Overview

Dataset statistics

Number of variables9
Number of observations60
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory4.8 KiB
Average record size in memory82.1 B

Variable types

DateTime1
Numeric8

Dataset

Description산림청 국립수목원의 월별 방문객 수에 대한 데이터로 어른, 청소년, 어린이, 유아 등으로 구분하여 각각의 항목에 대한 데이터를 제공합니다.
Author산림청 국립수목원
URLhttps://www.data.go.kr/data/15039322/fileData.do

Alerts

누적인원(명) is highly overall correlated with 입장객(기타)High correlation
입장인원(명) is highly overall correlated with 입장객(어른) and 5 other fieldsHigh correlation
입장객(어른) is highly overall correlated with 입장인원(명) and 5 other fieldsHigh correlation
입장객(청소년) is highly overall correlated with 입장인원(명) and 4 other fieldsHigh correlation
입장객(어린이) is highly overall correlated with 입장인원(명) and 4 other fieldsHigh correlation
입장객(유아) is highly overall correlated with 입장인원(명) and 5 other fieldsHigh correlation
입장객(경로) is highly overall correlated with 입장인원(명) and 5 other fieldsHigh correlation
입장객(기타) is highly overall correlated with 누적인원(명) and 4 other fieldsHigh correlation
구분 has unique valuesUnique
입장인원(명) has unique valuesUnique
입장객(어른) has unique valuesUnique
입장객(유아) has unique valuesUnique
입장객(경로) has unique valuesUnique
입장인원(명) has 1 (1.7%) zerosZeros
입장객(어른) has 1 (1.7%) zerosZeros
입장객(청소년) has 1 (1.7%) zerosZeros
입장객(어린이) has 1 (1.7%) zerosZeros
입장객(유아) has 1 (1.7%) zerosZeros
입장객(경로) has 1 (1.7%) zerosZeros
입장객(기타) has 2 (3.3%) zerosZeros

Reproduction

Analysis started2024-03-15 01:34:13.811723
Analysis finished2024-03-15 01:34:30.667032
Duration16.86 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

구분
Date

UNIQUE 

Distinct60
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size608.0 B
Minimum2019-01-31 00:00:00
Maximum2023-12-31 00:00:00
2024-03-15T10:34:30.806870image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T10:34:31.066316image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

누적인원(명)
Real number (ℝ)

HIGH CORRELATION 

Distinct59
Distinct (%)98.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean166894.38
Minimum4182
Maximum402392
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size668.0 B
2024-03-15T10:34:31.415185image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum4182
5-th percentile7282.85
Q154130.75
median151551.5
Q3250588.25
95-th percentile387089.95
Maximum402392
Range398210
Interquartile range (IQR)196457.5

Descriptive statistics

Standard deviation121640.33
Coefficient of variation (CV)0.72884616
Kurtosis-0.94247097
Mean166894.38
Median Absolute Deviation (MAD)99793
Skewness0.34202092
Sum10013663
Variance1.479637 × 1010
MonotonicityNot monotonic
2024-03-15T10:34:31.707416image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
125352 2
 
3.3%
4947 1
 
1.7%
15300 1
 
1.7%
217030 1
 
1.7%
255845 1
 
1.7%
288051 1
 
1.7%
297003 1
 
1.7%
5019 1
 
1.7%
15089 1
 
1.7%
50146 1
 
1.7%
Other values (49) 49
81.7%
ValueCountFrequency (%)
4182 1
1.7%
4947 1
1.7%
5019 1
1.7%
7402 1
1.7%
8135 1
1.7%
9988 1
1.7%
14055 1
1.7%
15089 1
1.7%
15300 1
1.7%
17017 1
1.7%
ValueCountFrequency (%)
402392 1
1.7%
394629 1
1.7%
394157 1
1.7%
386718 1
1.7%
370682 1
1.7%
364268 1
1.7%
354978 1
1.7%
344067 1
1.7%
322700 1
1.7%
297003 1
1.7%

입장인원(명)
Real number (ℝ)

HIGH CORRELATION  UNIQUE  ZEROS 

Distinct60
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean28225.583
Minimum0
Maximum72593
Zeros1
Zeros (%)1.7%
Negative0
Negative (%)0.0%
Memory size668.0 B
2024-03-15T10:34:31.991687image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile4908.75
Q19324
median31372.5
Q339352.75
95-th percentile59034.5
Maximum72593
Range72593
Interquartile range (IQR)30028.75

Descriptive statistics

Standard deviation18095.859
Coefficient of variation (CV)0.64111551
Kurtosis-0.3267096
Mean28225.583
Median Absolute Deviation (MAD)11796
Skewness0.39310015
Sum1693535
Variance3.2746012 × 108
MonotonicityNot monotonic
2024-03-15T10:34:32.255817image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
4947 1
 
1.7%
33023 1
 
1.7%
38815 1
 
1.7%
32206 1
 
1.7%
8952 1
 
1.7%
5019 1
 
1.7%
10070 1
 
1.7%
35057 1
 
1.7%
33645 1
 
1.7%
41561 1
 
1.7%
Other values (50) 50
83.3%
ValueCountFrequency (%)
0 1
1.7%
1906 1
1.7%
4182 1
1.7%
4947 1
1.7%
5019 1
1.7%
5806 1
1.7%
6414 1
1.7%
6653 1
1.7%
7402 1
1.7%
7911 1
1.7%
ValueCountFrequency (%)
72593 1
1.7%
69543 1
1.7%
68354 1
1.7%
58544 1
1.7%
57021 1
1.7%
52305 1
1.7%
49428 1
1.7%
47523 1
1.7%
43265 1
1.7%
43072 1
1.7%

입장객(어른)
Real number (ℝ)

HIGH CORRELATION  UNIQUE  ZEROS 

Distinct60
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean15999.7
Minimum0
Maximum35158
Zeros1
Zeros (%)1.7%
Negative0
Negative (%)0.0%
Memory size668.0 B
2024-03-15T10:34:32.666497image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile2825.25
Q15837
median17938.5
Q322421.25
95-th percentile31209.2
Maximum35158
Range35158
Interquartile range (IQR)16584.25

Descriptive statistics

Standard deviation9486.5723
Coefficient of variation (CV)0.59292189
Kurtosis-0.94432865
Mean15999.7
Median Absolute Deviation (MAD)6888
Skewness0.070643841
Sum959982
Variance89995054
MonotonicityNot monotonic
2024-03-15T10:34:33.116764image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
2203 1
 
1.7%
22726 1
 
1.7%
25416 1
 
1.7%
20518 1
 
1.7%
5747 1
 
1.7%
3450 1
 
1.7%
6675 1
 
1.7%
21540 1
 
1.7%
20955 1
 
1.7%
26217 1
 
1.7%
Other values (50) 50
83.3%
ValueCountFrequency (%)
0 1
1.7%
1302 1
1.7%
2203 1
1.7%
2858 1
1.7%
3450 1
1.7%
3627 1
1.7%
3857 1
1.7%
4091 1
1.7%
4547 1
1.7%
4578 1
1.7%
ValueCountFrequency (%)
35158 1
1.7%
34919 1
1.7%
34101 1
1.7%
31057 1
1.7%
30847 1
1.7%
28968 1
1.7%
26380 1
1.7%
26217 1
1.7%
25416 1
1.7%
24936 1
1.7%

입장객(청소년)
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct57
Distinct (%)95.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean398.85
Minimum0
Maximum2133
Zeros1
Zeros (%)1.7%
Negative0
Negative (%)0.0%
Memory size668.0 B
2024-03-15T10:34:33.713910image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile66.45
Q1154.5
median287
Q3520.75
95-th percentile890.6
Maximum2133
Range2133
Interquartile range (IQR)366.25

Descriptive statistics

Standard deviation358.99699
Coefficient of variation (CV)0.90008022
Kurtosis8.2718111
Mean398.85
Median Absolute Deviation (MAD)168
Skewness2.3071438
Sum23931
Variance128878.84
MonotonicityNot monotonic
2024-03-15T10:34:34.181414image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
430 2
 
3.3%
234 2
 
3.3%
138 2
 
3.3%
56 1
 
1.7%
105 1
 
1.7%
165 1
 
1.7%
196 1
 
1.7%
885 1
 
1.7%
688 1
 
1.7%
782 1
 
1.7%
Other values (47) 47
78.3%
ValueCountFrequency (%)
0 1
1.7%
54 1
1.7%
56 1
1.7%
67 1
1.7%
86 1
1.7%
88 1
1.7%
90 1
1.7%
100 1
1.7%
104 1
1.7%
105 1
1.7%
ValueCountFrequency (%)
2133 1
1.7%
1260 1
1.7%
997 1
1.7%
885 1
1.7%
881 1
1.7%
836 1
1.7%
782 1
1.7%
765 1
1.7%
757 1
1.7%
715 1
1.7%

입장객(어린이)
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct59
Distinct (%)98.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean952.11667
Minimum0
Maximum3001
Zeros1
Zeros (%)1.7%
Negative0
Negative (%)0.0%
Memory size668.0 B
2024-03-15T10:34:34.604878image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile102.65
Q1379.5
median793
Q31321.5
95-th percentile2381.5
Maximum3001
Range3001
Interquartile range (IQR)942

Descriptive statistics

Standard deviation724.52105
Coefficient of variation (CV)0.76095827
Kurtosis0.87318454
Mean952.11667
Median Absolute Deviation (MAD)425
Skewness1.0704977
Sum57127
Variance524930.75
MonotonicityNot monotonic
2024-03-15T10:34:35.119586image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
128 2
 
3.3%
64 1
 
1.7%
258 1
 
1.7%
1313 1
 
1.7%
1729 1
 
1.7%
1089 1
 
1.7%
372 1
 
1.7%
547 1
 
1.7%
3001 1
 
1.7%
2291 1
 
1.7%
Other values (49) 49
81.7%
ValueCountFrequency (%)
0 1
1.7%
64 1
1.7%
96 1
1.7%
103 1
1.7%
109 1
1.7%
128 2
3.3%
144 1
1.7%
258 1
1.7%
262 1
1.7%
287 1
1.7%
ValueCountFrequency (%)
3001 1
1.7%
2991 1
1.7%
2619 1
1.7%
2369 1
1.7%
2291 1
1.7%
2116 1
1.7%
1729 1
1.7%
1674 1
1.7%
1654 1
1.7%
1613 1
1.7%

입장객(유아)
Real number (ℝ)

HIGH CORRELATION  UNIQUE  ZEROS 

Distinct60
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1658.3167
Minimum0
Maximum8851
Zeros1
Zeros (%)1.7%
Negative0
Negative (%)0.0%
Memory size668.0 B
2024-03-15T10:34:35.732471image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile129.35
Q1447.25
median1389.5
Q32260.25
95-th percentile4089
Maximum8851
Range8851
Interquartile range (IQR)1813

Descriptive statistics

Standard deviation1511.945
Coefficient of variation (CV)0.91173478
Kurtosis7.518282
Mean1658.3167
Median Absolute Deviation (MAD)942
Skewness2.1026789
Sum99499
Variance2285977.6
MonotonicityNot monotonic
2024-03-15T10:34:36.216691image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
76 1
 
1.7%
1714 1
 
1.7%
1742 1
 
1.7%
1324 1
 
1.7%
266 1
 
1.7%
147 1
 
1.7%
751 1
 
1.7%
3199 1
 
1.7%
2454 1
 
1.7%
2645 1
 
1.7%
Other values (50) 50
83.3%
ValueCountFrequency (%)
0 1
1.7%
76 1
1.7%
98 1
1.7%
131 1
1.7%
147 1
1.7%
154 1
1.7%
161 1
1.7%
222 1
1.7%
266 1
1.7%
274 1
1.7%
ValueCountFrequency (%)
8851 1
1.7%
4501 1
1.7%
4317 1
1.7%
4077 1
1.7%
4036 1
1.7%
3841 1
1.7%
3254 1
1.7%
3199 1
1.7%
2987 1
1.7%
2799 1
1.7%

입장객(경로)
Real number (ℝ)

HIGH CORRELATION  UNIQUE  ZEROS 

Distinct60
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean6809.5833
Minimum0
Maximum20115
Zeros1
Zeros (%)1.7%
Negative0
Negative (%)0.0%
Memory size668.0 B
2024-03-15T10:34:36.663364image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile886.7
Q12087.25
median6690
Q38903.25
95-th percentile15774.6
Maximum20115
Range20115
Interquartile range (IQR)6816

Descriptive statistics

Standard deviation5022.3784
Coefficient of variation (CV)0.73754563
Kurtosis0.029034117
Mean6809.5833
Median Absolute Deviation (MAD)4386.5
Skewness0.74532376
Sum408575
Variance25224285
MonotonicityNot monotonic
2024-03-15T10:34:37.161473image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1272 1
 
1.7%
6074 1
 
1.7%
7947 1
 
1.7%
7724 1
 
1.7%
2268 1
 
1.7%
1044 1
 
1.7%
1811 1
 
1.7%
6362 1
 
1.7%
7189 1
 
1.7%
8907 1
 
1.7%
Other values (50) 50
83.3%
ValueCountFrequency (%)
0 1
1.7%
335 1
1.7%
767 1
1.7%
893 1
1.7%
1044 1
1.7%
1131 1
1.7%
1154 1
1.7%
1231 1
1.7%
1272 1
1.7%
1496 1
1.7%
ValueCountFrequency (%)
20115 1
1.7%
19398 1
1.7%
16071 1
1.7%
15759 1
1.7%
15579 1
1.7%
14993 1
1.7%
14941 1
1.7%
14406 1
1.7%
12180 1
1.7%
11579 1
1.7%

입장객(기타)
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct59
Distinct (%)98.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2407.0167
Minimum0
Maximum12099
Zeros2
Zeros (%)3.3%
Negative0
Negative (%)0.0%
Memory size668.0 B
2024-03-15T10:34:37.842633image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile23.85
Q1144.25
median985
Q33572.25
95-th percentile9429.55
Maximum12099
Range12099
Interquartile range (IQR)3428

Descriptive statistics

Standard deviation3125.426
Coefficient of variation (CV)1.2984646
Kurtosis1.8698922
Mean2407.0167
Median Absolute Deviation (MAD)903.5
Skewness1.5998165
Sum144421
Variance9768287.7
MonotonicityNot monotonic
2024-03-15T10:34:38.309695image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 2
 
3.3%
1276 1
 
1.7%
801 1
 
1.7%
1554 1
 
1.7%
906 1
 
1.7%
146 1
 
1.7%
85 1
 
1.7%
90 1
 
1.7%
70 1
 
1.7%
68 1
 
1.7%
Other values (49) 49
81.7%
ValueCountFrequency (%)
0 2
3.3%
21 1
1.7%
24 1
1.7%
25 1
1.7%
48 1
1.7%
68 1
1.7%
70 1
1.7%
78 1
1.7%
85 1
1.7%
88 1
1.7%
ValueCountFrequency (%)
12099 1
1.7%
11795 1
1.7%
10219 1
1.7%
9388 1
1.7%
7778 1
1.7%
6445 1
1.7%
6392 1
1.7%
6318 1
1.7%
6101 1
1.7%
6058 1
1.7%

Interactions

2024-03-15T10:34:28.339439image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T10:34:14.211477image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T10:34:16.232783image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T10:34:18.348374image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T10:34:20.248918image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T10:34:22.280885image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T10:34:24.572023image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T10:34:26.462588image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T10:34:28.602994image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T10:34:14.485927image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T10:34:16.424100image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T10:34:18.528315image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T10:34:20.586028image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T10:34:22.588791image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T10:34:24.836414image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T10:34:26.739653image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T10:34:28.876947image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T10:34:14.754370image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T10:34:16.678017image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T10:34:18.693133image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T10:34:20.852362image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T10:34:22.924991image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T10:34:25.091936image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T10:34:27.005141image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T10:34:29.044046image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T10:34:15.029304image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T10:34:17.013186image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T10:34:18.889252image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T10:34:21.121652image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T10:34:23.205100image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T10:34:25.415735image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T10:34:27.231365image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T10:34:29.182748image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T10:34:15.349233image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T10:34:17.178843image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T10:34:19.133209image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T10:34:21.367303image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T10:34:23.467214image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T10:34:25.649020image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T10:34:27.379437image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T10:34:29.371773image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T10:34:15.517578image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T10:34:17.437015image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T10:34:19.396492image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T10:34:21.616071image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T10:34:23.730770image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T10:34:25.894245image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T10:34:27.559751image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T10:34:29.715487image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T10:34:15.711664image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T10:34:17.693052image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T10:34:19.640153image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T10:34:21.753863image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T10:34:24.011049image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T10:34:26.024381image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T10:34:27.812429image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T10:34:29.886641image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T10:34:15.964461image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T10:34:17.919708image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T10:34:19.911267image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T10:34:22.021750image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T10:34:24.317267image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T10:34:26.216570image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T10:34:28.078806image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-03-15T10:34:38.595614image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
구분누적인원(명)입장인원(명)입장객(어른)입장객(청소년)입장객(어린이)입장객(유아)입장객(경로)입장객(기타)
구분1.0001.0001.0001.0001.0001.0001.0001.0001.000
누적인원(명)1.0001.0000.7990.7760.5870.5510.5900.4670.848
입장인원(명)1.0000.7991.0000.9490.7950.7540.7370.8310.865
입장객(어른)1.0000.7760.9491.0000.7270.7040.7740.6930.727
입장객(청소년)1.0000.5870.7950.7271.0000.8280.9170.6690.596
입장객(어린이)1.0000.5510.7540.7040.8281.0000.7300.7510.454
입장객(유아)1.0000.5900.7370.7740.9170.7301.0000.5830.653
입장객(경로)1.0000.4670.8310.6930.6690.7510.5831.0000.744
입장객(기타)1.0000.8480.8650.7270.5960.4540.6530.7441.000
2024-03-15T10:34:38.814999image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
누적인원(명)입장인원(명)입장객(어른)입장객(청소년)입장객(어린이)입장객(유아)입장객(경로)입장객(기타)
누적인원(명)1.0000.3830.3590.3320.1830.3330.3690.512
입장인원(명)0.3831.0000.9590.8200.7960.8910.9430.649
입장객(어른)0.3590.9591.0000.8530.8830.8930.8550.527
입장객(청소년)0.3320.8200.8531.0000.8400.8150.7150.453
입장객(어린이)0.1830.7960.8830.8401.0000.8780.6760.271
입장객(유아)0.3330.8910.8930.8150.8781.0000.8000.513
입장객(경로)0.3690.9430.8550.7150.6760.8001.0000.678
입장객(기타)0.5120.6490.5270.4530.2710.5130.6781.000

Missing values

2024-03-15T10:34:30.176589image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-03-15T10:34:30.573733image/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

구분누적인원(명)입장인원(명)입장객(어른)입장객(청소년)입장객(어린이)입장객(유아)입장객(경로)입장객(기타)
02023-01-3149474947220356647612721276
12023-02-281530010353498115525832824412190
22023-03-31434572815713372236626110567176101
32023-04-3090980475232156771598418581218010219
42023-05-3114328552305243263307862482149939388
52023-06-3018635743072210162516511797115797778
62023-07-31218999326421801743053873180824844
72023-08-31249732307331674638565479075354623
82023-09-302823853265314795222656182387656392
92023-10-313549787259335158538108343171939812099
구분누적인원(명)입장인원(명)입장객(어른)입장객(청소년)입장객(어린이)입장객(유아)입장객(경로)입장객(기타)
502019-03-312408614098934621059711812243521
512019-04-305545931373174282431456253773432366
522019-05-311140035854430847126026194077144065335
532019-06-3016343149428310574702116325492063325
542019-07-311939103047920366681990150256611279
552019-08-312284213451123238881147319206075924
562019-09-302531572473612716836958233346453248
572019-10-313227006954334101213329918851157595708
582019-11-3036426841568263807651347384179341301
592019-12-31370682641445471331441611131298