Overview

Dataset statistics

Number of variables14
Number of observations28
Missing cells1
Missing cells (%)0.3%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory3.5 KiB
Average record size in memory128.6 B

Variable types

DateTime1
Numeric12
Categorical1

Dataset

Description2021년 이후 방위사업청 사무용 전산장비 사용현황을 파악하기 위하여 PC 정비 요청처리 기간, 각 장애 유형별 건수와 만족도,만족도 점수 합의 정보를 제공함
Author방위사업청
URLhttps://www.data.go.kr/data/15038441/fileData.do

Alerts

컴퓨터(PC) 장애 is highly overall correlated with 변경설치 and 4 other fieldsHigh correlation
기타문의 is highly overall correlated with 컴퓨터(PC)정비 요청처리 만족도 회신 건수 and 1 other fieldsHigh correlation
변경설치 is highly overall correlated with 컴퓨터(PC) 장애 and 4 other fieldsHigh correlation
신규설치 is highly overall correlated with 컴퓨터(PC) 장애 and 4 other fieldsHigh correlation
프린터 장애 is highly overall correlated with 컴퓨터(PC)정비 요청처리 완료건수High correlation
컴퓨터(PC)정비 요청처리 완료건수 is highly overall correlated with 컴퓨터(PC) 장애 and 5 other fieldsHigh correlation
컴퓨터(PC)정비 요청처리 만족도 회신 건수 is highly overall correlated with 컴퓨터(PC) 장애 and 5 other fieldsHigh correlation
컴퓨터(PC)정비 요청처리만족도 점수 합 is highly overall correlated with 컴퓨터(PC) 장애 and 5 other fieldsHigh correlation
변경설치 has 1 (3.6%) missing valuesMissing
기간 has unique valuesUnique
컴퓨터(PC)정비 요청처리만족도 점수 합 has unique valuesUnique

Reproduction

Analysis started2024-03-15 00:28:53.300260
Analysis finished2024-03-15 00:29:30.061424
Duration36.76 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

기간
Date

UNIQUE 

Distinct28
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size352.0 B
Minimum2024-01-22 00:00:00
Maximum2024-12-22 00:00:00
2024-03-15T09:29:30.355131image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T09:29:30.850461image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=28)

컴퓨터(PC) 장애
Real number (ℝ)

HIGH CORRELATION 

Distinct24
Distinct (%)85.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean132.64286
Minimum77
Maximum197
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size380.0 B
2024-03-15T09:29:31.145529image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum77
5-th percentile95.1
Q1113.5
median130.5
Q3147
95-th percentile185.85
Maximum197
Range120
Interquartile range (IQR)33.5

Descriptive statistics

Standard deviation29.46588
Coefficient of variation (CV)0.22214449
Kurtosis-0.012776286
Mean132.64286
Median Absolute Deviation (MAD)18.5
Skewness0.45423533
Sum3714
Variance868.2381
MonotonicityNot monotonic
2024-03-15T09:29:31.377802image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=24)
ValueCountFrequency (%)
167 2
 
7.1%
133 2
 
7.1%
128 2
 
7.1%
101 2
 
7.1%
117 1
 
3.6%
196 1
 
3.6%
93 1
 
3.6%
109 1
 
3.6%
137 1
 
3.6%
99 1
 
3.6%
Other values (14) 14
50.0%
ValueCountFrequency (%)
77 1
3.6%
93 1
3.6%
99 1
3.6%
101 2
7.1%
105 1
3.6%
109 1
3.6%
115 1
3.6%
117 1
3.6%
119 1
3.6%
121 1
3.6%
ValueCountFrequency (%)
197 1
3.6%
196 1
3.6%
167 2
7.1%
163 1
3.6%
162 1
3.6%
159 1
3.6%
143 1
3.6%
142 1
3.6%
140 1
3.6%
139 1
3.6%

기타 장애
Real number (ℝ)

Distinct12
Distinct (%)42.9%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean14.571429
Minimum9
Maximum22
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size380.0 B
2024-03-15T09:29:31.718592image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum9
5-th percentile9.35
Q112.75
median14
Q317
95-th percentile21
Maximum22
Range13
Interquartile range (IQR)4.25

Descriptive statistics

Standard deviation3.4364988
Coefficient of variation (CV)0.23583815
Kurtosis-0.1060674
Mean14.571429
Median Absolute Deviation (MAD)2
Skewness0.40508077
Sum408
Variance11.809524
MonotonicityNot monotonic
2024-03-15T09:29:32.300110image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=12)
ValueCountFrequency (%)
17 4
14.3%
14 4
14.3%
13 4
14.3%
15 3
10.7%
16 2
7.1%
12 2
7.1%
21 2
7.1%
9 2
7.1%
10 2
7.1%
22 1
 
3.6%
Other values (2) 2
7.1%
ValueCountFrequency (%)
9 2
7.1%
10 2
7.1%
11 1
 
3.6%
12 2
7.1%
13 4
14.3%
14 4
14.3%
15 3
10.7%
16 2
7.1%
17 4
14.3%
18 1
 
3.6%
ValueCountFrequency (%)
22 1
 
3.6%
21 2
7.1%
18 1
 
3.6%
17 4
14.3%
16 2
7.1%
15 3
10.7%
14 4
14.3%
13 4
14.3%
12 2
7.1%
11 1
 
3.6%

기타문의
Real number (ℝ)

HIGH CORRELATION 

Distinct11
Distinct (%)39.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean6.4642857
Minimum1
Maximum14
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size380.0 B
2024-03-15T09:29:32.638999image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile3
Q13
median5
Q38
95-th percentile14
Maximum14
Range13
Interquartile range (IQR)5

Descriptive statistics

Standard deviation3.9579469
Coefficient of variation (CV)0.61227908
Kurtosis-0.54088998
Mean6.4642857
Median Absolute Deviation (MAD)2
Skewness0.83954591
Sum181
Variance15.665344
MonotonicityNot monotonic
2024-03-15T09:29:33.038490image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=11)
ValueCountFrequency (%)
3 7
25.0%
4 5
17.9%
8 4
14.3%
14 3
10.7%
5 2
 
7.1%
6 2
 
7.1%
13 1
 
3.6%
12 1
 
3.6%
7 1
 
3.6%
11 1
 
3.6%
ValueCountFrequency (%)
1 1
 
3.6%
3 7
25.0%
4 5
17.9%
5 2
 
7.1%
6 2
 
7.1%
7 1
 
3.6%
8 4
14.3%
11 1
 
3.6%
12 1
 
3.6%
13 1
 
3.6%
ValueCountFrequency (%)
14 3
10.7%
13 1
 
3.6%
12 1
 
3.6%
11 1
 
3.6%
8 4
14.3%
7 1
 
3.6%
6 2
 
7.1%
5 2
 
7.1%
4 5
17.9%
3 7
25.0%

변경설치
Real number (ℝ)

HIGH CORRELATION  MISSING 

Distinct11
Distinct (%)40.7%
Missing1
Missing (%)3.6%
Infinite0
Infinite (%)0.0%
Mean6.2222222
Minimum2
Maximum16
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size380.0 B
2024-03-15T09:29:33.347980image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum2
5-th percentile2
Q13
median6
Q38
95-th percentile13.1
Maximum16
Range14
Interquartile range (IQR)5

Descriptive statistics

Standard deviation3.7757662
Coefficient of variation (CV)0.60681956
Kurtosis0.41070506
Mean6.2222222
Median Absolute Deviation (MAD)3
Skewness0.9064052
Sum168
Variance14.25641
MonotonicityNot monotonic
2024-03-15T09:29:33.665291image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=11)
ValueCountFrequency (%)
3 6
21.4%
2 4
14.3%
7 4
14.3%
10 3
10.7%
6 3
10.7%
8 2
 
7.1%
11 1
 
3.6%
14 1
 
3.6%
16 1
 
3.6%
5 1
 
3.6%
ValueCountFrequency (%)
2 4
14.3%
3 6
21.4%
4 1
 
3.6%
5 1
 
3.6%
6 3
10.7%
7 4
14.3%
8 2
 
7.1%
10 3
10.7%
11 1
 
3.6%
14 1
 
3.6%
ValueCountFrequency (%)
16 1
 
3.6%
14 1
 
3.6%
11 1
 
3.6%
10 3
10.7%
8 2
 
7.1%
7 4
14.3%
6 3
10.7%
5 1
 
3.6%
4 1
 
3.6%
3 6
21.4%

신규설치
Real number (ℝ)

HIGH CORRELATION 

Distinct11
Distinct (%)39.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean5.25
Minimum1
Maximum15
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size380.0 B
2024-03-15T09:29:34.014930image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q12
median4.5
Q38
95-th percentile11.6
Maximum15
Range14
Interquartile range (IQR)6

Descriptive statistics

Standard deviation3.6679291
Coefficient of variation (CV)0.69865316
Kurtosis0.51021558
Mean5.25
Median Absolute Deviation (MAD)2.5
Skewness0.92961511
Sum147
Variance13.453704
MonotonicityNot monotonic
2024-03-15T09:29:34.357133image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=11)
ValueCountFrequency (%)
2 6
21.4%
1 3
10.7%
8 3
10.7%
9 3
10.7%
3 3
10.7%
7 2
 
7.1%
6 2
 
7.1%
4 2
 
7.1%
5 2
 
7.1%
13 1
 
3.6%
ValueCountFrequency (%)
1 3
10.7%
2 6
21.4%
3 3
10.7%
4 2
 
7.1%
5 2
 
7.1%
6 2
 
7.1%
7 2
 
7.1%
8 3
10.7%
9 3
10.7%
13 1
 
3.6%
ValueCountFrequency (%)
15 1
 
3.6%
13 1
 
3.6%
9 3
10.7%
8 3
10.7%
7 2
 
7.1%
6 2
 
7.1%
5 2
 
7.1%
4 2
 
7.1%
3 3
10.7%
2 6
21.4%

업무지원
Real number (ℝ)

Distinct15
Distinct (%)53.6%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean9.75
Minimum2
Maximum23
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size380.0 B
2024-03-15T09:29:34.706435image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum2
5-th percentile3.35
Q17
median10
Q311.25
95-th percentile15.65
Maximum23
Range21
Interquartile range (IQR)4.25

Descriptive statistics

Standard deviation4.3000861
Coefficient of variation (CV)0.44103448
Kurtosis2.2244168
Mean9.75
Median Absolute Deviation (MAD)2
Skewness0.82864142
Sum273
Variance18.490741
MonotonicityNot monotonic
2024-03-15T09:29:35.048235image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=15)
ValueCountFrequency (%)
11 5
17.9%
10 4
14.3%
8 4
14.3%
7 3
10.7%
12 2
 
7.1%
14 1
 
3.6%
3 1
 
3.6%
2 1
 
3.6%
6 1
 
3.6%
4 1
 
3.6%
Other values (5) 5
17.9%
ValueCountFrequency (%)
2 1
 
3.6%
3 1
 
3.6%
4 1
 
3.6%
5 1
 
3.6%
6 1
 
3.6%
7 3
10.7%
8 4
14.3%
10 4
14.3%
11 5
17.9%
12 2
 
7.1%
ValueCountFrequency (%)
23 1
 
3.6%
16 1
 
3.6%
15 1
 
3.6%
14 1
 
3.6%
13 1
 
3.6%
12 2
 
7.1%
11 5
17.9%
10 4
14.3%
8 4
14.3%
7 3
10.7%

프로그램 장애
Real number (ℝ)

Distinct20
Distinct (%)71.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean21.464286
Minimum5
Maximum46
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size380.0 B
2024-03-15T09:29:35.333286image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum5
5-th percentile11.35
Q114.75
median21.5
Q325
95-th percentile37.9
Maximum46
Range41
Interquartile range (IQR)10.25

Descriptive statistics

Standard deviation8.9504072
Coefficient of variation (CV)0.41699068
Kurtosis1.1818191
Mean21.464286
Median Absolute Deviation (MAD)6
Skewness0.8092465
Sum601
Variance80.109788
MonotonicityNot monotonic
2024-03-15T09:29:35.530249image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=20)
ValueCountFrequency (%)
25 3
 
10.7%
21 2
 
7.1%
13 2
 
7.1%
24 2
 
7.1%
22 2
 
7.1%
12 2
 
7.1%
15 2
 
7.1%
14 1
 
3.6%
29 1
 
3.6%
20 1
 
3.6%
Other values (10) 10
35.7%
ValueCountFrequency (%)
5 1
3.6%
11 1
3.6%
12 2
7.1%
13 2
7.1%
14 1
3.6%
15 2
7.1%
17 1
3.6%
18 1
3.6%
20 1
3.6%
21 2
7.1%
ValueCountFrequency (%)
46 1
 
3.6%
40 1
 
3.6%
34 1
 
3.6%
29 1
 
3.6%
28 1
 
3.6%
27 1
 
3.6%
25 3
10.7%
24 2
7.1%
23 1
 
3.6%
22 2
7.1%

프린터 장애
Real number (ℝ)

HIGH CORRELATION 

Distinct25
Distinct (%)89.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean65.25
Minimum43
Maximum95
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size380.0 B
2024-03-15T09:29:35.743076image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum43
5-th percentile45.7
Q153
median63
Q375.5
95-th percentile90.95
Maximum95
Range52
Interquartile range (IQR)22.5

Descriptive statistics

Standard deviation14.663194
Coefficient of variation (CV)0.22472328
Kurtosis-0.78527969
Mean65.25
Median Absolute Deviation (MAD)12
Skewness0.33023216
Sum1827
Variance215.00926
MonotonicityNot monotonic
2024-03-15T09:29:35.971612image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=25)
ValueCountFrequency (%)
53 2
 
7.1%
75 2
 
7.1%
49 2
 
7.1%
77 1
 
3.6%
89 1
 
3.6%
64 1
 
3.6%
61 1
 
3.6%
95 1
 
3.6%
45 1
 
3.6%
62 1
 
3.6%
Other values (15) 15
53.6%
ValueCountFrequency (%)
43 1
3.6%
45 1
3.6%
47 1
3.6%
48 1
3.6%
49 2
7.1%
53 2
7.1%
56 1
3.6%
57 1
3.6%
58 1
3.6%
60 1
3.6%
ValueCountFrequency (%)
95 1
3.6%
92 1
3.6%
89 1
3.6%
80 1
3.6%
79 1
3.6%
78 1
3.6%
77 1
3.6%
75 2
7.1%
72 1
3.6%
71 1
3.6%

컴퓨터(PC)정비 요청처리 완료건수
Real number (ℝ)

HIGH CORRELATION 

Distinct27
Distinct (%)96.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean261.39286
Minimum193
Maximum370
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size380.0 B
2024-03-15T09:29:36.203603image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum193
5-th percentile207.4
Q1232.75
median249.5
Q3290.5
95-th percentile332.55
Maximum370
Range177
Interquartile range (IQR)57.75

Descriptive statistics

Standard deviation44.396646
Coefficient of variation (CV)0.16984644
Kurtosis-0.17143368
Mean261.39286
Median Absolute Deviation (MAD)24.5
Skewness0.73383293
Sum7319
Variance1971.0622
MonotonicityNot monotonic
2024-03-15T09:29:36.511309image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=27)
ValueCountFrequency (%)
234 2
 
7.1%
253 1
 
3.6%
239 1
 
3.6%
218 1
 
3.6%
238 1
 
3.6%
304 1
 
3.6%
206 1
 
3.6%
193 1
 
3.6%
248 1
 
3.6%
323 1
 
3.6%
Other values (17) 17
60.7%
ValueCountFrequency (%)
193 1
3.6%
206 1
3.6%
210 1
3.6%
218 1
3.6%
222 1
3.6%
225 1
3.6%
229 1
3.6%
234 2
7.1%
235 1
3.6%
238 1
3.6%
ValueCountFrequency (%)
370 1
3.6%
335 1
3.6%
328 1
3.6%
323 1
3.6%
316 1
3.6%
305 1
3.6%
304 1
3.6%
286 1
3.6%
274 1
3.6%
273 1
3.6%
Distinct24
Distinct (%)85.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean138.39286
Minimum105
Maximum199
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size380.0 B
2024-03-15T09:29:36.743753image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum105
5-th percentile106.35
Q1114.75
median129
Q3150.25
95-th percentile196.2
Maximum199
Range94
Interquartile range (IQR)35.5

Descriptive statistics

Standard deviation29.280684
Coefficient of variation (CV)0.21157656
Kurtosis-0.30711668
Mean138.39286
Median Absolute Deviation (MAD)18
Skewness0.8787544
Sum3875
Variance857.35847
MonotonicityNot monotonic
2024-03-15T09:29:36.968542image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=24)
ValueCountFrequency (%)
199 2
 
7.1%
111 2
 
7.1%
129 2
 
7.1%
142 2
 
7.1%
135 1
 
3.6%
106 1
 
3.6%
157 1
 
3.6%
109 1
 
3.6%
145 1
 
3.6%
184 1
 
3.6%
Other values (14) 14
50.0%
ValueCountFrequency (%)
105 1
3.6%
106 1
3.6%
107 1
3.6%
109 1
3.6%
111 2
7.1%
114 1
3.6%
115 1
3.6%
118 1
3.6%
120 1
3.6%
121 1
3.6%
ValueCountFrequency (%)
199 2
7.1%
191 1
3.6%
184 1
3.6%
180 1
3.6%
159 1
3.6%
157 1
3.6%
148 1
3.6%
147 1
3.6%
145 1
3.6%
142 2
7.1%
Distinct12
Distinct (%)42.9%
Missing0
Missing (%)0.0%
Memory size352.0 B
54%
50%
52%
47%
57%
Other values (7)

Length

Max length3
Median length3
Mean length3
Min length3

Unique

Unique5 ?
Unique (%)17.9%

Sample

1st row79%
2nd row50%
3rd row48%
4th row47%
5th row51%

Common Values

ValueCountFrequency (%)
54% 5
17.9%
50% 4
14.3%
52% 4
14.3%
47% 3
10.7%
57% 3
10.7%
48% 2
 
7.1%
49% 2
 
7.1%
79% 1
 
3.6%
51% 1
 
3.6%
55% 1
 
3.6%
Other values (2) 2
 
7.1%

Length

2024-03-15T09:29:37.201094image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
54 5
17.9%
50 4
14.3%
52 4
14.3%
47 3
10.7%
57 3
10.7%
48 2
 
7.1%
49 2
 
7.1%
79 1
 
3.6%
51 1
 
3.6%
55 1
 
3.6%
Other values (2) 2
 
7.1%
Distinct12
Distinct (%)42.9%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean4.9446429
Minimum4.83
Maximum5
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size380.0 B
2024-03-15T09:29:37.383106image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum4.83
5-th percentile4.8835
Q14.92
median4.95
Q34.97
95-th percentile5
Maximum5
Range0.17
Interquartile range (IQR)0.05

Descriptive statistics

Standard deviation0.040504425
Coefficient of variation (CV)0.0081915775
Kurtosis0.96419362
Mean4.9446429
Median Absolute Deviation (MAD)0.025
Skewness-0.71353948
Sum138.45
Variance0.0016406085
MonotonicityNot monotonic
2024-03-15T09:29:37.682314image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=12)
ValueCountFrequency (%)
5.0 4
14.3%
4.92 4
14.3%
4.96 4
14.3%
4.93 4
14.3%
4.95 3
10.7%
4.97 2
7.1%
4.99 2
7.1%
4.9 1
 
3.6%
4.89 1
 
3.6%
4.94 1
 
3.6%
Other values (2) 2
7.1%
ValueCountFrequency (%)
4.83 1
 
3.6%
4.88 1
 
3.6%
4.89 1
 
3.6%
4.9 1
 
3.6%
4.92 4
14.3%
4.93 4
14.3%
4.94 1
 
3.6%
4.95 3
10.7%
4.96 4
14.3%
4.97 2
7.1%
ValueCountFrequency (%)
5.0 4
14.3%
4.99 2
7.1%
4.97 2
7.1%
4.96 4
14.3%
4.95 3
10.7%
4.94 1
 
3.6%
4.93 4
14.3%
4.92 4
14.3%
4.9 1
 
3.6%
4.89 1
 
3.6%

컴퓨터(PC)정비 요청처리만족도 점수 합
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct28
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean684.39286
Minimum512
Maximum989
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size380.0 B
2024-03-15T09:29:37.967436image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum512
5-th percentile527.1
Q1573
median640
Q3744.25
95-th percentile971.6
Maximum989
Range477
Interquartile range (IQR)171.25

Descriptive statistics

Standard deviation145.55598
Coefficient of variation (CV)0.21267899
Kurtosis-0.24508021
Mean684.39286
Median Absolute Deviation (MAD)86.5
Skewness0.90120034
Sum19163
Variance21186.544
MonotonicityNot monotonic
2024-03-15T09:29:38.461295image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=28)
ValueCountFrequency (%)
989 1
 
3.6%
582 1
 
3.6%
512 1
 
3.6%
547 1
 
3.6%
772 1
 
3.6%
551 1
 
3.6%
536 1
 
3.6%
708 1
 
3.6%
918 1
 
3.6%
891 1
 
3.6%
Other values (18) 18
64.3%
ValueCountFrequency (%)
512 1
3.6%
525 1
3.6%
531 1
3.6%
536 1
3.6%
547 1
3.6%
551 1
3.6%
570 1
3.6%
574 1
3.6%
582 1
3.6%
592 1
3.6%
ValueCountFrequency (%)
989 1
3.6%
987 1
3.6%
943 1
3.6%
918 1
3.6%
891 1
3.6%
783 1
3.6%
772 1
3.6%
735 1
3.6%
724 1
3.6%
708 1
3.6%

Interactions

2024-03-15T09:29:26.267359image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T09:28:54.327662image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T09:28:56.868367image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T09:28:59.836059image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T09:29:03.046288image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T09:29:06.282227image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T09:29:09.179277image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T09:29:11.568058image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T09:29:14.003427image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T09:29:16.695154image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T09:29:19.817840image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T09:29:23.256556image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T09:29:26.420182image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T09:28:54.569924image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T09:28:57.124563image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T09:29:00.309618image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T09:29:03.312628image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T09:29:06.543175image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T09:29:09.375523image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T09:29:11.804296image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T09:29:14.247411image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T09:29:16.868586image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T09:29:20.136096image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T09:29:23.534981image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T09:29:26.569904image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T09:28:54.731263image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T09:28:57.373214image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T09:29:00.564310image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T09:29:03.566825image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T09:29:07.025630image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T09:29:09.518492image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T09:29:11.944764image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T09:29:14.489019image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T09:29:17.077605image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T09:29:20.478096image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T09:29:23.814217image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T09:29:26.809146image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T09:28:54.892721image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T09:28:57.607950image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T09:29:00.814558image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T09:29:03.827643image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T09:29:07.299893image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T09:29:09.661306image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T09:29:12.087321image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T09:29:14.730925image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T09:29:17.334713image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T09:29:20.878203image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T09:29:24.079090image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T09:29:27.069114image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T09:28:55.082659image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T09:28:57.863229image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T09:29:01.066172image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T09:29:04.082340image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T09:29:07.610610image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T09:29:09.833646image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T09:29:12.253996image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T09:29:14.982773image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T09:29:17.605375image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T09:29:21.124844image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T09:29:24.443045image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T09:29:27.322875image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T09:28:55.336124image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T09:28:58.112749image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T09:29:01.316506image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T09:29:04.408489image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T09:29:07.899245image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T09:29:10.122267image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T09:29:12.485524image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T09:29:15.138327image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T09:29:17.876707image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T09:29:21.385497image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T09:29:24.706990image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T09:29:27.556395image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T09:28:55.573637image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T09:28:58.340716image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T09:29:01.546689image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T09:29:04.652245image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T09:29:08.038265image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T09:29:10.274422image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T09:29:12.613620image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T09:29:15.294837image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T09:29:18.117949image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T09:29:21.626749image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T09:29:24.947086image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T09:29:27.802541image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T09:28:55.805981image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T09:28:58.573966image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T09:29:01.779444image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T09:29:04.871149image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T09:29:08.169278image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T09:29:10.513574image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T09:29:12.839568image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T09:29:15.462725image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T09:29:18.347646image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T09:29:21.873531image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T09:29:25.189486image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T09:29:28.043402image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T09:28:56.045999image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T09:28:58.811512image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T09:29:02.015810image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T09:29:05.140684image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T09:29:08.319295image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T09:29:10.744908image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T09:29:13.066730image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T09:29:15.706484image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T09:29:18.751091image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T09:29:22.145283image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T09:29:25.435858image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T09:29:28.306019image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T09:28:56.225311image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T09:28:59.077599image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T09:29:02.280320image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T09:29:05.444448image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T09:29:08.485139image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T09:29:10.992232image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T09:29:13.328131image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T09:29:15.990927image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T09:29:19.012334image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T09:29:22.413068image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T09:29:25.713371image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T09:29:28.545530image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T09:28:56.369675image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T09:28:59.321034image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T09:29:02.521358image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T09:29:05.717726image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T09:29:08.670308image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T09:29:11.225159image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T09:29:13.518721image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T09:29:16.227784image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T09:29:19.258329image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T09:29:22.668214image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T09:29:25.945532image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T09:29:28.814794image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T09:28:56.618060image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T09:28:59.587990image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T09:29:02.797544image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T09:29:05.996457image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T09:29:08.932869image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T09:29:11.430325image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T09:29:13.766407image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T09:29:16.485991image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T09:29:19.532182image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T09:29:22.979623image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T09:29:26.113549image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-03-15T09:29:38.770802image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
기간컴퓨터(PC) 장애기타 장애기타문의변경설치신규설치업무지원프로그램 장애프린터 장애컴퓨터(PC)정비 요청처리 완료건수컴퓨터(PC)정비 요청처리 만족도 회신 건수컴퓨터(PC)정비 요청처리 만족도 응답률컴퓨터(PC)정비 요청처리 만족도컴퓨터(PC)정비 요청처리만족도 점수 합
기간1.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.000
컴퓨터(PC) 장애1.0001.0000.0000.0000.4980.4440.5260.7320.4640.8290.7570.5650.0000.749
기타 장애1.0000.0001.0000.0000.0000.0000.0000.6310.0000.0000.0000.5160.0000.000
기타문의1.0000.0000.0001.0000.7560.3840.0000.6080.0000.0000.0000.7900.7930.000
변경설치1.0000.4980.0000.7561.0000.6030.7230.0000.3410.7000.8080.0000.4060.694
신규설치1.0000.4440.0000.3840.6031.0000.0000.0000.2900.7320.2360.0000.6570.359
업무지원1.0000.5260.0000.0000.7230.0001.0000.0000.3210.6630.8070.0000.0000.826
프로그램 장애1.0000.7320.6310.6080.0000.0000.0001.0000.0000.0360.8110.6990.0000.640
프린터 장애1.0000.4640.0000.0000.3410.2900.3210.0001.0000.6880.0000.0000.5070.000
컴퓨터(PC)정비 요청처리 완료건수1.0000.8290.0000.0000.7000.7320.6630.0360.6881.0000.6510.0000.1540.715
컴퓨터(PC)정비 요청처리 만족도 회신 건수1.0000.7570.0000.0000.8080.2360.8070.8110.0000.6511.0000.0000.0000.998
컴퓨터(PC)정비 요청처리 만족도 응답률1.0000.5650.5160.7900.0000.0000.0000.6990.0000.0000.0001.0000.5470.000
컴퓨터(PC)정비 요청처리 만족도1.0000.0000.0000.7930.4060.6570.0000.0000.5070.1540.0000.5471.0000.000
컴퓨터(PC)정비 요청처리만족도 점수 합1.0000.7490.0000.0000.6940.3590.8260.6400.0000.7150.9980.0000.0001.000
2024-03-15T09:29:39.181757image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
컴퓨터(PC) 장애기타 장애기타문의변경설치신규설치업무지원프로그램 장애프린터 장애컴퓨터(PC)정비 요청처리 완료건수컴퓨터(PC)정비 요청처리 만족도 회신 건수컴퓨터(PC)정비 요청처리 만족도컴퓨터(PC)정비 요청처리만족도 점수 합컴퓨터(PC)정비 요청처리 만족도 응답률
컴퓨터(PC) 장애1.000-0.1640.3750.6580.562-0.182-0.1490.3010.8570.7410.0690.7440.274
기타 장애-0.1641.0000.1670.1190.1080.3690.073-0.1530.0420.0730.3240.0990.175
기타문의0.3750.1671.0000.4360.1790.0720.1330.0380.4830.5320.1210.5310.429
변경설치0.6580.1190.4361.0000.5830.1760.1870.3660.8040.605-0.2040.5980.000
신규설치0.5620.1080.1790.5831.0000.142-0.0580.3560.6140.563-0.0390.5490.000
업무지원-0.1820.3690.0720.1760.1421.0000.417-0.0970.0580.089-0.2880.0850.000
프로그램 장애-0.1490.0730.1330.187-0.0580.4171.000-0.1780.0290.043-0.0320.0430.330
프린터 장애0.301-0.1530.0380.3660.356-0.097-0.1781.0000.5610.449-0.3150.4200.000
컴퓨터(PC)정비 요청처리 완료건수0.8570.0420.4830.8040.6140.0580.0290.5611.0000.897-0.0710.8920.000
컴퓨터(PC)정비 요청처리 만족도 회신 건수0.7410.0730.5320.6050.5630.0890.0430.4490.8971.000-0.0340.9980.000
컴퓨터(PC)정비 요청처리 만족도0.0690.3240.121-0.204-0.039-0.288-0.032-0.315-0.071-0.0341.0000.0120.204
컴퓨터(PC)정비 요청처리만족도 점수 합0.7440.0990.5310.5980.5490.0850.0430.4200.8920.9980.0121.0000.000
컴퓨터(PC)정비 요청처리 만족도 응답률0.2740.1750.4290.0000.0000.0000.3300.0000.0000.0000.2040.0001.000

Missing values

2024-03-15T09:29:29.185823image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-03-15T09:29:29.804157image/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

기간컴퓨터(PC) 장애기타 장애기타문의변경설치신규설치업무지원프로그램 장애프린터 장애컴퓨터(PC)정비 요청처리 완료건수컴퓨터(PC)정비 요청처리 만족도 회신 건수컴퓨터(PC)정비 요청처리 만족도 응답률컴퓨터(PC)정비 요청처리 만족도컴퓨터(PC)정비 요청처리만족도 점수 합
02024-06-211171682210217725319979%4.97989
12024-07-211011732211254921010550%5.0525
22024-08-21167221311710277132815948%4.92783
32024-09-211051482214285622910747%4.96531
42024-10-21133125313254322511451%5.0570
52024-11-211282112367114723512955%5.0645
62024-12-21139171481311145727314854%4.97735
72024-01-221671371088137930514247%4.95703
82024-02-22123143282125822211552%4.99574
92024-03-221979141496299237019954%4.96987
기간컴퓨터(PC) 장애기타 장애기타문의변경설치신규설치업무지원프로그램 장애프린터 장애컴퓨터(PC)정비 요청처리 완료건수컴퓨터(PC)정비 요청처리 만족도 회신 건수컴퓨터(PC)정비 요청처리 만족도 응답률컴퓨터(PC)정비 요청처리 만족도컴퓨터(PC)정비 요청처리만족도 점수 합
182024-12-221401066611227027114754%4.93724
192024-01-23196134101510256233519157%4.94943
202024-02-23163171416823225331618057%4.95891
212024-03-2314221410916467532318457%4.99918
222024-04-2311514116112404924814558%4.88708
232024-05-2377123338345319310956%4.92536
242024-06-23991635212244520611154%4.96551
252024-07-231371557915219530415752%4.92772
262024-08-231091588211246123811147%4.93547
272024-09-23931314713236421810649%4.83512