619 1
4.0%
7174 1
4.0%
8343 1
4.0%
8851 1
4.0%
9315 1
4.0%
10708 1
4.0%
ValueCountFrequency (%)
332720 1
4.0%
104522 1
4.0%
72301 1
4.0%
70289 1
4.0%
67165 1
4.0%
65984 1
4.0%
62599 1
4.0%
40333 1
4.0%
32582 1
4.0%
32349 1
4.0%

Interactions

2023-12-12T08:17:22.660559image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:17:06.746918image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:17:07.935238image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:17:09.357050image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:17:10.540837image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:17:12.153707image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:17:13.445182image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:17:14.648720image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:17:15.947774image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:17:17.313205image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:17:18.851107image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:17:20.034607image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:17:21.286034image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:17:22.849553image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:17:06.836149image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:17:08.013448image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:17:09.451168image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:17:10.621070image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:17:12.230036image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:17:13.532586image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:17:14.735181image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:17:16.062319image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:17:17.392238image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:17:18.955032image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:17:20.114397image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:17:21.375475image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:17:22.992992image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:17:06.931132image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:17:08.101634image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:17:09.565810image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:17:10.712741image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:17:12.335269image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:17:13.627158image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:17:14.855848image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:17:16.157043image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:17:17.483068image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:17:19.054022image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:17:20.187270image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:17:21.492809image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:17:23.095720image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:17:07.027848image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:17:08.219389image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:17:09.651500image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:17:10.797623image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:17:12.414267image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:17:13.714511image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:17:14.956829image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:17:16.256123image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:17:17.577728image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:17:19.150365image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:17:20.258538image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:17:21.596699image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:17:23.206179image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:17:07.113071image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:17:08.309847image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:17:09.733462image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:17:10.879624image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:17:12.503983image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:17:13.796413image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:17:15.037322image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:17:16.360239image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:17:17.678699image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:17:19.263805image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:17:20.344607image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:17:21.700275image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:17:23.316497image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:17:07.198233image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:17:08.413734image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:17:09.839455image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:17:10.951695image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:17:12.599779image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:17:13.876401image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:17:15.115686image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:17:16.451141image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:17:17.769380image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:17:19.357149image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:17:20.424999image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:17:21.805362image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:17:23.412651image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:17:07.305964image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:17:08.530220image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:17:09.916423image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:17:11.049334image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:17:12.699363image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:17:13.962204image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:17:15.218695image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:17:16.573265image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:17:17.859924image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:17:19.457768image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:17:20.515172image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:17:21.908787image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:17:23.516026image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:17:07.408457image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:17:08.666919image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:17:10.010477image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:17:11.157386image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:17:12.817982image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:17:14.066350image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:17:15.333535image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:17:16.684608image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:17:17.967933image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:17:19.545999image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:17:20.633816image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:17:22.019506image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:17:23.617622image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:17:07.483572image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:17:08.765139image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:17:10.082296image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:17:11.256989image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:17:12.924348image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:17:14.164138image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:17:15.407482image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:17:16.792464image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:17:18.053458image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:17:19.618594image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:17:20.739484image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:17:22.101787image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:17:23.716272image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:17:07.560385image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:17:08.886999image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:17:10.161879image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:17:11.358265image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:17:13.007617image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:17:14.240570image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:17:15.511654image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:17:16.879147image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:17:18.145124image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:17:19.686944image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:17:20.884956image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:17:22.211297image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:17:23.810244image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:17:07.653763image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:17:09.006748image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:17:10.259624image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:17:11.471783image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:17:13.135750image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:17:14.339771image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:17:15.604474image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:17:17.002795image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:17:18.254226image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:17:19.769588image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:17:20.986134image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:17:22.308765image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:17:23.951513image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:17:07.743627image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:17:09.124922image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:17:10.354618image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:17:11.577690image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:17:13.239987image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:17:14.430887image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:17:15.732196image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:17:17.113034image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:17:18.337377image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:17:19.858791image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:17:21.082625image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:17:22.427319image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:17:24.090633image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:17:07.836696image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:17:09.247286image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:17:10.461135image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:17:11.999233image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:17:13.339999image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:17:14.550408image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:17:15.834828image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:17:17.223523image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:17:18.424911image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:17:19.951553image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:17:21.180088image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:17:22.528931image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-12T08:17:29.293779image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
상호매장명1월2월3월4월5월6월7월8월9월10월11월12월
상호1.0000.0000.0000.0000.8000.8550.7800.0000.0000.0000.0000.0000.6390.0000.000
매장명0.0001.0000.5870.6940.0000.4770.6870.7580.6720.6160.5430.8360.4000.2870.703
1월0.0000.5871.0000.9980.9870.9030.8650.9780.9630.9670.8520.9730.8320.8270.973
2월0.0000.6940.9981.0000.9800.9140.8670.9910.9720.9750.8570.9800.8250.8280.977
3월0.8000.0000.9870.9801.0000.9060.8770.9490.9270.9340.7810.9440.7910.7910.944
4월0.8550.4770.9030.9140.9061.0000.9880.8540.7540.7650.9200.7900.8800.8640.810
5월0.7800.6870.8650.8670.8770.9881.0000.8750.8290.8090.9260.8100.8780.8810.827
6월0.0000.7580.9780.9910.9490.8540.8751.0000.9860.9850.8650.9780.8180.7760.981
7월0.0000.6720.9630.9720.9270.7540.8290.9861.0000.9960.9040.9850.8300.8710.994
8월0.0000.6160.9670.9750.9340.7650.8090.9850.9961.0000.9530.9830.8820.8080.987
9월0.0000.5430.8520.8570.7810.9200.9260.8650.9040.9531.0000.8950.9810.8950.921
10월0.0000.8360.9730.9800.9440.7900.8100.9780.9850.9830.8951.0000.8260.8380.992
11월0.6390.4000.8320.8250.7910.8800.8780.8180.8300.8820.9810.8261.0000.9790.832
12월0.0000.2870.8270.8280.7910.8640.8810.7760.8710.8080.8950.8380.9791.0000.875
0.0000.7030.9730.9770.9440.8100.8270.9810.9940.9870.9210.9920.8320.8751.000
2023-12-12T08:17:29.447320image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
1월2월3월4월5월6월7월8월9월10월11월12월매장명
1월1.0000.9840.9420.8270.7650.7570.7130.7180.6220.5970.5390.6410.7880.328
2월0.9841.0000.9630.8530.7970.7710.7030.7080.6140.5840.5030.5910.7870.428
3월0.9420.9631.0000.8670.7960.7570.6590.6730.6090.5840.5070.5650.7700.000
4월0.8270.8530.8671.0000.8830.8620.7500.7640.7940.7370.6190.6590.8710.203
5월0.7650.7970.7960.8831.0000.9750.8610.8700.6810.6110.6100.6350.9200.372
6월0.7570.7710.7570.8620.9751.0000.9150.9250.7550.6710.6790.7150.9560.499
7월0.7130.7030.6590.7500.8610.9151.0000.9920.8320.7470.7660.7430.9050.406
8월0.7180.7080.6730.7640.8700.9250.9921.0000.8450.7730.7820.7570.9210.354
9월0.6220.6140.6090.7940.6810.7550.8320.8451.0000.9190.8250.7750.8180.251
10월0.5970.5840.5840.7370.6110.6710.7470.7730.9191.0000.9140.8530.8050.601
11월0.5390.5030.5070.6190.6100.6790.7660.7820.8250.9141.0000.9460.8210.200
12월0.6410.5910.5650.6590.6350.7150.7430.7570.7750.8530.9461.0000.8460.109
0.7880.7870.7700.8710.9200.9560.9050.9210.8180.8050.8210.8461.0000.453
매장명0.3280.4280.0000.2030.3720.4990.4060.3540.2510.6010.2000.1090.4531.000

Missing values

2023-12-12T08:17:24.559891image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-12T08:17:24.769818image/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

상호매장명1월2월3월4월5월6월7월8월9월10월11월12월
0국립박물관문화재단박물관상품관17664597540384617869890821231214561778510476927410040104522
1국립박물관문화재단박물관상품관244693713235526975349577674348815659983315822462465984
2국립박물관문화재단어린이박물관 박물관상품관11339938988321115128315441910103012101143127914370
3국립박물관문화재단기획전시실 박물관상품관106511637309167247582656855828000028460
4국립박물관문화재단특별전시실 박물관상품관630521463015471203152616720101475166110708
5국립박물관문화재단 경주지점박물관상품관(내부)1516169692919513148190800000110212250
6국립박물관문화재단 경주지점박물관상품관(외부)1944215884519373010320143336018379467403516283740333
7국립박물관문화재단 광주지점박물관상품관279273324242405376429477294239310336497174
8국립박물관문화재단 대구지점박물관상품관3992873752453524545016413613483243974684
9국립박물관문화재단 김해지점박물관상품관2971432000000000442
상호매장명1월2월3월4월5월6월7월8월9월10월11월12월
15국립박물관문화재단 전주지점박물관상품관01142163136875886688861302391321344107
16푸드코트식음료점218761801611055119982340927013389354670523607348383649138777332720
17거울못식당식음료점0000000001374368832818343
18투썸카페I(외부)식음료점242824203786679710024706759157018486767146816331367165
19투썸카페II(내부)식음료점53804216303734546726668483038891478158336663833372301
20전통찻집 사유식음료점26152199157914142565279037784104232826142891347232349
21으뜸홀카페식음료점49554269275525264859544076898150421355985605654062599
22극장'용'카페식음료점720414150815017961154138225881780117778851
23외부식당 야미당식음료점18161292120839693272257937454035200131082910264732582
24경천사탑 식당 두레식음료점0009285071786691331051212066633310034834670289