Overview

Dataset statistics

Number of variables14
Number of observations36
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory4.5 KiB
Average record size in memory127.7 B

Variable types

Categorical2
Numeric12

Dataset

Description함안지방공사에서 운영하는 체육시설인 함안체육관 및 칠원국민체육센터의 군민 이용 현황 정보제공 (수영장 과 헬스장을 이용한 월간 이용객수)
URLhttps://www.data.go.kr/data/15010457/fileData.do

Alerts

수영회원 is highly overall correlated with 수영일일 and 11 other fieldsHigh correlation
수영일일 is highly overall correlated with 수영회원 and 11 other fieldsHigh correlation
수영소계 is highly overall correlated with 수영회원 and 11 other fieldsHigh correlation
수영일평균 is highly overall correlated with 수영회원 and 11 other fieldsHigh correlation
헬스회원 is highly overall correlated with 수영회원 and 11 other fieldsHigh correlation
헬스일일 is highly overall correlated with 수영회원 and 10 other fieldsHigh correlation
헬스소계 is highly overall correlated with 수영회원 and 10 other fieldsHigh correlation
헬스일평균 is highly overall correlated with 수영회원 and 11 other fieldsHigh correlation
그룹운동(GX)인원 is highly overall correlated with 수영회원 and 10 other fieldsHigh correlation
그룹운동(GX)일평균 is highly overall correlated with 수영회원 and 10 other fieldsHigh correlation
is highly overall correlated with 수영회원 and 11 other fieldsHigh correlation
일평균 is highly overall correlated with 수영회원 and 11 other fieldsHigh correlation
연도 is highly overall correlated with 수영회원 and 7 other fieldsHigh correlation
수영회원 has 14 (38.9%) zerosZeros
수영일일 has 14 (38.9%) zerosZeros
수영소계 has 14 (38.9%) zerosZeros
수영일평균 has 14 (38.9%) zerosZeros
헬스회원 has 14 (38.9%) zerosZeros
헬스일일 has 21 (58.3%) zerosZeros
헬스소계 has 13 (36.1%) zerosZeros
헬스일평균 has 13 (36.1%) zerosZeros
그룹운동(GX)인원 has 29 (80.6%) zerosZeros
그룹운동(GX)일평균 has 29 (80.6%) zerosZeros
has 13 (36.1%) zerosZeros
일평균 has 13 (36.1%) zerosZeros

Reproduction

Analysis started2023-12-12 03:30:47.941183
Analysis finished2023-12-12 03:31:06.548031
Duration18.61 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

연도
Categorical

HIGH CORRELATION 

Distinct3
Distinct (%)8.3%
Missing0
Missing (%)0.0%
Memory size420.0 B
2020년
12 
2021년
12 
2022년
12 

Length

Max length5
Median length5
Mean length5
Min length5

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2020년
2nd row2020년
3rd row2020년
4th row2020년
5th row2020년

Common Values

ValueCountFrequency (%)
2020년 12
33.3%
2021년 12
33.3%
2022년 12
33.3%

Length

2023-12-12T12:31:06.643677image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T12:31:06.797999image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2020년 12
33.3%
2021년 12
33.3%
2022년 12
33.3%


Categorical

Distinct12
Distinct (%)33.3%
Missing0
Missing (%)0.0%
Memory size420.0 B
1월
2월
3월
4월
5월
Other values (7)
21 

Length

Max length3
Median length2
Mean length2.25
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row1월
2nd row2월
3rd row3월
4th row4월
5th row5월

Common Values

ValueCountFrequency (%)
1월 3
8.3%
2월 3
8.3%
3월 3
8.3%
4월 3
8.3%
5월 3
8.3%
6월 3
8.3%
7월 3
8.3%
8월 3
8.3%
9월 3
8.3%
10월 3
8.3%
Other values (2) 6
16.7%

Length

2023-12-12T12:31:06.976222image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
1월 3
8.3%
2월 3
8.3%
3월 3
8.3%
4월 3
8.3%
5월 3
8.3%
6월 3
8.3%
7월 3
8.3%
8월 3
8.3%
9월 3
8.3%
10월 3
8.3%
Other values (2) 6
16.7%

수영회원
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct23
Distinct (%)63.9%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2009.2222
Minimum0
Maximum7069
Zeros14
Zeros (%)38.9%
Negative0
Negative (%)0.0%
Memory size456.0 B
2023-12-12T12:31:07.161195image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median1852
Q33093.25
95-th percentile5496.25
Maximum7069
Range7069
Interquartile range (IQR)3093.25

Descriptive statistics

Standard deviation2100.4869
Coefficient of variation (CV)1.0454229
Kurtosis-0.66479721
Mean2009.2222
Median Absolute Deviation (MAD)1852
Skewness0.68107235
Sum72332
Variance4412045.4
MonotonicityNot monotonic
2023-12-12T12:31:07.344003image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=23)
ValueCountFrequency (%)
0 14
38.9%
7069 1
 
2.8%
2240 1
 
2.8%
4665 1
 
2.8%
4834 1
 
2.8%
4449 1
 
2.8%
4240 1
 
2.8%
5476 1
 
2.8%
5557 1
 
2.8%
4357 1
 
2.8%
Other values (13) 13
36.1%
ValueCountFrequency (%)
0 14
38.9%
315 1
 
2.8%
1089 1
 
2.8%
1471 1
 
2.8%
1578 1
 
2.8%
2126 1
 
2.8%
2240 1
 
2.8%
2289 1
 
2.8%
2305 1
 
2.8%
2538 1
 
2.8%
ValueCountFrequency (%)
7069 1
2.8%
5557 1
2.8%
5476 1
2.8%
5155 1
2.8%
4834 1
2.8%
4665 1
2.8%
4449 1
2.8%
4357 1
2.8%
4240 1
2.8%
2711 1
2.8%

수영일일
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct22
Distinct (%)61.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean209.44444
Minimum0
Maximum721
Zeros14
Zeros (%)38.9%
Negative0
Negative (%)0.0%
Memory size456.0 B
2023-12-12T12:31:07.523766image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median121.5
Q3342.25
95-th percentile684
Maximum721
Range721
Interquartile range (IQR)342.25

Descriptive statistics

Standard deviation243.18793
Coefficient of variation (CV)1.1611095
Kurtosis-0.53529297
Mean209.44444
Median Absolute Deviation (MAD)121.5
Skewness0.91436603
Sum7540
Variance59140.368
MonotonicityNot monotonic
2023-12-12T12:31:07.680120image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=22)
ValueCountFrequency (%)
0 14
38.9%
191 2
 
5.6%
488 1
 
2.8%
306 1
 
2.8%
471 1
 
2.8%
451 1
 
2.8%
673 1
 
2.8%
547 1
 
2.8%
606 1
 
2.8%
721 1
 
2.8%
Other values (12) 12
33.3%
ValueCountFrequency (%)
0 14
38.9%
21 1
 
2.8%
85 1
 
2.8%
88 1
 
2.8%
114 1
 
2.8%
129 1
 
2.8%
191 2
 
5.6%
193 1
 
2.8%
199 1
 
2.8%
212 1
 
2.8%
ValueCountFrequency (%)
721 1
2.8%
717 1
2.8%
673 1
2.8%
606 1
2.8%
589 1
2.8%
547 1
2.8%
488 1
2.8%
471 1
2.8%
451 1
2.8%
306 1
2.8%

수영소계
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct23
Distinct (%)63.9%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2218.6667
Minimum0
Maximum7557
Zeros14
Zeros (%)38.9%
Negative0
Negative (%)0.0%
Memory size456.0 B
2023-12-12T12:31:07.859325image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median2004.5
Q33671.75
95-th percentile6131
Maximum7557
Range7557
Interquartile range (IQR)3671.75

Descriptive statistics

Standard deviation2321.2915
Coefficient of variation (CV)1.0462552
Kurtosis-0.80599541
Mean2218.6667
Median Absolute Deviation (MAD)2004.5
Skewness0.6533641
Sum79872
Variance5388394.5
MonotonicityNot monotonic
2023-12-12T12:31:08.011302image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=23)
ValueCountFrequency (%)
0 14
38.9%
7557 1
 
2.8%
2433 1
 
2.8%
5136 1
 
2.8%
5285 1
 
2.8%
5122 1
 
2.8%
4787 1
 
2.8%
6082 1
 
2.8%
6278 1
 
2.8%
5074 1
 
2.8%
Other values (13) 13
36.1%
ValueCountFrequency (%)
0 14
38.9%
336 1
 
2.8%
1177 1
 
2.8%
1556 1
 
2.8%
1692 1
 
2.8%
2317 1
 
2.8%
2418 1
 
2.8%
2433 1
 
2.8%
2611 1
 
2.8%
2781 1
 
2.8%
ValueCountFrequency (%)
7557 1
2.8%
6278 1
2.8%
6082 1
2.8%
5460 1
2.8%
5285 1
2.8%
5136 1
2.8%
5122 1
2.8%
5074 1
2.8%
4787 1
2.8%
3300 1
2.8%

수영일평균
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct22
Distinct (%)61.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean93.972222
Minimum0
Maximum329
Zeros14
Zeros (%)38.9%
Negative0
Negative (%)0.0%
Memory size456.0 B
2023-12-12T12:31:08.154140image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median88
Q3142.75
95-th percentile261
Maximum329
Range329
Interquartile range (IQR)142.75

Descriptive statistics

Standard deviation96.65387
Coefficient of variation (CV)1.0285366
Kurtosis-0.09797413
Mean93.972222
Median Absolute Deviation (MAD)88
Skewness0.81492127
Sum3383
Variance9341.9706
MonotonicityNot monotonic
2023-12-12T12:31:08.324970image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=22)
ValueCountFrequency (%)
0 14
38.9%
110 2
 
5.6%
329 1
 
2.8%
100 1
 
2.8%
190 1
 
2.8%
203 1
 
2.8%
197 1
 
2.8%
208 1
 
2.8%
225 1
 
2.8%
241 1
 
2.8%
Other values (12) 12
33.3%
ValueCountFrequency (%)
0 14
38.9%
77 1
 
2.8%
78 1
 
2.8%
84 1
 
2.8%
86 1
 
2.8%
90 1
 
2.8%
93 1
 
2.8%
100 1
 
2.8%
103 1
 
2.8%
107 1
 
2.8%
ValueCountFrequency (%)
329 1
2.8%
321 1
2.8%
241 1
2.8%
225 1
2.8%
208 1
2.8%
203 1
2.8%
197 1
2.8%
195 1
2.8%
190 1
2.8%
127 1
2.8%

헬스회원
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct22
Distinct (%)61.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1327.3611
Minimum0
Maximum4049
Zeros14
Zeros (%)38.9%
Negative0
Negative (%)0.0%
Memory size456.0 B
2023-12-12T12:31:08.495195image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median1559.5
Q32357
95-th percentile3002.75
Maximum4049
Range4049
Interquartile range (IQR)2357

Descriptive statistics

Standard deviation1236.7931
Coefficient of variation (CV)0.93176836
Kurtosis-1.3314923
Mean1327.3611
Median Absolute Deviation (MAD)1238.5
Skewness0.18591679
Sum47785
Variance1529657.2
MonotonicityNot monotonic
2023-12-12T12:31:08.652244image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=22)
ValueCountFrequency (%)
0 14
38.9%
2049 2
 
5.6%
4049 1
 
2.8%
1390 1
 
2.8%
3098 1
 
2.8%
2798 1
 
2.8%
2520 1
 
2.8%
2248 1
 
2.8%
2369 1
 
2.8%
2601 1
 
2.8%
Other values (12) 12
33.3%
ValueCountFrequency (%)
0 14
38.9%
321 1
 
2.8%
750 1
 
2.8%
1254 1
 
2.8%
1390 1
 
2.8%
1729 1
 
2.8%
1838 1
 
2.8%
2049 2
 
5.6%
2052 1
 
2.8%
2248 1
 
2.8%
ValueCountFrequency (%)
4049 1
2.8%
3098 1
2.8%
2971 1
2.8%
2798 1
2.8%
2601 1
2.8%
2520 1
2.8%
2407 1
2.8%
2398 1
2.8%
2369 1
2.8%
2353 1
2.8%

헬스일일
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct15
Distinct (%)41.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean49.388889
Minimum0
Maximum267
Zeros21
Zeros (%)58.3%
Negative0
Negative (%)0.0%
Memory size456.0 B
2023-12-12T12:31:08.811105image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q3109.5
95-th percentile187.5
Maximum267
Range267
Interquartile range (IQR)109.5

Descriptive statistics

Standard deviation76.5093
Coefficient of variation (CV)1.5491197
Kurtosis0.7524984
Mean49.388889
Median Absolute Deviation (MAD)0
Skewness1.3373139
Sum1778
Variance5853.673
MonotonicityNot monotonic
2023-12-12T12:31:08.970818image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=15)
ValueCountFrequency (%)
0 21
58.3%
133 2
 
5.6%
267 1
 
2.8%
228 1
 
2.8%
163 1
 
2.8%
1 1
 
2.8%
6 1
 
2.8%
8 1
 
2.8%
79 1
 
2.8%
85 1
 
2.8%
Other values (5) 5
 
13.9%
ValueCountFrequency (%)
0 21
58.3%
1 1
 
2.8%
6 1
 
2.8%
8 1
 
2.8%
79 1
 
2.8%
85 1
 
2.8%
106 1
 
2.8%
120 1
 
2.8%
128 1
 
2.8%
133 2
 
5.6%
ValueCountFrequency (%)
267 1
2.8%
228 1
2.8%
174 1
2.8%
163 1
2.8%
147 1
2.8%
133 2
5.6%
128 1
2.8%
120 1
2.8%
106 1
2.8%
85 1
2.8%

헬스소계
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct24
Distinct (%)66.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1376.75
Minimum0
Maximum4316
Zeros13
Zeros (%)36.1%
Negative0
Negative (%)0.0%
Memory size456.0 B
2023-12-12T12:31:09.140817image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median1559.5
Q32406.5
95-th percentile3217.25
Maximum4316
Range4316
Interquartile range (IQR)2406.5

Descriptive statistics

Standard deviation1288.8667
Coefficient of variation (CV)0.93616612
Kurtosis-1.1968433
Mean1376.75
Median Absolute Deviation (MAD)1302.5
Skewness0.25469857
Sum49563
Variance1661177.4
MonotonicityNot monotonic
2023-12-12T12:31:09.336008image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=24)
ValueCountFrequency (%)
0 13
36.1%
4316 1
 
2.8%
1390 1
 
2.8%
3272 1
 
2.8%
2926 1
 
2.8%
2626 1
 
2.8%
2381 1
 
2.8%
2489 1
 
2.8%
2748 1
 
2.8%
2483 1
 
2.8%
Other values (14) 14
38.9%
ValueCountFrequency (%)
0 13
36.1%
163 1
 
2.8%
321 1
 
2.8%
750 1
 
2.8%
1254 1
 
2.8%
1390 1
 
2.8%
1729 1
 
2.8%
1971 1
 
2.8%
2049 1
 
2.8%
2052 1
 
2.8%
ValueCountFrequency (%)
4316 1
2.8%
3272 1
2.8%
3199 1
2.8%
2926 1
2.8%
2748 1
2.8%
2626 1
2.8%
2489 1
2.8%
2486 1
2.8%
2483 1
2.8%
2381 1
2.8%

헬스일평균
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct21
Distinct (%)58.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean59.722222
Minimum0
Maximum188
Zeros13
Zeros (%)36.1%
Negative0
Negative (%)0.0%
Memory size456.0 B
2023-12-12T12:31:09.503360image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median74.5
Q393
95-th percentile137.75
Maximum188
Range188
Interquartile range (IQR)93

Descriptive statistics

Standard deviation53.78455
Coefficient of variation (CV)0.90057851
Kurtosis-0.23913351
Mean59.722222
Median Absolute Deviation (MAD)35
Skewness0.44686536
Sum2150
Variance2892.7778
MonotonicityNot monotonic
2023-12-12T12:31:10.043405image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=21)
ValueCountFrequency (%)
0 13
36.1%
188 2
 
5.6%
96 2
 
5.6%
79 2
 
5.6%
63 1
 
2.8%
121 1
 
2.8%
113 1
 
2.8%
101 1
 
2.8%
104 1
 
2.8%
92 1
 
2.8%
Other values (11) 11
30.6%
ValueCountFrequency (%)
0 13
36.1%
27 1
 
2.8%
50 1
 
2.8%
63 1
 
2.8%
70 1
 
2.8%
73 1
 
2.8%
76 1
 
2.8%
79 2
 
5.6%
80 1
 
2.8%
82 1
 
2.8%
ValueCountFrequency (%)
188 2
5.6%
121 1
2.8%
113 1
2.8%
106 1
2.8%
104 1
2.8%
101 1
2.8%
96 2
5.6%
92 1
2.8%
91 1
2.8%
88 1
2.8%

그룹운동(GX)인원
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct8
Distinct (%)22.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean114.08333
Minimum0
Maximum1224
Zeros29
Zeros (%)80.6%
Negative0
Negative (%)0.0%
Memory size456.0 B
2023-12-12T12:31:10.199515image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile649.75
Maximum1224
Range1224
Interquartile range (IQR)0

Descriptive statistics

Standard deviation283.05733
Coefficient of variation (CV)2.4811453
Kurtosis7.3012959
Mean114.08333
Median Absolute Deviation (MAD)0
Skewness2.7173368
Sum4107
Variance80121.45
MonotonicityNot monotonic
2023-12-12T12:31:10.354020image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=8)
ValueCountFrequency (%)
0 29
80.6%
1224 1
 
2.8%
907 1
 
2.8%
35 1
 
2.8%
450 1
 
2.8%
564 1
 
2.8%
479 1
 
2.8%
448 1
 
2.8%
ValueCountFrequency (%)
0 29
80.6%
35 1
 
2.8%
448 1
 
2.8%
450 1
 
2.8%
479 1
 
2.8%
564 1
 
2.8%
907 1
 
2.8%
1224 1
 
2.8%
ValueCountFrequency (%)
1224 1
 
2.8%
907 1
 
2.8%
564 1
 
2.8%
479 1
 
2.8%
450 1
 
2.8%
448 1
 
2.8%
35 1
 
2.8%
0 29
80.6%

그룹운동(GX)일평균
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct7
Distinct (%)19.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean5.1111111
Minimum0
Maximum53
Zeros29
Zeros (%)80.6%
Negative0
Negative (%)0.0%
Memory size456.0 B
2023-12-12T12:31:10.572948image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile29.75
Maximum53
Range53
Interquartile range (IQR)0

Descriptive statistics

Standard deviation13.283239
Coefficient of variation (CV)2.5988946
Kurtosis8.4007963
Mean5.1111111
Median Absolute Deviation (MAD)0
Skewness2.9383947
Sum184
Variance176.44444
MonotonicityNot monotonic
2023-12-12T12:31:10.698037image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=7)
ValueCountFrequency (%)
0 29
80.6%
53 2
 
5.6%
1 1
 
2.8%
20 1
 
2.8%
22 1
 
2.8%
18 1
 
2.8%
17 1
 
2.8%
ValueCountFrequency (%)
0 29
80.6%
1 1
 
2.8%
17 1
 
2.8%
18 1
 
2.8%
20 1
 
2.8%
22 1
 
2.8%
53 2
 
5.6%
ValueCountFrequency (%)
53 2
 
5.6%
22 1
 
2.8%
20 1
 
2.8%
18 1
 
2.8%
17 1
 
2.8%
1 1
 
2.8%
0 29
80.6%


Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct24
Distinct (%)66.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean3709.5
Minimum0
Maximum13097
Zeros13
Zeros (%)36.1%
Negative0
Negative (%)0.0%
Memory size456.0 B
2023-12-12T12:31:10.879358image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median3564
Q36228.75
95-th percentile9187.25
Maximum13097
Range13097
Interquartile range (IQR)6228.75

Descriptive statistics

Standard deviation3764.5829
Coefficient of variation (CV)1.0148491
Kurtosis-0.69322557
Mean3709.5
Median Absolute Deviation (MAD)3564
Skewness0.59394522
Sum133542
Variance14172084
MonotonicityNot monotonic
2023-12-12T12:31:11.075534image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=24)
ValueCountFrequency (%)
0 13
36.1%
13097 1
 
2.8%
3082 1
 
2.8%
8856 1
 
2.8%
8690 1
 
2.8%
8312 1
 
2.8%
7618 1
 
2.8%
8571 1
 
2.8%
9061 1
 
2.8%
7557 1
 
2.8%
Other values (14) 14
38.9%
ValueCountFrequency (%)
0 13
36.1%
163 1
 
2.8%
657 1
 
2.8%
1927 1
 
2.8%
2810 1
 
2.8%
3082 1
 
2.8%
4046 1
 
2.8%
4470 1
 
2.8%
4482 1
 
2.8%
4668 1
 
2.8%
ValueCountFrequency (%)
13097 1
2.8%
9566 1
2.8%
9061 1
2.8%
8856 1
2.8%
8690 1
2.8%
8571 1
2.8%
8312 1
2.8%
7618 1
2.8%
7557 1
2.8%
5786 1
2.8%

일평균
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct23
Distinct (%)63.9%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean158.83333
Minimum0
Maximum569
Zeros13
Zeros (%)36.1%
Negative0
Negative (%)0.0%
Memory size456.0 B
2023-12-12T12:31:11.250937image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median165
Q3240
95-th percentile402.5
Maximum569
Range569
Interquartile range (IQR)240

Descriptive statistics

Standard deviation158.78692
Coefficient of variation (CV)0.99970778
Kurtosis0.41372552
Mean158.83333
Median Absolute Deviation (MAD)164
Skewness0.85948667
Sum5718
Variance25213.286
MonotonicityNot monotonic
2023-12-12T12:31:11.406083image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=23)
ValueCountFrequency (%)
0 13
36.1%
196 2
 
5.6%
569 1
 
2.8%
166 1
 
2.8%
328 1
 
2.8%
334 1
 
2.8%
320 1
 
2.8%
331 1
 
2.8%
317 1
 
2.8%
349 1
 
2.8%
Other values (13) 13
36.1%
ValueCountFrequency (%)
0 13
36.1%
27 1
 
2.8%
128 1
 
2.8%
140 1
 
2.8%
156 1
 
2.8%
164 1
 
2.8%
166 1
 
2.8%
172 1
 
2.8%
176 1
 
2.8%
180 1
 
2.8%
ValueCountFrequency (%)
569 1
2.8%
563 1
2.8%
349 1
2.8%
334 1
2.8%
331 1
2.8%
328 1
2.8%
320 1
2.8%
317 1
2.8%
291 1
2.8%
223 1
2.8%

Interactions

2023-12-12T12:31:04.636847image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T12:30:48.682489image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T12:30:50.299243image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T12:30:51.723910image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T12:30:53.109605image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T12:30:54.539854image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T12:30:56.023456image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T12:30:57.267596image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T12:30:58.605495image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T12:30:59.988293image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T12:31:01.648679image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T12:31:03.380779image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T12:31:04.763269image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T12:30:48.819021image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T12:30:50.429088image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T12:30:51.830498image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T12:30:53.238288image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T12:30:54.644667image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T12:30:56.114626image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T12:30:57.365396image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T12:30:58.733353image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T12:31:00.112854image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T12:31:01.791487image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T12:31:03.479205image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T12:31:04.878885image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T12:30:48.964633image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T12:30:50.558419image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T12:30:51.958154image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T12:30:53.379223image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T12:30:54.742480image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T12:30:56.207875image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T12:30:57.468252image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T12:30:58.867474image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T12:31:00.234530image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T12:31:01.900820image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T12:31:03.588788image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T12:31:04.997223image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T12:30:49.115476image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T12:30:50.707344image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T12:30:52.072900image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T12:30:53.501938image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T12:30:55.182163image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T12:30:56.303051image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T12:30:57.586228image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T12:30:58.987495image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T12:31:00.392781image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T12:31:02.038694image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T12:31:03.702421image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T12:31:05.101686image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T12:30:49.261653image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T12:30:50.824369image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T12:30:52.217942image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T12:30:53.625767image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T12:30:55.273040image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T12:30:56.402420image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T12:30:57.689751image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T12:30:59.092884image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T12:31:00.518656image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T12:31:02.144802image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T12:31:03.803690image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T12:31:05.238623image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T12:30:49.407220image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T12:30:50.959612image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T12:30:52.334124image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T12:30:53.765157image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T12:30:55.378315image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T12:30:56.500399image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T12:30:57.827746image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T12:30:59.220747image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T12:31:00.664940image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T12:31:02.282063image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T12:31:03.917416image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T12:31:05.361980image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T12:30:49.543840image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T12:30:51.060933image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T12:30:52.432730image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T12:30:53.881853image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T12:30:55.468473image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T12:30:56.587070image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T12:30:57.952144image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T12:30:59.311167image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T12:31:00.780371image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T12:31:02.739251image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T12:31:04.015512image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T12:31:05.468684image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T12:30:49.651945image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T12:30:51.168346image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T12:30:52.521752image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T12:30:53.979242image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T12:30:55.555007image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T12:30:56.681288image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T12:30:58.055980image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T12:30:59.412171image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T12:31:00.906045image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T12:31:02.832841image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T12:31:04.094412image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T12:31:05.606678image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T12:30:49.778316image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T12:30:51.294915image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T12:30:52.631615image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T12:30:54.098791image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T12:30:55.648224image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T12:30:56.780920image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T12:30:58.179239image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T12:30:59.533760image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T12:31:01.053700image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T12:31:02.959649image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T12:31:04.217530image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T12:31:05.731948image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T12:30:49.894683image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T12:30:51.395481image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T12:30:52.748858image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T12:30:54.200541image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T12:30:55.736200image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T12:30:56.969441image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T12:30:58.292728image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T12:30:59.648318image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T12:31:01.202921image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T12:31:03.078273image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T12:31:04.318686image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T12:31:05.830170image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T12:30:50.044892image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T12:30:51.491627image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T12:30:52.869891image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T12:30:54.302058image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T12:30:55.826591image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T12:30:57.066873image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T12:30:58.397922image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T12:30:59.746205image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T12:31:01.344712image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T12:31:03.188984image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T12:31:04.434186image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T12:31:05.936654image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T12:30:50.178859image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T12:30:51.598368image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T12:30:52.990798image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T12:30:54.425722image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T12:30:55.932961image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T12:30:57.163332image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T12:30:58.506705image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T12:30:59.880667image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T12:31:01.493181image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T12:31:03.287475image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T12:31:04.544839image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-12T12:31:11.550074image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연도수영회원수영일일수영소계수영일평균헬스회원헬스일일헬스소계헬스일평균그룹운동(GX)인원그룹운동(GX)일평균일평균
연도1.0000.0000.7230.8530.9320.7260.7070.4350.8180.7810.3410.3320.9320.930
0.0001.0000.0000.0000.0000.0000.0000.0000.1130.0000.0000.0000.0000.000
수영회원0.7230.0001.0000.8700.9680.8720.9790.8850.9190.9590.8040.9160.9580.896
수영일일0.8530.0000.8701.0000.9410.8360.8150.7910.8910.8310.7600.7500.9480.842
수영소계0.9320.0000.9680.9411.0000.8820.9280.8920.9750.9000.8920.8190.9980.965
수영일평균0.7260.0000.8720.8360.8821.0000.7910.8820.7860.8080.7370.8240.8430.977
헬스회원0.7070.0000.9790.8150.9280.7911.0000.8650.9770.9600.7860.8760.9400.843
헬스일일0.4350.0000.8850.7910.8920.8820.8651.0000.7050.8870.8950.9640.8680.851
헬스소계0.8180.1130.9190.8910.9750.7860.9770.7051.0000.8690.8000.7090.9810.880
헬스일평균0.7810.0000.9590.8310.9000.8080.9600.8870.8691.0000.7490.9600.9040.861
그룹운동(GX)인원0.3410.0000.8040.7600.8920.7370.7860.8950.8000.7491.0001.0000.8700.693
그룹운동(GX)일평균0.3320.0000.9160.7500.8190.8240.8760.9640.7090.9601.0001.0000.7730.827
0.9320.0000.9580.9480.9980.8430.9400.8680.9810.9040.8700.7731.0000.940
일평균0.9300.0000.8960.8420.9650.9770.8430.8510.8800.8610.6930.8270.9401.000
2023-12-12T12:31:11.728453image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연도
연도1.0000.000
0.0001.000
2023-12-12T12:31:11.872805image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
수영회원수영일일수영소계수영일평균헬스회원헬스일일헬스소계헬스일평균그룹운동(GX)인원그룹운동(GX)일평균일평균연도
수영회원1.0000.9651.0000.9870.9840.7740.9850.9680.6630.6610.9910.9820.5640.000
수영일일0.9651.0000.9660.9560.9430.7380.9460.9280.5760.5760.9520.9460.5110.000
수영소계1.0000.9661.0000.9870.9840.7740.9840.9680.6630.6610.9910.9820.6250.000
수영일평균0.9870.9560.9871.0000.9660.7590.9690.9740.6740.6740.9790.9870.6060.000
헬스회원0.9840.9430.9840.9661.0000.7430.9910.9740.6670.6630.9830.9740.5450.000
헬스일일0.7740.7380.7740.7590.7431.0000.7980.7810.7080.7090.8160.8030.2740.000
헬스소계0.9850.9460.9840.9690.9910.7981.0000.9840.6820.6790.9950.9880.4710.000
헬스일평균0.9680.9280.9680.9740.9740.7810.9841.0000.7020.7010.9820.9930.6390.000
그룹운동(GX)인원0.6630.5760.6630.6740.6670.7080.6820.7021.0000.9990.6880.7020.2590.000
그룹운동(GX)일평균0.6610.5760.6610.6740.6630.7090.6790.7010.9991.0000.6860.7010.3120.000
0.9910.9520.9910.9790.9830.8160.9950.9820.6880.6861.0000.9920.6250.000
일평균0.9820.9460.9820.9870.9740.8030.9880.9930.7020.7010.9921.0000.6460.000
연도0.5640.5110.6250.6060.5450.2740.4710.6390.2590.3120.6250.6461.0000.000
0.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0001.000

Missing values

2023-12-12T12:31:06.202511image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-12T12:31:06.454912image/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

연도수영회원수영일일수영소계수영일평균헬스회원헬스일일헬스소계헬스일평균그룹운동(GX)인원그룹운동(GX)일평균일평균
02020년1월706948875573294049267431618812245313097569
12020년2월5155305546032129712283199188907539566563
22020년3월000000000000
32020년4월000000000000
42020년5월000000000000
52020년6월000000000000
62020년7월000000000000
72020년8월000000000000
82020년9월000000000000
92020년10월000000000000
연도수영회원수영일일수영소계수영일평균헬스회원헬스일일헬스소계헬스일평균그룹운동(GX)인원그룹운동(GX)일평균일평균
262022년3월224019324339020490204976004482166
272022년4월2305306261110020498205779004668180
282022년5월27115893300127240779248696005786223
292022년6월43577175074195239885248396007557291
302022년7월55577216278241260114727481063519061349
312022년8월547660660822252369120248992008571317
322022년9월4240547478720822481332381104450207618331
332022년10월4449673512219725201062626101564228312320
342022년11월4834451528520327981282926113479188690334
352022년12월4665471513619030981743272121448178856328