Overview

Dataset statistics

Number of variables15
Number of observations28
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory3.7 KiB
Average record size in memory136.6 B

Variable types

Text1
Categorical1
Numeric12
DateTime1

Dataset

Description전북특별자치도 정읍시 소재 주요 관광지점 입장객 현황 자료중(관광지 명칭, 방문자 국적, 1월 ~12월 입장객수)의 정보를 제공합니다.
Author전북특별자치도 정읍시
URLhttps://www.data.go.kr/data/3079973/fileData.do

Alerts

데이터기준일자 has constant value ""Constant
01월 is highly overall correlated with 02월 and 10 other fieldsHigh correlation
02월 is highly overall correlated with 01월 and 10 other fieldsHigh correlation
03월 is highly overall correlated with 01월 and 10 other fieldsHigh correlation
04월 is highly overall correlated with 01월 and 10 other fieldsHigh correlation
05월 is highly overall correlated with 01월 and 10 other fieldsHigh correlation
06월 is highly overall correlated with 01월 and 10 other fieldsHigh correlation
07월 is highly overall correlated with 01월 and 10 other fieldsHigh correlation
08월 is highly overall correlated with 01월 and 10 other fieldsHigh correlation
9월 is highly overall correlated with 01월 and 10 other fieldsHigh correlation
10월 is highly overall correlated with 01월 and 10 other fieldsHigh correlation
11월 is highly overall correlated with 01월 and 10 other fieldsHigh correlation
12월 is highly overall correlated with 01월 and 10 other fieldsHigh correlation
01월 has 8 (28.6%) zerosZeros
02월 has 7 (25.0%) zerosZeros
03월 has 8 (28.6%) zerosZeros
04월 has 7 (25.0%) zerosZeros
05월 has 7 (25.0%) zerosZeros
06월 has 7 (25.0%) zerosZeros
07월 has 7 (25.0%) zerosZeros
08월 has 7 (25.0%) zerosZeros
9월 has 7 (25.0%) zerosZeros
10월 has 7 (25.0%) zerosZeros
11월 has 7 (25.0%) zerosZeros
12월 has 8 (28.6%) zerosZeros

Reproduction

Analysis started2024-03-14 19:54:59.184531
Analysis finished2024-03-14 19:55:39.427187
Duration40.24 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

관광지 명칭
Text

Distinct20
Distinct (%)71.4%
Missing0
Missing (%)0.0%
Memory size352.0 B
2024-03-15T04:55:40.279367image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length15
Median length11
Mean length8.4285714
Min length3

Characters and Unicode

Total characters236
Distinct characters92
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique12 ?
Unique (%)42.9%

Sample

1st row내장산 골프앤리조트
2nd row송참봉조선동네
3rd row정읍시 내장산 국민여가캠핑장
4th row천사히어로즈
5th row국립전북기상과학관
ValueCountFrequency (%)
정읍 4
 
9.3%
어울림센터 2
 
4.7%
시립미술관 2
 
4.7%
국립전북기상과학관 2
 
4.7%
첨단과학관 2
 
4.7%
무성서원 2
 
4.7%
내장산국립공원(정읍시 2
 
4.7%
내장산 2
 
4.7%
황토현권역 2
 
4.7%
센터 2
 
4.7%
Other values (18) 21
48.8%
2024-03-15T04:55:41.640710image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
15
 
6.4%
관 12
 
5.1%
정 11
 
4.7%
읍 8
 
3.4%
시 7
 
3.0%
립 7
 
3.0%
원 6
 
2.5%
기 6
 
2.5%
산 6
 
2.5%
마 5
 
2.1%
Other values (82) 153
64.8%

Most occurring categories

ValueCountFrequency (%)
Other Letter 215
91.1%
Space Separator 15
 
6.4%
Close Punctuation 3
 
1.3%
Open Punctuation 3
 
1.3%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
관 12
 
5.6%
정 11
 
5.1%
읍 8
 
3.7%
시 7
 
3.3%
립 7
 
3.3%
원 6
 
2.8%
기 6
 
2.8%
산 6
 
2.8%
마 5
 
2.3%
국 5
 
2.3%
Other values (79) 142
66.0%
Space Separator
ValueCountFrequency (%)
15
100.0%
Close Punctuation
ValueCountFrequency (%)
) 3
100.0%
Open Punctuation
ValueCountFrequency (%)
( 3
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 215
91.1%
Common 21
 
8.9%

Most frequent character per script

Hangul
ValueCountFrequency (%)
관 12
 
5.6%
정 11
 
5.1%
읍 8
 
3.7%
시 7
 
3.3%
립 7
 
3.3%
원 6
 
2.8%
기 6
 
2.8%
산 6
 
2.8%
마 5
 
2.3%
국 5
 
2.3%
Other values (79) 142
66.0%
Common
ValueCountFrequency (%)
15
71.4%
) 3
 
14.3%
( 3
 
14.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 215
91.1%
ASCII 21
 
8.9%

Most frequent character per block

ASCII
ValueCountFrequency (%)
15
71.4%
) 3
 
14.3%
( 3
 
14.3%
Hangul
ValueCountFrequency (%)
관 12
 
5.6%
정 11
 
5.1%
읍 8
 
3.7%
시 7
 
3.3%
립 7
 
3.3%
원 6
 
2.8%
기 6
 
2.8%
산 6
 
2.8%
마 5
 
2.3%
국 5
 
2.3%
Other values (79) 142
66.0%

방문자 국적
Categorical

Distinct2
Distinct (%)7.1%
Missing0
Missing (%)0.0%
Memory size352.0 B
내국인
20 
외국인
8 

Length

Max length3
Median length3
Mean length3
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
내국인 20
71.4%
외국인 8
 
28.6%

Length

2024-03-15T04:55:41.878959image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-15T04:55:42.047122image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
내국인 20
71.4%
외국인 8
 
28.6%

01월
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct20
Distinct (%)71.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2140.1429
Minimum0
Maximum37388
Zeros8
Zeros (%)28.6%
Negative0
Negative (%)0.0%
Memory size380.0 B
2024-03-15T04:55:42.214724image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median415.5
Q3837.5
95-th percentile5355.95
Maximum37388
Range37388
Interquartile range (IQR)837.5

Descriptive statistics

Standard deviation7042.5547
Coefficient of variation (CV)3.2906937
Kurtosis25.677497
Mean2140.1429
Median Absolute Deviation (MAD)415.5
Skewness4.9907941
Sum59924
Variance49597576
MonotonicityNot monotonic
2024-03-15T04:55:42.432161image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=20)
ValueCountFrequency (%)
0 8
28.6%
713 2
 
7.1%
2185 1
 
3.6%
465 1
 
3.6%
315 1
 
3.6%
24 1
 
3.6%
1663 1
 
3.6%
226 1
 
3.6%
432 1
 
3.6%
419 1
 
3.6%
Other values (10) 10
35.7%
ValueCountFrequency (%)
0 8
28.6%
24 1
 
3.6%
98 1
 
3.6%
226 1
 
3.6%
315 1
 
3.6%
405 1
 
3.6%
412 1
 
3.6%
419 1
 
3.6%
432 1
 
3.6%
465 1
 
3.6%
ValueCountFrequency (%)
37388 1
3.6%
5623 1
3.6%
4860 1
3.6%
2185 1
3.6%
1663 1
3.6%
1565 1
3.6%
1211 1
3.6%
713 2
7.1%
662 1
3.6%
545 1
3.6%

02월
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct22
Distinct (%)78.6%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2086.9643
Minimum0
Maximum29717
Zeros7
Zeros (%)25.0%
Negative0
Negative (%)0.0%
Memory size380.0 B
2024-03-15T04:55:42.762632image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q16.75
median356.5
Q31000.75
95-th percentile6732.4
Maximum29717
Range29717
Interquartile range (IQR)994

Descriptive statistics

Standard deviation5712.3098
Coefficient of variation (CV)2.7371383
Kurtosis22.011347
Mean2086.9643
Median Absolute Deviation (MAD)356.5
Skewness4.527685
Sum58435
Variance32630483
MonotonicityNot monotonic
2024-03-15T04:55:43.147679image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=22)
ValueCountFrequency (%)
0 7
25.0%
4328 1
 
3.6%
364 1
 
3.6%
384 1
 
3.6%
56 1
 
3.6%
1968 1
 
3.6%
252 1
 
3.6%
295 1
 
3.6%
767 1
 
3.6%
391 1
 
3.6%
Other values (12) 12
42.9%
ValueCountFrequency (%)
0 7
25.0%
9 1
 
3.6%
56 1
 
3.6%
209 1
 
3.6%
252 1
 
3.6%
295 1
 
3.6%
343 1
 
3.6%
349 1
 
3.6%
364 1
 
3.6%
384 1
 
3.6%
ValueCountFrequency (%)
29717 1
3.6%
7046 1
3.6%
6150 1
3.6%
4328 1
3.6%
2213 1
3.6%
1968 1
3.6%
1240 1
3.6%
921 1
3.6%
846 1
3.6%
767 1
3.6%

03월
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct21
Distinct (%)75.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2427.3214
Minimum0
Maximum37176
Zeros8
Zeros (%)28.6%
Negative0
Negative (%)0.0%
Memory size380.0 B
2024-03-15T04:55:43.510365image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median398
Q31011.25
95-th percentile6523.85
Maximum37176
Range37176
Interquartile range (IQR)1011.25

Descriptive statistics

Standard deviation7045.0849
Coefficient of variation (CV)2.9024112
Kurtosis24.038529
Mean2427.3214
Median Absolute Deviation (MAD)398
Skewness4.7779905
Sum67965
Variance49633222
MonotonicityNot monotonic
2024-03-15T04:55:43.900079image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=21)
ValueCountFrequency (%)
0 8
28.6%
7059 1
 
3.6%
412 1
 
3.6%
344 1
 
3.6%
42 1
 
3.6%
2396 1
 
3.6%
237 1
 
3.6%
358 1
 
3.6%
829 1
 
3.6%
384 1
 
3.6%
Other values (11) 11
39.3%
ValueCountFrequency (%)
0 8
28.6%
42 1
 
3.6%
44 1
 
3.6%
237 1
 
3.6%
344 1
 
3.6%
358 1
 
3.6%
384 1
 
3.6%
412 1
 
3.6%
829 1
 
3.6%
846 1
 
3.6%
ValueCountFrequency (%)
37176 1
3.6%
7059 1
3.6%
5530 1
3.6%
4665 1
3.6%
2935 1
3.6%
2396 1
3.6%
1048 1
3.6%
999 1
3.6%
939 1
3.6%
867 1
3.6%

04월
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct22
Distinct (%)78.6%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2858.8929
Minimum0
Maximum46925
Zeros7
Zeros (%)25.0%
Negative0
Negative (%)0.0%
Memory size380.0 B
2024-03-15T04:55:44.333417image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q115.75
median527
Q31418.25
95-th percentile7170.15
Maximum46925
Range46925
Interquartile range (IQR)1402.5

Descriptive statistics

Standard deviation8836.5833
Coefficient of variation (CV)3.090911
Kurtosis25.261334
Mean2858.8929
Median Absolute Deviation (MAD)527
Skewness4.9364671
Sum80049
Variance78085205
MonotonicityNot monotonic
2024-03-15T04:55:44.646400image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=22)
ValueCountFrequency (%)
0 7
25.0%
8196 1
 
3.6%
381 1
 
3.6%
501 1
 
3.6%
59 1
 
3.6%
3357 1
 
3.6%
244 1
 
3.6%
300 1
 
3.6%
553 1
 
3.6%
663 1
 
3.6%
Other values (12) 12
42.9%
ValueCountFrequency (%)
0 7
25.0%
21 1
 
3.6%
59 1
 
3.6%
244 1
 
3.6%
300 1
 
3.6%
381 1
 
3.6%
444 1
 
3.6%
501 1
 
3.6%
553 1
 
3.6%
621 1
 
3.6%
ValueCountFrequency (%)
46925 1
3.6%
8196 1
3.6%
5265 1
3.6%
3734 1
3.6%
3357 1
3.6%
1914 1
3.6%
1659 1
3.6%
1338 1
3.6%
1318 1
3.6%
1311 1
3.6%

05월
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct22
Distinct (%)78.6%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean3912.1429
Minimum0
Maximum48733
Zeros7
Zeros (%)25.0%
Negative0
Negative (%)0.0%
Memory size380.0 B
2024-03-15T04:55:44.846134image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q125.5
median616
Q31659.5
95-th percentile18706.3
Maximum48733
Range48733
Interquartile range (IQR)1634

Descriptive statistics

Standard deviation10025.15
Coefficient of variation (CV)2.5625725
Kurtosis15.940548
Mean3912.1429
Median Absolute Deviation (MAD)616
Skewness3.8710275
Sum109540
Variance1.0050362 × 108
MonotonicityNot monotonic
2024-03-15T04:55:45.134674image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=22)
ValueCountFrequency (%)
0 7
25.0%
8188 1
 
3.6%
1206 1
 
3.6%
648 1
 
3.6%
55 1
 
3.6%
4323 1
 
3.6%
272 1
 
3.6%
376 1
 
3.6%
584 1
 
3.6%
733 1
 
3.6%
Other values (12) 12
42.9%
ValueCountFrequency (%)
0 7
25.0%
34 1
 
3.6%
55 1
 
3.6%
272 1
 
3.6%
320 1
 
3.6%
374 1
 
3.6%
376 1
 
3.6%
584 1
 
3.6%
648 1
 
3.6%
733 1
 
3.6%
ValueCountFrequency (%)
48733 1
3.6%
24370 1
3.6%
8188 1
3.6%
6723 1
3.6%
5258 1
3.6%
4323 1
3.6%
2183 1
3.6%
1485 1
3.6%
1373 1
3.6%
1283 1
3.6%

06월
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct22
Distinct (%)78.6%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean4063.1786
Minimum0
Maximum74402
Zeros7
Zeros (%)25.0%
Negative0
Negative (%)0.0%
Memory size380.0 B
2024-03-15T04:55:45.453014image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q149.5
median635.5
Q31322.75
95-th percentile7249.05
Maximum74402
Range74402
Interquartile range (IQR)1273.25

Descriptive statistics

Standard deviation13947.009
Coefficient of variation (CV)3.4325366
Kurtosis26.572454
Mean4063.1786
Median Absolute Deviation (MAD)634.5
Skewness5.1021087
Sum113769
Variance1.9451907 × 108
MonotonicityNot monotonic
2024-03-15T04:55:45.675972image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=22)
ValueCountFrequency (%)
0 7
25.0%
8116 1
 
3.6%
1199 1
 
3.6%
394 1
 
3.6%
66 1
 
3.6%
4007 1
 
3.6%
347 1
 
3.6%
367 1
 
3.6%
996 1
 
3.6%
549 1
 
3.6%
Other values (12) 12
42.9%
ValueCountFrequency (%)
0 7
25.0%
66 1
 
3.6%
73 1
 
3.6%
347 1
 
3.6%
367 1
 
3.6%
394 1
 
3.6%
399 1
 
3.6%
549 1
 
3.6%
722 1
 
3.6%
996 1
 
3.6%
ValueCountFrequency (%)
74402 1
3.6%
8116 1
3.6%
5639 1
3.6%
5404 1
3.6%
4913 1
3.6%
4007 1
3.6%
1484 1
3.6%
1269 1
3.6%
1199 1
3.6%
1176 1
3.6%

07월
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct21
Distinct (%)75.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean3761
Minimum0
Maximum61371
Zeros7
Zeros (%)25.0%
Negative0
Negative (%)0.0%
Memory size380.0 B
2024-03-15T04:55:45.881710image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q146.5
median647.5
Q33089.5
95-th percentile7765.35
Maximum61371
Range61371
Interquartile range (IQR)3043

Descriptive statistics

Standard deviation11504.823
Coefficient of variation (CV)3.0589797
Kurtosis25.734445
Mean3761
Median Absolute Deviation (MAD)647.5
Skewness4.9913078
Sum105308
Variance1.3236094 × 108
MonotonicityNot monotonic
2024-03-15T04:55:46.190602image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=21)
ValueCountFrequency (%)
0 7
25.0%
865 2
 
7.1%
6492 1
 
3.6%
225 1
 
3.6%
380 1
 
3.6%
8451 1
 
3.6%
3547 1
 
3.6%
259 1
 
3.6%
277 1
 
3.6%
777 1
 
3.6%
Other values (11) 11
39.3%
ValueCountFrequency (%)
0 7
25.0%
62 1
 
3.6%
225 1
 
3.6%
259 1
 
3.6%
277 1
 
3.6%
371 1
 
3.6%
380 1
 
3.6%
518 1
 
3.6%
777 1
 
3.6%
865 2
 
7.1%
ValueCountFrequency (%)
61371 1
3.6%
8451 1
3.6%
6492 1
3.6%
5421 1
3.6%
3731 1
3.6%
3547 1
3.6%
3475 1
3.6%
2961 1
3.6%
2584 1
3.6%
1390 1
3.6%

08월
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct21
Distinct (%)75.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean4980.6786
Minimum0
Maximum82546
Zeros7
Zeros (%)25.0%
Negative0
Negative (%)0.0%
Memory size380.0 B
2024-03-15T04:55:46.561225image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q122.5
median708.5
Q32862.25
95-th percentile10864.6
Maximum82546
Range82546
Interquartile range (IQR)2839.75

Descriptive statistics

Standard deviation15512.063
Coefficient of variation (CV)3.1144478
Kurtosis25.568947
Mean4980.6786
Median Absolute Deviation (MAD)708.5
Skewness4.9712433
Sum139459
Variance2.4062411 × 108
MonotonicityNot monotonic
2024-03-15T04:55:46.937894image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=21)
ValueCountFrequency (%)
0 7
25.0%
452 2
 
7.1%
7129 1
 
3.6%
1805 1
 
3.6%
11195 1
 
3.6%
3854 1
 
3.6%
264 1
 
3.6%
320 1
 
3.6%
2579 1
 
3.6%
10251 1
 
3.6%
Other values (11) 11
39.3%
ValueCountFrequency (%)
0 7
25.0%
30 1
 
3.6%
230 1
 
3.6%
264 1
 
3.6%
320 1
 
3.6%
406 1
 
3.6%
452 2
 
7.1%
965 1
 
3.6%
1013 1
 
3.6%
1134 1
 
3.6%
ValueCountFrequency (%)
82546 1
3.6%
11195 1
3.6%
10251 1
3.6%
7129 1
3.6%
6746 1
3.6%
3854 1
3.6%
2971 1
3.6%
2826 1
3.6%
2579 1
3.6%
2291 1
3.6%

9월
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct22
Distinct (%)78.6%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean4137.3929
Minimum0
Maximum65549
Zeros7
Zeros (%)25.0%
Negative0
Negative (%)0.0%
Memory size380.0 B
2024-03-15T04:55:47.257695image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q131.5
median396.5
Q31192.5
95-th percentile16000.95
Maximum65549
Range65549
Interquartile range (IQR)1161

Descriptive statistics

Standard deviation12709.752
Coefficient of variation (CV)3.0719229
Kurtosis21.978049
Mean4137.3929
Median Absolute Deviation (MAD)396.5
Skewness4.5560798
Sum115847
Variance1.6153779 × 108
MonotonicityNot monotonic
2024-03-15T04:55:47.497836image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=22)
ValueCountFrequency (%)
0 7
25.0%
8433 1
 
3.6%
437 1
 
3.6%
414 1
 
3.6%
42 1
 
3.6%
3812 1
 
3.6%
357 1
 
3.6%
308 1
 
3.6%
471 1
 
3.6%
379 1
 
3.6%
Other values (12) 12
42.9%
ValueCountFrequency (%)
0 7
25.0%
42 1
 
3.6%
159 1
 
3.6%
231 1
 
3.6%
259 1
 
3.6%
308 1
 
3.6%
357 1
 
3.6%
379 1
 
3.6%
414 1
 
3.6%
437 1
 
3.6%
ValueCountFrequency (%)
65549 1
3.6%
20076 1
3.6%
8433 1
3.6%
5271 1
3.6%
4612 1
3.6%
3812 1
3.6%
1332 1
3.6%
1146 1
3.6%
965 1
3.6%
897 1
3.6%

10월
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct22
Distinct (%)78.6%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean14804.107
Minimum0
Maximum233755
Zeros7
Zeros (%)25.0%
Negative0
Negative (%)0.0%
Memory size380.0 B
2024-03-15T04:55:47.804464image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q126.25
median600.5
Q32292.75
95-th percentile94526.25
Maximum233755
Range233755
Interquartile range (IQR)2266.5

Descriptive statistics

Standard deviation50368.807
Coefficient of variation (CV)3.4023536
Kurtosis14.968981
Mean14804.107
Median Absolute Deviation (MAD)600.5
Skewness3.8788679
Sum414515
Variance2.5370167 × 109
MonotonicityNot monotonic
2024-03-15T04:55:48.058600image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=22)
ValueCountFrequency (%)
0 7
25.0%
8749 1
 
3.6%
365 1
 
3.6%
482 1
 
3.6%
35 1
 
3.6%
4783 1
 
3.6%
317 1
 
3.6%
343 1
 
3.6%
1196 1
 
3.6%
719 1
 
3.6%
Other values (12) 12
42.9%
ValueCountFrequency (%)
0 7
25.0%
35 1
 
3.6%
163 1
 
3.6%
253 1
 
3.6%
317 1
 
3.6%
343 1
 
3.6%
365 1
 
3.6%
482 1
 
3.6%
719 1
 
3.6%
864 1
 
3.6%
ValueCountFrequency (%)
233755 1
3.6%
140714 1
3.6%
8749 1
3.6%
6227 1
3.6%
5555 1
3.6%
4783 1
3.6%
3105 1
3.6%
2022 1
3.6%
1845 1
3.6%
1608 1
3.6%

11월
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct22
Distinct (%)78.6%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean8785.0714
Minimum0
Maximum193798
Zeros7
Zeros (%)25.0%
Negative0
Negative (%)0.0%
Memory size380.0 B
2024-03-15T04:55:48.413430image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q121
median730
Q34430.25
95-th percentile8651.85
Maximum193798
Range193798
Interquartile range (IQR)4409.25

Descriptive statistics

Standard deviation36352.494
Coefficient of variation (CV)4.137985
Kurtosis27.680025
Mean8785.0714
Median Absolute Deviation (MAD)730
Skewness5.2482554
Sum245982
Variance1.3215038 × 109
MonotonicityNot monotonic
2024-03-15T04:55:48.819047image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=22)
ValueCountFrequency (%)
0 7
25.0%
7099 1
 
3.6%
4362 1
 
3.6%
426 1
 
3.6%
28 1
 
3.6%
4635 1
 
3.6%
248 1
 
3.6%
344 1
 
3.6%
1062 1
 
3.6%
638 1
 
3.6%
Other values (12) 12
42.9%
ValueCountFrequency (%)
0 7
25.0%
28 1
 
3.6%
130 1
 
3.6%
248 1
 
3.6%
344 1
 
3.6%
426 1
 
3.6%
524 1
 
3.6%
638 1
 
3.6%
822 1
 
3.6%
1062 1
 
3.6%
ValueCountFrequency (%)
193798 1
3.6%
9488 1
3.6%
7099 1
3.6%
5998 1
3.6%
5338 1
3.6%
5035 1
3.6%
4635 1
3.6%
4362 1
3.6%
2475 1
3.6%
1253 1
3.6%

12월
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct21
Distinct (%)75.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2462.1786
Minimum0
Maximum33188
Zeros8
Zeros (%)28.6%
Negative0
Negative (%)0.0%
Memory size380.0 B
2024-03-15T04:55:49.140575image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median467
Q31773
95-th percentile6702.4
Maximum33188
Range33188
Interquartile range (IQR)1773

Descriptive statistics

Standard deviation6333.0686
Coefficient of variation (CV)2.5721402
Kurtosis22.304881
Mean2462.1786
Median Absolute Deviation (MAD)467
Skewness4.5483754
Sum68941
Variance40107757
MonotonicityNot monotonic
2024-03-15T04:55:49.339701image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=21)
ValueCountFrequency (%)
0 8
28.6%
2910 1
 
3.6%
113 1
 
3.6%
361 1
 
3.6%
21 1
 
3.6%
3364 1
 
3.6%
276 1
 
3.6%
336 1
 
3.6%
970 1
 
3.6%
404 1
 
3.6%
Other values (11) 11
39.3%
ValueCountFrequency (%)
0 8
28.6%
21 1
 
3.6%
113 1
 
3.6%
276 1
 
3.6%
336 1
 
3.6%
361 1
 
3.6%
404 1
 
3.6%
530 1
 
3.6%
642 1
 
3.6%
735 1
 
3.6%
ValueCountFrequency (%)
33188 1
3.6%
7184 1
3.6%
5808 1
3.6%
5471 1
3.6%
3364 1
3.6%
2980 1
3.6%
2910 1
3.6%
1394 1
3.6%
1370 1
3.6%
970 1
3.6%

데이터기준일자
Date

CONSTANT 

Distinct1
Distinct (%)3.6%
Missing0
Missing (%)0.0%
Memory size352.0 B
Minimum2023-12-31 00:00:00
Maximum2023-12-31 00:00:00
2024-03-15T04:55:49.615508image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T04:55:49.924603image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=1)

Interactions

2024-03-15T04:55:35.248197image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T04:55:00.146755image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T04:55:03.126715image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T04:55:07.559382image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T04:55:10.659680image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T04:55:13.605074image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T04:55:16.652712image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T04:55:19.591009image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T04:55:23.215247image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T04:55:26.398992image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T04:55:29.569417image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T04:55:32.530969image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T04:55:35.508259image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T04:55:00.449936image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T04:55:03.363759image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T04:55:07.860527image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T04:55:10.906844image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T04:55:13.853195image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T04:55:16.910791image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T04:55:19.900602image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T04:55:23.501753image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T04:55:26.652976image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T04:55:29.822155image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T04:55:32.801284image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T04:55:35.760051image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T04:55:00.702743image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T04:55:03.645919image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T04:55:08.111773image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T04:55:11.147071image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T04:55:14.293276image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T04:55:17.110593image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T04:55:20.275632image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T04:55:24.015569image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T04:55:26.900290image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T04:55:30.103830image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T04:55:32.957514image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T04:55:36.018465image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T04:55:00.959125image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T04:55:04.024335image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T04:55:08.374626image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T04:55:11.397102image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T04:55:14.540590image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T04:55:17.369224image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T04:55:20.554849image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T04:55:24.262804image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T04:55:27.154090image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T04:55:30.357163image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T04:55:33.122145image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T04:55:36.252476image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T04:55:01.194958image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T04:55:04.293500image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T04:55:08.619163image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T04:55:11.631086image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T04:55:14.769978image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T04:55:17.615398image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T04:55:20.872490image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T04:55:24.489644image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T04:55:27.388549image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T04:55:30.585463image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T04:55:33.359469image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T04:55:36.497799image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T04:55:01.451431image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T04:55:04.537394image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T04:55:08.869496image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T04:55:11.867977image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T04:55:15.005893image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T04:55:17.880584image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T04:55:21.165007image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T04:55:24.721536image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T04:55:27.629941image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T04:55:30.824324image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T04:55:33.609937image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T04:55:36.753467image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T04:55:01.734764image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T04:55:04.852742image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T04:55:09.129412image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T04:55:12.115610image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T04:55:15.255926image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T04:55:18.138593image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T04:55:21.501712image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T04:55:24.970326image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T04:55:27.886580image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T04:55:31.080009image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T04:55:33.938130image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T04:55:37.048001image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T04:55:01.991465image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T04:55:05.300483image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T04:55:09.384353image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T04:55:12.354941image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T04:55:15.499917image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T04:55:18.387036image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T04:55:21.771649image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T04:55:25.211870image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T04:55:28.334254image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T04:55:31.325586image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T04:55:34.199112image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T04:55:37.315588image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T04:55:02.230164image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T04:55:05.666296image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T04:55:09.641578image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T04:55:12.583179image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T04:55:15.730745image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T04:55:18.627223image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T04:55:22.019511image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T04:55:25.435104image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T04:55:28.571625image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T04:55:31.554466image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T04:55:34.442722image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T04:55:37.593900image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T04:55:02.488668image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T04:55:06.230586image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T04:55:09.893569image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T04:55:12.838197image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T04:55:15.932383image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T04:55:18.878757image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T04:55:22.282944image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T04:55:25.675233image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T04:55:28.823335image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T04:55:31.802928image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T04:55:34.700357image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T04:55:37.856594image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T04:55:02.734432image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T04:55:06.530110image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T04:55:10.134154image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T04:55:13.069749image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T04:55:16.127903image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T04:55:19.122618image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T04:55:22.555601image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T04:55:25.899957image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T04:55:29.057412image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T04:55:32.029457image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T04:55:34.905622image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T04:55:38.144708image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T04:55:02.959753image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T04:55:07.080304image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T04:55:10.405031image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T04:55:13.325226image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T04:55:16.386967image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T04:55:19.386381image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T04:55:22.910760image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T04:55:26.158125image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T04:55:29.321946image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T04:55:32.288770image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T04:55:35.074962image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-03-15T04:55:50.216231image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
관광지 명칭방문자 국적01월02월03월04월05월06월07월08월9월10월11월12월
관광지 명칭1.0000.0000.6450.9200.6440.6450.9190.6470.6450.6450.9200.6470.0000.000
방문자 국적0.0001.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.000
01월0.6450.0001.0001.0000.9930.9610.8260.9320.9320.9320.6430.9321.0000.826
02월0.9200.0001.0001.0001.0000.8500.9761.0000.7840.6440.9770.6421.0000.951
03월0.6440.0000.9931.0001.0000.9931.0000.9710.9500.9330.7370.9321.0000.760
04월0.6450.0000.9610.8500.9931.0000.8260.9850.9610.9320.7840.9321.0000.682
05월0.9190.0000.8260.9761.0000.8261.0000.7370.6820.7850.9901.0001.0000.923
06월0.6470.0000.9321.0000.9710.9850.7371.0000.9850.9321.0000.9321.0000.643
07월0.6450.0000.9320.7840.9500.9610.6820.9851.0000.9610.7840.9321.0000.645
08월0.6450.0000.9320.6440.9330.9320.7850.9320.9611.0000.7840.9851.0000.645
9월0.9200.0000.6430.9770.7370.7840.9901.0000.7840.7841.0001.0001.0000.853
10월0.6470.0000.9320.6420.9320.9321.0000.9320.9320.9851.0001.0001.0000.643
11월0.0000.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.000
12월0.0000.0000.8260.9510.7600.6820.9230.6430.6450.6450.8530.6431.0001.000
2024-03-15T04:55:50.577197image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
01월02월03월04월05월06월07월08월9월10월11월12월방문자 국적
01월1.0000.9750.9150.9470.9490.9310.8210.8460.9520.8610.8050.8770.000
02월0.9751.0000.9170.9640.9640.9490.8360.8590.9610.8950.8590.8990.000
03월0.9150.9171.0000.9670.9050.9140.7790.7940.9130.8880.8140.8190.000
04월0.9470.9640.9671.0000.9760.9620.8490.8570.9700.9220.8690.8930.000
05월0.9490.9640.9050.9761.0000.9620.8780.8810.9890.9320.8980.9100.000
06월0.9310.9490.9140.9620.9621.0000.8660.8560.9570.8900.8920.9390.000
07월0.8210.8360.7790.8490.8780.8661.0000.9830.8650.8070.8090.8580.000
08월0.8460.8590.7940.8570.8810.8560.9831.0000.8780.8280.8060.8380.000
9월0.9520.9610.9130.9700.9890.9570.8650.8781.0000.9450.9000.8930.000
10월0.8610.8950.8880.9220.9320.8900.8070.8280.9451.0000.9670.8120.000
11월0.8050.8590.8140.8690.8980.8920.8090.8060.9000.9671.0000.8350.000
12월0.8770.8990.8190.8930.9100.9390.8580.8380.8930.8120.8351.0000.000
방문자 국적0.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0001.000

Missing values

2024-03-15T04:55:38.391163image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-03-15T04:55:39.094480image/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

관광지 명칭방문자 국적01월02월03월04월05월06월07월08월9월10월11월12월데이터기준일자
0내장산 골프앤리조트내국인2185432870598196818881166492712984338749709929102023-12-31
1송참봉조선동네내국인121192110481338128314848659659658648226422023-12-31
2정읍시 내장산 국민여가캠핑장내국인4860615055305265672354042961297146126227503558082023-12-31
3천사히어로즈내국인5623704646651914525849135421674652715555533854712023-12-31
4국립전북기상과학관내국인71312409991659218310751390229111463105247513702023-12-31
5국립전북기상과학관외국인0000000000002023-12-31
6꽃두레 행복마을 센터내국인98343939621320117651840623125352413942023-12-31
7꽃두레 행복마을 센터외국인0000000000002023-12-31
8태산선비마을내국인4052098671245101972212861013697184511127352023-12-31
9태산선비마을외국인0000000000002023-12-31
관광지 명칭방문자 국적01월02월03월04월05월06월07월08월9월10월11월12월데이터기준일자
18정읍 첨단과학관내국인4653494124443743992252302591631301132023-12-31
19정읍 첨단과학관외국인0000000000002023-12-31
20구절초 지방정원내국인156522132935373424370563937311025120076233755948829802023-12-31
21김명관고택내국인4193913846637335493714523797196384042023-12-31
22동학농민혁명기념관내국인7137678295535849967772579471119610629702023-12-31
23박준승 기념관내국인4322953583003763672773203083433443362023-12-31
24백정기의사기념관내국인2262522372442723472592643573172482762023-12-31
25정읍시립박물관내국인1663196823963357432340073547385438124783463533642023-12-31
26칠보물테마유원지(전시관)내국인245642595566845111195423528212023-12-31
27피향정내국인3153843445016483943804524144824263612023-12-31