Overview

Dataset statistics

Number of variables17
Number of observations731
Missing cells3762
Missing cells (%)30.3%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory108.6 KiB
Average record size in memory152.2 B

Variable types

DateTime1
Numeric16

Dataset

Description한국남부발전(주)_사업소별트래픽에 대한 데이터로 날짜, 사업소별(본사, 하동, 남제주, 인천, 영월, 안동, 삼척, 부산) 평균 등의 항목을 제공합니다.
Author한국남부발전(주)
URLhttps://www.data.go.kr/data/15033833/fileData.do

Alerts

하동 평균(Mbps) is highly overall correlated with 하동 최대(Mbps) and 6 other fieldsHigh correlation
하동 최대(Mbps) is highly overall correlated with 하동 평균(Mbps) and 5 other fieldsHigh correlation
남제주 평균(Mbps) is highly overall correlated with 하동 평균(Mbps) and 5 other fieldsHigh correlation
남제주 최대(Mbps) is highly overall correlated with 남제주 평균(Mbps)High correlation
인천 평균(Mbps) is highly overall correlated with 하동 평균(Mbps) and 1 other fieldsHigh correlation
인천 최대(Mbps) is highly overall correlated with 인천 평균(Mbps)High correlation
영월 평균(Mbps) is highly overall correlated with 영월 최대(Mbps) and 1 other fieldsHigh correlation
영월 최대(Mbps) is highly overall correlated with 영월 평균(Mbps)High correlation
안동 평균(Mbps) is highly overall correlated with 하동 평균(Mbps) and 5 other fieldsHigh correlation
안동 최대(Mbps) is highly overall correlated with 하동 평균(Mbps) and 4 other fieldsHigh correlation
삼척 평균(Mbps) is highly overall correlated with 하동 평균(Mbps) and 5 other fieldsHigh correlation
삼척 최대(Mbps) is highly overall correlated with 하동 평균(Mbps) and 6 other fieldsHigh correlation
본사 평균(Mbps) has 306 (41.9%) missing valuesMissing
본사 최대(Mbps) has 306 (41.9%) missing valuesMissing
하동 평균(Mbps) has 209 (28.6%) missing valuesMissing
하동 최대(Mbps) has 209 (28.6%) missing valuesMissing
남제주 평균(Mbps) has 188 (25.7%) missing valuesMissing
남제주 최대(Mbps) has 188 (25.7%) missing valuesMissing
인천 평균(Mbps) has 306 (41.9%) missing valuesMissing
인천 최대(Mbps) has 306 (41.9%) missing valuesMissing
영월 평균(Mbps) has 166 (22.7%) missing valuesMissing
영월 최대(Mbps) has 166 (22.7%) missing valuesMissing
안동 평균(Mbps) has 263 (36.0%) missing valuesMissing
안동 최대(Mbps) has 263 (36.0%) missing valuesMissing
삼척 평균(Mbps) has 263 (36.0%) missing valuesMissing
삼척 최대(Mbps) has 263 (36.0%) missing valuesMissing
부산 평균(Mbps) has 180 (24.6%) missing valuesMissing
부산 최대(Mbps) has 180 (24.6%) missing valuesMissing
구분 has unique valuesUnique

Reproduction

Analysis started2024-05-11 07:50:24.829845
Analysis finished2024-05-11 07:51:29.258817
Duration1 minute and 4.43 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

구분
Date

UNIQUE 

Distinct731
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size5.8 KiB
Minimum2022-05-01 00:00:00
Maximum2024-04-30 00:00:00
2024-05-11T16:51:29.417793image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T16:51:29.764697image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

본사 평균(Mbps)
Real number (ℝ)

MISSING 

Distinct406
Distinct (%)95.5%
Missing306
Missing (%)41.9%
Infinite0
Infinite (%)0.0%
Mean121.32247
Minimum58.95
Maximum285.03
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size6.6 KiB
2024-05-11T16:51:30.067260image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum58.95
5-th percentile78.552
Q1109.17
median120.85
Q3132.02
95-th percentile163.492
Maximum285.03
Range226.08
Interquartile range (IQR)22.85

Descriptive statistics

Standard deviation26.224761
Coefficient of variation (CV)0.21615749
Kurtosis6.2990114
Mean121.32247
Median Absolute Deviation (MAD)11.43
Skewness1.3138425
Sum51562.05
Variance687.73807
MonotonicityNot monotonic
2024-05-11T16:51:30.396918image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
114.45 3
 
0.4%
122.76 2
 
0.3%
134.0 2
 
0.3%
111.08 2
 
0.3%
114.83 2
 
0.3%
72.11 2
 
0.3%
112.04 2
 
0.3%
126.29 2
 
0.3%
137.47 2
 
0.3%
121.09 2
 
0.3%
Other values (396) 404
55.3%
(Missing) 306
41.9%
ValueCountFrequency (%)
58.95 1
0.1%
60.26 1
0.1%
61.34 1
0.1%
65.04 1
0.1%
65.25 1
0.1%
66.52 1
0.1%
68.85 1
0.1%
69.45 1
0.1%
70.36 1
0.1%
71.36 1
0.1%
ValueCountFrequency (%)
285.03 1
0.1%
249.72 1
0.1%
239.28 1
0.1%
230.28 1
0.1%
207.02 1
0.1%
203.91 1
0.1%
199.82 1
0.1%
191.69 1
0.1%
185.17 1
0.1%
183.34 1
0.1%

본사 최대(Mbps)
Real number (ℝ)

MISSING 

Distinct418
Distinct (%)98.4%
Missing306
Missing (%)41.9%
Infinite0
Infinite (%)0.0%
Mean614.62616
Minimum360.74
Maximum894.35
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size6.6 KiB
2024-05-11T16:51:30.716874image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum360.74
5-th percentile494.83
Q1589.78
median620.84
Q3638.86
95-th percentile706.388
Maximum894.35
Range533.61
Interquartile range (IQR)49.08

Descriptive statistics

Standard deviation63.296607
Coefficient of variation (CV)0.10298391
Kurtosis3.7639355
Mean614.62616
Median Absolute Deviation (MAD)21.44
Skewness0.25754608
Sum261216.12
Variance4006.4604
MonotonicityNot monotonic
2024-05-11T16:51:31.070789image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
629.76 2
 
0.3%
644.61 2
 
0.3%
601.82 2
 
0.3%
615.18 2
 
0.3%
627.13 2
 
0.3%
629.77 2
 
0.3%
638.86 2
 
0.3%
628.02 1
 
0.1%
616.33 1
 
0.1%
619.95 1
 
0.1%
Other values (408) 408
55.8%
(Missing) 306
41.9%
ValueCountFrequency (%)
360.74 1
0.1%
425.26 1
0.1%
427.76 1
0.1%
428.63 1
0.1%
433.12 1
0.1%
445.23 1
0.1%
445.98 1
0.1%
453.82 1
0.1%
465.72 1
0.1%
468.16 1
0.1%
ValueCountFrequency (%)
894.35 1
0.1%
890.36 1
0.1%
841.2 1
0.1%
834.0 1
0.1%
821.81 1
0.1%
802.88 1
0.1%
802.54 1
0.1%
798.84 1
0.1%
794.96 1
0.1%
780.82 1
0.1%

하동 평균(Mbps)
Real number (ℝ)

HIGH CORRELATION  MISSING 

Distinct505
Distinct (%)96.7%
Missing209
Missing (%)28.6%
Infinite0
Infinite (%)0.0%
Mean97.916437
Minimum42.53
Maximum296.05
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size6.6 KiB
2024-05-11T16:51:31.517195image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum42.53
5-th percentile61.1925
Q177.7825
median91.495
Q3108.0325
95-th percentile169.624
Maximum296.05
Range253.52
Interquartile range (IQR)30.25

Descriptive statistics

Standard deviation34.073799
Coefficient of variation (CV)0.34798856
Kurtosis7.6155557
Mean97.916437
Median Absolute Deviation (MAD)15.13
Skewness2.2467219
Sum51112.38
Variance1161.0238
MonotonicityNot monotonic
2024-05-11T16:51:31.886578image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
81.04 2
 
0.3%
80.82 2
 
0.3%
116.11 2
 
0.3%
72.14 2
 
0.3%
71.31 2
 
0.3%
93.81 2
 
0.3%
93.34 2
 
0.3%
102.27 2
 
0.3%
110.95 2
 
0.3%
98.81 2
 
0.3%
Other values (495) 502
68.7%
(Missing) 209
28.6%
ValueCountFrequency (%)
42.53 1
0.1%
46.68 1
0.1%
47.32 1
0.1%
49.8 1
0.1%
49.85 1
0.1%
49.99 1
0.1%
50.41 1
0.1%
51.36 1
0.1%
51.76 1
0.1%
51.91 1
0.1%
ValueCountFrequency (%)
296.05 1
0.1%
294.22 1
0.1%
263.85 1
0.1%
258.62 1
0.1%
237.47 1
0.1%
236.94 1
0.1%
236.43 1
0.1%
213.13 1
0.1%
208.58 1
0.1%
207.65 1
0.1%

하동 최대(Mbps)
Real number (ℝ)

HIGH CORRELATION  MISSING 

Distinct515
Distinct (%)98.7%
Missing209
Missing (%)28.6%
Infinite0
Infinite (%)0.0%
Mean227.45573
Minimum104.64
Maximum875.37
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size6.6 KiB
2024-05-11T16:51:32.213494image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum104.64
5-th percentile135.2595
Q1172.2975
median207.82
Q3257.06
95-th percentile374.897
Maximum875.37
Range770.73
Interquartile range (IQR)84.7625

Descriptive statistics

Standard deviation88.593653
Coefficient of variation (CV)0.38949845
Kurtosis11.300369
Mean227.45573
Median Absolute Deviation (MAD)41.815
Skewness2.5960557
Sum118731.89
Variance7848.8354
MonotonicityNot monotonic
2024-05-11T16:51:32.598520image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
168.57 2
 
0.3%
188.2 2
 
0.3%
203.01 2
 
0.3%
201.4 2
 
0.3%
199.31 2
 
0.3%
250.05 2
 
0.3%
128.71 2
 
0.3%
171.56 1
 
0.1%
156.95 1
 
0.1%
247.98 1
 
0.1%
Other values (505) 505
69.1%
(Missing) 209
28.6%
ValueCountFrequency (%)
104.64 1
0.1%
108.0 1
0.1%
108.35 1
0.1%
111.18 1
0.1%
112.06 1
0.1%
112.16 1
0.1%
113.77 1
0.1%
114.62 1
0.1%
120.33 1
0.1%
121.37 1
0.1%
ValueCountFrequency (%)
875.37 1
0.1%
688.89 1
0.1%
683.06 1
0.1%
670.53 1
0.1%
664.83 1
0.1%
651.16 1
0.1%
625.17 1
0.1%
561.03 1
0.1%
529.13 1
0.1%
469.21 1
0.1%

남제주 평균(Mbps)
Real number (ℝ)

HIGH CORRELATION  MISSING 

Distinct502
Distinct (%)92.4%
Missing188
Missing (%)25.7%
Infinite0
Infinite (%)0.0%
Mean45.718103
Minimum22.63
Maximum90.76
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size6.6 KiB
2024-05-11T16:51:33.004976image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum22.63
5-th percentile31.808
Q139.26
median44.37
Q349.975
95-th percentile66.144
Maximum90.76
Range68.13
Interquartile range (IQR)10.715

Descriptive statistics

Standard deviation10.494069
Coefficient of variation (CV)0.2295386
Kurtosis2.3935716
Mean45.718103
Median Absolute Deviation (MAD)5.3
Skewness1.1978152
Sum24824.93
Variance110.12549
MonotonicityNot monotonic
2024-05-11T16:51:33.424973image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
48.27 3
 
0.4%
41.86 3
 
0.4%
43.38 3
 
0.4%
40.3 3
 
0.4%
42.67 2
 
0.3%
47.92 2
 
0.3%
44.77 2
 
0.3%
47.77 2
 
0.3%
38.33 2
 
0.3%
43.36 2
 
0.3%
Other values (492) 519
71.0%
(Missing) 188
 
25.7%
ValueCountFrequency (%)
22.63 1
0.1%
23.55 1
0.1%
25.34 1
0.1%
26.82 1
0.1%
26.88 1
0.1%
26.97 1
0.1%
27.24 1
0.1%
28.13 1
0.1%
28.16 1
0.1%
28.19 1
0.1%
ValueCountFrequency (%)
90.76 1
0.1%
84.46 1
0.1%
84.23 1
0.1%
82.88 1
0.1%
82.04 1
0.1%
81.54 1
0.1%
80.3 1
0.1%
78.53 1
0.1%
78.2 1
0.1%
77.87 1
0.1%

남제주 최대(Mbps)
Real number (ℝ)

HIGH CORRELATION  MISSING 

Distinct535
Distinct (%)98.5%
Missing188
Missing (%)25.7%
Infinite0
Infinite (%)0.0%
Mean118.75663
Minimum61.06
Maximum613.28
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size6.6 KiB
2024-05-11T16:51:33.987747image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum61.06
5-th percentile81.151
Q198.085
median111.82
Q3130.58
95-th percentile174.382
Maximum613.28
Range552.22
Interquartile range (IQR)32.495

Descriptive statistics

Standard deviation39.122173
Coefficient of variation (CV)0.32943149
Kurtosis70.908064
Mean118.75663
Median Absolute Deviation (MAD)15.55
Skewness6.3715269
Sum64484.85
Variance1530.5444
MonotonicityNot monotonic
2024-05-11T16:51:34.518790image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
101.0 2
 
0.3%
110.97 2
 
0.3%
114.51 2
 
0.3%
139.59 2
 
0.3%
98.37 2
 
0.3%
109.99 2
 
0.3%
134.16 2
 
0.3%
125.52 2
 
0.3%
145.5 1
 
0.1%
113.91 1
 
0.1%
Other values (525) 525
71.8%
(Missing) 188
 
25.7%
ValueCountFrequency (%)
61.06 1
0.1%
70.1 1
0.1%
71.35 1
0.1%
73.67 1
0.1%
74.08 1
0.1%
74.76 1
0.1%
75.44 1
0.1%
76.3 1
0.1%
76.69 1
0.1%
76.87 1
0.1%
ValueCountFrequency (%)
613.28 1
0.1%
540.95 1
0.1%
237.14 1
0.1%
217.13 1
0.1%
212.3 1
0.1%
206.59 1
0.1%
203.73 1
0.1%
201.83 1
0.1%
201.34 1
0.1%
199.88 1
0.1%

인천 평균(Mbps)
Real number (ℝ)

HIGH CORRELATION  MISSING 

Distinct413
Distinct (%)97.2%
Missing306
Missing (%)41.9%
Infinite0
Infinite (%)0.0%
Mean48.540494
Minimum18.12
Maximum285.03
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size6.6 KiB
2024-05-11T16:51:35.277183image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum18.12
5-th percentile27.058
Q135.03
median41.89
Q350.83
95-th percentile98.52
Maximum285.03
Range266.91
Interquartile range (IQR)15.8

Descriptive statistics

Standard deviation27.690712
Coefficient of variation (CV)0.57046621
Kurtosis24.21614
Mean48.540494
Median Absolute Deviation (MAD)7.59
Skewness4.0666082
Sum20629.71
Variance766.77553
MonotonicityNot monotonic
2024-05-11T16:51:35.622427image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
44.77 3
 
0.4%
43.2 2
 
0.3%
39.35 2
 
0.3%
27.56 2
 
0.3%
50.83 2
 
0.3%
44.14 2
 
0.3%
31.52 2
 
0.3%
49.31 2
 
0.3%
72.11 2
 
0.3%
43.76 2
 
0.3%
Other values (403) 404
55.3%
(Missing) 306
41.9%
ValueCountFrequency (%)
18.12 1
0.1%
19.61 1
0.1%
19.88 1
0.1%
21.06 1
0.1%
21.74 1
0.1%
22.42 1
0.1%
22.44 1
0.1%
23.05 1
0.1%
23.36 1
0.1%
23.5 1
0.1%
ValueCountFrequency (%)
285.03 1
0.1%
249.72 1
0.1%
230.28 1
0.1%
158.05 1
0.1%
157.9 1
0.1%
151.59 1
0.1%
136.1 1
0.1%
132.65 1
0.1%
130.42 1
0.1%
129.66 1
0.1%

인천 최대(Mbps)
Real number (ℝ)

HIGH CORRELATION  MISSING 

Distinct422
Distinct (%)99.3%
Missing306
Missing (%)41.9%
Infinite0
Infinite (%)0.0%
Mean190.68285
Minimum60.65
Maximum890.36
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size6.6 KiB
2024-05-11T16:51:35.927298image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum60.65
5-th percentile78.032
Q1100.83
median118.12
Q3145.6
95-th percentile674.982
Maximum890.36
Range829.71
Interquartile range (IQR)44.77

Descriptive statistics

Standard deviation192.19983
Coefficient of variation (CV)1.0079555
Kurtosis2.9824704
Mean190.68285
Median Absolute Deviation (MAD)20.23
Skewness2.1515086
Sum81040.21
Variance36940.775
MonotonicityNot monotonic
2024-05-11T16:51:36.304017image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
126.07 2
 
0.3%
134.85 2
 
0.3%
108.47 2
 
0.3%
108.62 1
 
0.1%
115.27 1
 
0.1%
141.84 1
 
0.1%
154.19 1
 
0.1%
72.98 1
 
0.1%
92.74 1
 
0.1%
105.54 1
 
0.1%
Other values (412) 412
56.4%
(Missing) 306
41.9%
ValueCountFrequency (%)
60.65 1
0.1%
64.13 1
0.1%
65.45 1
0.1%
65.67 1
0.1%
66.69 1
0.1%
68.42 1
0.1%
68.82 1
0.1%
71.13 1
0.1%
72.35 1
0.1%
72.98 1
0.1%
ValueCountFrequency (%)
890.36 1
0.1%
834.0 1
0.1%
821.81 1
0.1%
802.88 1
0.1%
798.84 1
0.1%
773.18 1
0.1%
751.95 1
0.1%
751.74 1
0.1%
744.9 1
0.1%
744.77 1
0.1%

영월 평균(Mbps)
Real number (ℝ)

HIGH CORRELATION  MISSING 

Distinct491
Distinct (%)86.9%
Missing166
Missing (%)22.7%
Infinite0
Infinite (%)0.0%
Mean13.825168
Minimum3.12
Maximum46.92
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size6.6 KiB
2024-05-11T16:51:36.690182image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum3.12
5-th percentile5.734
Q19.85
median12.96
Q316.7
95-th percentile24.342
Maximum46.92
Range43.8
Interquartile range (IQR)6.85

Descriptive statistics

Standard deviation6.2050956
Coefficient of variation (CV)0.44882605
Kurtosis4.7248975
Mean13.825168
Median Absolute Deviation (MAD)3.52
Skewness1.5784361
Sum7811.22
Variance38.503212
MonotonicityNot monotonic
2024-05-11T16:51:37.017107image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
14.32 4
 
0.5%
13.74 3
 
0.4%
10.21 3
 
0.4%
10.14 3
 
0.4%
15.71 3
 
0.4%
12.54 3
 
0.4%
12.61 3
 
0.4%
16.87 3
 
0.4%
10.42 3
 
0.4%
8.6 2
 
0.3%
Other values (481) 535
73.2%
(Missing) 166
 
22.7%
ValueCountFrequency (%)
3.12 1
0.1%
3.69 1
0.1%
4.05 1
0.1%
4.11 1
0.1%
4.18 1
0.1%
4.42 1
0.1%
4.55 1
0.1%
4.65 1
0.1%
4.67 1
0.1%
4.69 1
0.1%
ValueCountFrequency (%)
46.92 1
0.1%
46.75 1
0.1%
43.73 1
0.1%
39.83 1
0.1%
36.65 1
0.1%
36.56 1
0.1%
36.1 1
0.1%
35.26 1
0.1%
34.12 1
0.1%
33.91 1
0.1%

영월 최대(Mbps)
Real number (ℝ)

HIGH CORRELATION  MISSING 

Distinct535
Distinct (%)94.7%
Missing166
Missing (%)22.7%
Infinite0
Infinite (%)0.0%
Mean58.638814
Minimum20.89
Maximum410.15
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size6.6 KiB
2024-05-11T16:51:37.325320image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum20.89
5-th percentile29.06
Q140.11
median52.94
Q365.17
95-th percentile108.752
Maximum410.15
Range389.26
Interquartile range (IQR)25.06

Descriptive statistics

Standard deviation35.969946
Coefficient of variation (CV)0.6134153
Kurtosis37.370071
Mean58.638814
Median Absolute Deviation (MAD)12.63
Skewness5.0460062
Sum33130.93
Variance1293.837
MonotonicityNot monotonic
2024-05-11T16:51:37.629894image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
74.27 3
 
0.4%
48.79 3
 
0.4%
45.85 2
 
0.3%
54.52 2
 
0.3%
59.85 2
 
0.3%
37.37 2
 
0.3%
37.55 2
 
0.3%
42.92 2
 
0.3%
70.59 2
 
0.3%
44.8 2
 
0.3%
Other values (525) 543
74.3%
(Missing) 166
 
22.7%
ValueCountFrequency (%)
20.89 1
0.1%
20.98 1
0.1%
22.12 1
0.1%
22.78 1
0.1%
23.02 1
0.1%
23.14 1
0.1%
23.71 1
0.1%
24.36 1
0.1%
24.62 1
0.1%
24.8 1
0.1%
ValueCountFrequency (%)
410.15 1
0.1%
376.29 1
0.1%
306.64 1
0.1%
303.01 1
0.1%
302.63 1
0.1%
187.71 1
0.1%
172.43 1
0.1%
170.46 1
0.1%
161.74 1
0.1%
157.94 1
0.1%

안동 평균(Mbps)
Real number (ℝ)

HIGH CORRELATION  MISSING 

Distinct440
Distinct (%)94.0%
Missing263
Missing (%)36.0%
Infinite0
Infinite (%)0.0%
Mean17.939188
Minimum2.49
Maximum42.95
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size6.6 KiB
2024-05-11T16:51:37.950903image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum2.49
5-th percentile6.7045
Q111.9575
median16.89
Q323.9475
95-th percentile31.8555
Maximum42.95
Range40.46
Interquartile range (IQR)11.99

Descriptive statistics

Standard deviation7.7495192
Coefficient of variation (CV)0.43198829
Kurtosis-0.35658587
Mean17.939188
Median Absolute Deviation (MAD)5.84
Skewness0.42538407
Sum8395.54
Variance60.055048
MonotonicityNot monotonic
2024-05-11T16:51:38.239893image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
14.11 3
 
0.4%
8.8 2
 
0.3%
8.98 2
 
0.3%
26.94 2
 
0.3%
12.1 2
 
0.3%
9.1 2
 
0.3%
11.05 2
 
0.3%
16.62 2
 
0.3%
18.53 2
 
0.3%
16.33 2
 
0.3%
Other values (430) 447
61.1%
(Missing) 263
36.0%
ValueCountFrequency (%)
2.49 1
0.1%
3.42 1
0.1%
3.59 1
0.1%
3.72 1
0.1%
3.88 1
0.1%
4.03 1
0.1%
4.34 1
0.1%
4.47 2
0.3%
4.67 1
0.1%
4.74 1
0.1%
ValueCountFrequency (%)
42.95 1
0.1%
40.66 1
0.1%
38.75 1
0.1%
37.63 1
0.1%
37.56 1
0.1%
36.95 1
0.1%
36.21 1
0.1%
35.91 1
0.1%
34.91 1
0.1%
34.9 1
0.1%

안동 최대(Mbps)
Real number (ℝ)

HIGH CORRELATION  MISSING 

Distinct454
Distinct (%)97.0%
Missing263
Missing (%)36.0%
Infinite0
Infinite (%)0.0%
Mean64.601496
Minimum20.71
Maximum136.66
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size6.6 KiB
2024-05-11T16:51:38.604401image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum20.71
5-th percentile34.5155
Q147.0875
median60.37
Q380.0225
95-th percentile105.785
Maximum136.66
Range115.95
Interquartile range (IQR)32.935

Descriptive statistics

Standard deviation22.116378
Coefficient of variation (CV)0.34235087
Kurtosis-0.1584077
Mean64.601496
Median Absolute Deviation (MAD)16.2
Skewness0.58666765
Sum30233.5
Variance489.13419
MonotonicityNot monotonic
2024-05-11T16:51:38.940885image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
80.75 2
 
0.3%
53.42 2
 
0.3%
93.46 2
 
0.3%
44.95 2
 
0.3%
53.1 2
 
0.3%
60.76 2
 
0.3%
41.2 2
 
0.3%
51.99 2
 
0.3%
56.79 2
 
0.3%
49.59 2
 
0.3%
Other values (444) 448
61.3%
(Missing) 263
36.0%
ValueCountFrequency (%)
20.71 1
0.1%
21.74 1
0.1%
24.97 1
0.1%
25.5 1
0.1%
27.45 1
0.1%
27.89 1
0.1%
28.69 2
0.3%
28.94 1
0.1%
29.75 1
0.1%
29.95 1
0.1%
ValueCountFrequency (%)
136.66 1
0.1%
136.35 1
0.1%
135.32 1
0.1%
134.6 1
0.1%
115.38 1
0.1%
115.22 1
0.1%
114.41 1
0.1%
113.02 1
0.1%
112.16 1
0.1%
110.67 1
0.1%

삼척 평균(Mbps)
Real number (ℝ)

HIGH CORRELATION  MISSING 

Distinct445
Distinct (%)95.1%
Missing263
Missing (%)36.0%
Infinite0
Infinite (%)0.0%
Mean35.070064
Minimum7.94
Maximum88.13
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size6.6 KiB
2024-05-11T16:51:39.367042image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum7.94
5-th percentile19.624
Q126.26
median33.55
Q341.525
95-th percentile60.556
Maximum88.13
Range80.19
Interquartile range (IQR)15.265

Descriptive statistics

Standard deviation12.125604
Coefficient of variation (CV)0.3457537
Kurtosis1.858174
Mean35.070064
Median Absolute Deviation (MAD)7.45
Skewness1.0541728
Sum16412.79
Variance147.03028
MonotonicityNot monotonic
2024-05-11T16:51:39.706646image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
35.63 2
 
0.3%
43.69 2
 
0.3%
25.29 2
 
0.3%
23.8 2
 
0.3%
21.49 2
 
0.3%
39.59 2
 
0.3%
35.94 2
 
0.3%
24.88 2
 
0.3%
25.42 2
 
0.3%
39.76 2
 
0.3%
Other values (435) 448
61.3%
(Missing) 263
36.0%
ValueCountFrequency (%)
7.94 1
0.1%
12.44 1
0.1%
12.47 1
0.1%
14.12 1
0.1%
14.22 1
0.1%
14.9 1
0.1%
14.95 1
0.1%
15.01 1
0.1%
15.2 1
0.1%
15.35 1
0.1%
ValueCountFrequency (%)
88.13 1
0.1%
85.68 1
0.1%
77.09 1
0.1%
75.36 1
0.1%
73.66 1
0.1%
73.19 1
0.1%
72.4 1
0.1%
69.94 1
0.1%
69.23 1
0.1%
66.84 1
0.1%

삼척 최대(Mbps)
Real number (ℝ)

HIGH CORRELATION  MISSING 

Distinct456
Distinct (%)97.4%
Missing263
Missing (%)36.0%
Infinite0
Infinite (%)0.0%
Mean94.009103
Minimum32.93
Maximum224.07
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size6.6 KiB
2024-05-11T16:51:40.006180image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum32.93
5-th percentile51.574
Q165.6475
median89.09
Q3110.37
95-th percentile173.116
Maximum224.07
Range191.14
Interquartile range (IQR)44.7225

Descriptive statistics

Standard deviation36.190736
Coefficient of variation (CV)0.38497055
Kurtosis1.5148962
Mean94.009103
Median Absolute Deviation (MAD)22.505
Skewness1.1774544
Sum43996.26
Variance1309.7694
MonotonicityNot monotonic
2024-05-11T16:51:40.487926image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
103.83 3
 
0.4%
67.98 2
 
0.3%
87.73 2
 
0.3%
110.37 2
 
0.3%
61.52 2
 
0.3%
91.6 2
 
0.3%
96.85 2
 
0.3%
112.41 2
 
0.3%
110.09 2
 
0.3%
51.95 2
 
0.3%
Other values (446) 447
61.1%
(Missing) 263
36.0%
ValueCountFrequency (%)
32.93 1
0.1%
39.31 1
0.1%
40.44 1
0.1%
41.53 1
0.1%
43.78 1
0.1%
44.52 1
0.1%
44.9 1
0.1%
45.56 1
0.1%
45.77 1
0.1%
45.81 1
0.1%
ValueCountFrequency (%)
224.07 1
0.1%
223.28 1
0.1%
221.36 1
0.1%
215.28 1
0.1%
214.13 1
0.1%
213.24 1
0.1%
205.56 1
0.1%
203.35 1
0.1%
202.65 1
0.1%
196.64 1
0.1%

부산 평균(Mbps)
Real number (ℝ)

MISSING 

Distinct508
Distinct (%)92.2%
Missing180
Missing (%)24.6%
Infinite0
Infinite (%)0.0%
Mean39.108966
Minimum18.14
Maximum87.31
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size6.6 KiB
2024-05-11T16:51:40.767090image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum18.14
5-th percentile25.025
Q132.15
median37.62
Q343.99
95-th percentile60.08
Maximum87.31
Range69.17
Interquartile range (IQR)11.84

Descriptive statistics

Standard deviation10.732321
Coefficient of variation (CV)0.27442099
Kurtosis2.5374514
Mean39.108966
Median Absolute Deviation (MAD)5.77
Skewness1.302199
Sum21549.04
Variance115.18271
MonotonicityNot monotonic
2024-05-11T16:51:41.052534image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
38.9 3
 
0.4%
32.9 3
 
0.4%
24.14 2
 
0.3%
32.64 2
 
0.3%
33.52 2
 
0.3%
27.9 2
 
0.3%
34.53 2
 
0.3%
33.56 2
 
0.3%
45.48 2
 
0.3%
28.53 2
 
0.3%
Other values (498) 529
72.4%
(Missing) 180
 
24.6%
ValueCountFrequency (%)
18.14 1
0.1%
20.17 1
0.1%
21.0 2
0.3%
21.27 1
0.1%
22.23 1
0.1%
22.65 2
0.3%
23.05 1
0.1%
23.08 1
0.1%
23.17 1
0.1%
23.21 1
0.1%
ValueCountFrequency (%)
87.31 1
0.1%
80.29 1
0.1%
79.27 1
0.1%
78.7 1
0.1%
77.92 1
0.1%
77.27 1
0.1%
75.68 1
0.1%
73.92 1
0.1%
73.72 1
0.1%
72.79 1
0.1%

부산 최대(Mbps)
Real number (ℝ)

MISSING 

Distinct537
Distinct (%)97.5%
Missing180
Missing (%)24.6%
Infinite0
Infinite (%)0.0%
Mean127.84969
Minimum61.66
Maximum342.73
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size6.6 KiB
2024-05-11T16:51:41.321924image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum61.66
5-th percentile79.275
Q198.625
median119.53
Q3154.14
95-th percentile191.625
Maximum342.73
Range281.07
Interquartile range (IQR)55.515

Descriptive statistics

Standard deviation38.550499
Coefficient of variation (CV)0.30152985
Kurtosis2.5459576
Mean127.84969
Median Absolute Deviation (MAD)25.96
Skewness1.1031384
Sum70445.18
Variance1486.1409
MonotonicityNot monotonic
2024-05-11T16:51:41.596339image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
99.43 3
 
0.4%
119.57 2
 
0.3%
149.5 2
 
0.3%
109.31 2
 
0.3%
108.95 2
 
0.3%
114.95 2
 
0.3%
119.53 2
 
0.3%
89.71 2
 
0.3%
159.85 2
 
0.3%
117.72 2
 
0.3%
Other values (527) 530
72.5%
(Missing) 180
 
24.6%
ValueCountFrequency (%)
61.66 1
0.1%
63.02 1
0.1%
64.34 1
0.1%
64.57 1
0.1%
66.04 1
0.1%
68.08 1
0.1%
68.77 1
0.1%
71.04 1
0.1%
71.78 1
0.1%
73.21 1
0.1%
ValueCountFrequency (%)
342.73 1
0.1%
331.09 1
0.1%
254.9 1
0.1%
251.9 1
0.1%
246.03 1
0.1%
239.61 1
0.1%
233.34 1
0.1%
228.98 1
0.1%
225.43 1
0.1%
222.0 1
0.1%

Interactions

2024-05-11T16:51:23.151455image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T16:50:26.531877image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T16:50:30.199058image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T16:50:33.422613image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T16:50:36.907070image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T16:50:40.340393image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T16:50:43.982093image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T16:50:47.101484image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T16:50:50.517733image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T16:50:54.132208image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T16:50:58.401616image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T16:51:03.114558image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T16:51:06.876885image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T16:51:11.128985image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T16:51:14.880258image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T16:51:18.646752image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T16:51:23.336520image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T16:50:26.766560image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T16:50:30.365067image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T16:50:33.600093image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T16:50:37.081154image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T16:50:40.514776image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T16:50:44.160275image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T16:50:47.293183image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T16:50:50.812595image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T16:50:54.268084image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T16:50:58.646675image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T16:51:03.293438image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T16:51:07.077469image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T16:51:11.339538image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T16:51:15.091130image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T16:51:18.868596image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T16:51:23.529900image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T16:50:26.972808image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T16:50:30.565058image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T16:50:33.866345image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T16:50:37.272925image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T16:50:40.747611image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T16:50:44.333415image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T16:50:47.462227image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T16:50:51.113355image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T16:50:54.467036image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T16:50:58.998157image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T16:51:03.484291image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T16:51:07.264607image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T16:51:11.551005image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T16:51:15.314985image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T16:51:19.084075image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T16:51:23.817228image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T16:50:27.194715image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T16:50:30.735228image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T16:50:34.207840image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T16:50:37.456827image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T16:50:40.961766image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T16:50:44.520772image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T16:50:47.621938image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T16:50:51.400489image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T16:50:54.628150image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T16:50:59.356612image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T16:51:03.665995image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T16:51:07.486710image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T16:51:11.820840image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T16:51:15.503272image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T16:51:19.400422image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T16:51:24.219503image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T16:50:27.372315image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T16:50:30.944667image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T16:50:34.418642image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T16:50:37.684499image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T16:50:41.664478image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T16:50:44.734151image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T16:50:47.817727image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T16:50:51.599165image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T16:50:54.818280image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T16:50:59.752764image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T16:51:03.855647image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T16:51:07.733964image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T16:51:12.037510image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T16:51:15.723514image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T16:51:19.708122image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T16:51:24.510504image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T16:50:27.574457image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T16:50:31.163210image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T16:50:34.638289image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T16:50:37.998187image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T16:50:41.873332image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T16:50:44.924637image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T16:50:48.016504image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T16:50:51.953001image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T16:50:55.565060image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T16:51:00.176821image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T16:51:04.058383image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T16:51:07.956902image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T16:51:12.284993image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T16:51:15.930521image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T16:51:20.055577image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T16:51:25.253474image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T16:50:27.797393image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T16:50:31.362480image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T16:50:34.804874image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T16:50:38.192380image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T16:50:42.052814image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T16:50:45.091887image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T16:50:48.419191image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T16:50:52.148100image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T16:50:55.747828image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T16:51:00.441008image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T16:51:04.281183image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T16:51:08.198835image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T16:51:12.525223image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T16:51:16.140524image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T16:51:20.394780image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T16:51:25.482317image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T16:50:27.957224image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T16:50:31.581235image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T16:50:34.969688image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T16:50:38.403148image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T16:50:42.226404image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T16:50:45.266441image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T16:50:48.706186image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T16:50:52.353604image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T16:50:55.978088image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T16:51:00.736371image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T16:51:04.482983image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T16:51:08.404302image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T16:51:12.725905image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T16:51:16.317621image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T16:51:20.641102image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T16:51:25.679390image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T16:50:28.112686image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T16:50:31.809384image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T16:50:35.149796image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T16:50:38.675589image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T16:50:42.395025image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T16:50:45.411968image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T16:50:48.838769image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T16:50:52.598632image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T16:50:56.144451image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T16:51:00.933015image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T16:51:04.662737image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T16:51:08.577410image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T16:51:12.936209image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T16:51:16.491180image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T16:51:20.867608image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T16:51:25.861518image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T16:50:28.639417image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T16:50:31.969838image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T16:50:35.321728image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T16:50:38.894446image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T16:50:42.564178image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T16:50:45.596665image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T16:50:48.982491image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T16:50:52.826817image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T16:50:56.417270image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T16:51:01.145965image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T16:51:04.857494image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T16:51:08.798778image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T16:51:13.130481image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T16:51:16.662056image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T16:51:21.083655image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T16:51:26.086949image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T16:50:28.810817image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T16:50:32.165347image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T16:50:35.518347image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T16:50:39.123429image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T16:50:42.759054image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T16:50:45.820482image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T16:50:49.145399image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T16:50:53.001547image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T16:50:56.652580image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T16:51:01.407058image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T16:51:05.239828image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T16:51:09.010835image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T16:51:13.428431image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T16:51:16.939167image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T16:51:21.303154image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T16:51:26.315289image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T16:50:29.007243image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T16:50:32.372679image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T16:50:35.722837image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T16:50:39.328056image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T16:50:42.941977image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T16:50:46.077904image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T16:50:49.384026image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T16:50:53.191449image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T16:50:56.862379image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T16:51:01.675024image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T16:51:05.531075image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T16:51:09.264369image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T16:51:13.725384image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T16:51:17.367230image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T16:51:21.563875image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T16:51:26.550379image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T16:50:29.289993image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T16:50:32.605228image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T16:50:35.894479image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T16:50:39.539170image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T16:50:43.118336image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T16:50:46.284573image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T16:50:49.607125image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T16:50:53.370573image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T16:50:57.132657image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T16:51:01.898077image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T16:51:05.786298image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T16:51:09.540026image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T16:51:13.949261image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T16:51:17.669101image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T16:51:21.887065image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T16:51:26.793064image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T16:50:29.542946image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T16:50:32.827849image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T16:50:36.130659image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T16:50:39.743972image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T16:50:43.304633image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T16:50:46.505769image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T16:50:49.840300image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T16:50:53.560914image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T16:50:57.492880image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T16:51:02.227516image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T16:51:06.047290image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T16:51:09.809928image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T16:51:14.179167image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T16:51:17.901840image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T16:51:22.176657image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T16:51:27.124396image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T16:50:29.734372image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T16:50:33.040995image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T16:50:36.373909image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T16:50:39.957545image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T16:50:43.569278image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T16:50:46.753792image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T16:50:50.093191image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T16:50:53.788788image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T16:50:57.834905image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T16:51:02.471766image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T16:51:06.331009image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T16:51:10.156332image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T16:51:14.432795image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T16:51:18.141407image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T16:51:22.608221image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T16:51:27.333520image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T16:50:29.991818image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T16:50:33.250021image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T16:50:36.656603image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T16:50:40.147984image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T16:50:43.772187image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T16:50:46.931027image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T16:50:50.293980image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T16:50:53.967541image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T16:50:58.142440image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T16:51:02.807653image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T16:51:06.660436image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T16:51:10.434227image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T16:51:14.676044image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T16:51:18.415749image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T16:51:22.871912image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-05-11T16:51:41.838527image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
본사 평균(Mbps)본사 최대(Mbps)하동 평균(Mbps)하동 최대(Mbps)남제주 평균(Mbps)남제주 최대(Mbps)인천 평균(Mbps)인천 최대(Mbps)영월 평균(Mbps)영월 최대(Mbps)안동 평균(Mbps)안동 최대(Mbps)삼척 평균(Mbps)삼척 최대(Mbps)부산 평균(Mbps)부산 최대(Mbps)
본사 평균(Mbps)1.0000.5620.3600.3580.0000.0940.8630.5240.1240.3120.4160.5350.6830.4460.2500.116
본사 최대(Mbps)0.5621.0000.3370.2380.1940.1440.6300.6630.2950.5750.2780.3560.3380.3560.0000.243
하동 평균(Mbps)0.3600.3371.0000.8260.7490.3760.7690.3850.6720.4070.4860.4010.6260.6270.6700.230
하동 최대(Mbps)0.3580.2380.8261.0000.5070.7450.6020.4540.5710.5730.4410.4510.5510.5840.4160.520
남제주 평균(Mbps)0.0000.1940.7490.5071.0000.5740.4270.3260.7150.3270.6020.6130.7530.7350.6890.337
남제주 최대(Mbps)0.0940.1440.3760.7450.5741.0000.3450.3500.4570.5200.4290.3590.5310.5680.3780.521
인천 평균(Mbps)0.8630.6300.7690.6020.4270.3451.0000.6650.3610.5930.3870.4250.6110.5060.4970.000
인천 최대(Mbps)0.5240.6630.3850.4540.3260.3500.6651.0000.2440.4950.3240.2220.3400.3460.3070.728
영월 평균(Mbps)0.1240.2950.6720.5710.7150.4570.3610.2441.0000.6500.5780.5270.7220.7330.6700.327
영월 최대(Mbps)0.3120.5750.4070.5730.3270.5200.5930.4950.6501.0000.1990.2130.3590.4180.2380.366
안동 평균(Mbps)0.4160.2780.4860.4410.6020.4290.3870.3240.5780.1991.0000.8510.7070.7070.7420.245
안동 최대(Mbps)0.5350.3560.4010.4510.6130.3590.4250.2220.5270.2130.8511.0000.6750.6870.5030.216
삼척 평균(Mbps)0.6830.3380.6260.5510.7530.5310.6110.3400.7220.3590.7070.6751.0000.8610.7130.283
삼척 최대(Mbps)0.4460.3560.6270.5840.7350.5680.5060.3460.7330.4180.7070.6870.8611.0000.7200.302
부산 평균(Mbps)0.2500.0000.6700.4160.6890.3780.4970.3070.6700.2380.7420.5030.7130.7201.0000.461
부산 최대(Mbps)0.1160.2430.2300.5200.3370.5210.0000.7280.3270.3660.2450.2160.2830.3020.4611.000
2024-05-11T16:51:42.207219image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
본사 평균(Mbps)본사 최대(Mbps)하동 평균(Mbps)하동 최대(Mbps)남제주 평균(Mbps)남제주 최대(Mbps)인천 평균(Mbps)인천 최대(Mbps)영월 평균(Mbps)영월 최대(Mbps)안동 평균(Mbps)안동 최대(Mbps)삼척 평균(Mbps)삼척 최대(Mbps)부산 평균(Mbps)부산 최대(Mbps)
본사 평균(Mbps)1.0000.3840.2180.2450.1570.1620.064-0.1040.1490.1430.3170.3120.3430.3060.078-0.089
본사 최대(Mbps)0.3841.0000.2890.3000.1300.0950.2950.1560.1190.1570.2070.1890.2600.318-0.015-0.155
하동 평균(Mbps)0.2180.2891.0000.8780.5620.3910.5110.2250.4880.3920.5700.5030.6370.6680.449-0.002
하동 최대(Mbps)0.2450.3000.8781.0000.5270.4390.4670.1940.4990.4240.5910.5380.6230.6980.4300.003
남제주 평균(Mbps)0.1570.1300.5620.5271.0000.6610.3630.1310.3830.2810.5330.4740.5510.5510.4250.001
남제주 최대(Mbps)0.1620.0950.3910.4390.6611.0000.2870.0560.2980.2540.4010.3900.4390.4950.2920.113
인천 평균(Mbps)0.0640.2950.5110.4670.3630.2871.0000.7040.4530.4250.3400.2910.3480.4000.3100.069
인천 최대(Mbps)-0.1040.1560.2250.1940.1310.0560.7041.0000.1620.1860.0940.0520.0980.1330.1580.315
영월 평균(Mbps)0.1490.1190.4880.4990.3830.2980.4530.1621.0000.7910.4090.4200.4730.5490.4150.025
영월 최대(Mbps)0.1430.1570.3920.4240.2810.2540.4250.1860.7911.0000.2430.2770.3170.4230.2760.044
안동 평균(Mbps)0.3170.2070.5700.5910.5330.4010.3400.0940.4090.2431.0000.8650.7070.6470.468-0.089
안동 최대(Mbps)0.3120.1890.5030.5380.4740.3900.2910.0520.4200.2770.8651.0000.6330.6010.386-0.078
삼척 평균(Mbps)0.3430.2600.6370.6230.5510.4390.3480.0980.4730.3170.7070.6331.0000.8310.407-0.087
삼척 최대(Mbps)0.3060.3180.6680.6980.5510.4950.4000.1330.5490.4230.6470.6010.8311.0000.438-0.080
부산 평균(Mbps)0.078-0.0150.4490.4300.4250.2920.3100.1580.4150.2760.4680.3860.4070.4381.0000.386
부산 최대(Mbps)-0.089-0.155-0.0020.0030.0010.1130.0690.3150.0250.044-0.089-0.078-0.087-0.0800.3861.000

Missing values

2024-05-11T16:51:27.625371image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-05-11T16:51:28.167133image/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.
2024-05-11T16:51:28.705841image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
The correlation heatmap measures nullity correlation: how strongly the presence or absence of one variable affects the presence of another.

Sample

구분본사 평균(Mbps)본사 최대(Mbps)하동 평균(Mbps)하동 최대(Mbps)남제주 평균(Mbps)남제주 최대(Mbps)인천 평균(Mbps)인천 최대(Mbps)영월 평균(Mbps)영월 최대(Mbps)안동 평균(Mbps)안동 최대(Mbps)삼척 평균(Mbps)삼척 최대(Mbps)부산 평균(Mbps)부산 최대(Mbps)
02022-05-0196.48486.6860.37128.7145.27111.0335.3373.215.524.816.1645.1424.5862.8632.5184.7
12022-05-02118.2659.4395.6274.261.27128.8541.8996.0815.5161.6722.0267.5932.487.7338.89201.11
22022-05-03135.47716.4391.26212.3957.59131.246.88123.520.1666.4722.8565.9530.2586.3242.88131.7
32022-05-04127.36643.5589.48267.5851.26126.048.19114.1316.6557.2424.9798.4230.4385.6251.56117.79
42022-05-0594.09601.2777.47156.3948.11105.4729.4484.36.9248.4713.6538.0115.0150.1344.7399.89
52022-05-06115.54587.2688.06222.0348.2120.3439.61103.168.1935.7726.5976.437.4990.0940.95118.23
62022-05-07114.13592.3880.34146.2954.27108.9542.29148.389.4433.1113.0751.3120.1957.1642.72194.96
72022-05-08101.66433.1270.63136.5647.7102.1237.99106.9217.6967.817.057.9514.9544.948.85116.23
82022-05-09112.95594.3186.45171.5645.03128.8240.0492.4716.6269.8429.7496.5430.2185.5648.3147.46
92022-05-10170.36671.4791.79266.1655.19141.2743.7699.6315.7754.0227.4281.5332.34102.1454.87141.81
구분본사 평균(Mbps)본사 최대(Mbps)하동 평균(Mbps)하동 최대(Mbps)남제주 평균(Mbps)남제주 최대(Mbps)인천 평균(Mbps)인천 최대(Mbps)영월 평균(Mbps)영월 최대(Mbps)안동 평균(Mbps)안동 최대(Mbps)삼척 평균(Mbps)삼척 최대(Mbps)부산 평균(Mbps)부산 최대(Mbps)
7212024-04-2179.86599.7593.03192.9845.17125.5279.86599.755.5838.265.8233.4324.3469.9536.26142.41
7222024-04-22106.7673.13156.83451.4859.21147.69106.7673.1323.4484.4630.38103.4549.08146.9155.58154.13
7232024-04-2376.99638.31125.78267.9547.57121.876.99638.3120.0262.1730.62105.8247.17141.2944.7112.58
7242024-04-24114.45666.56131.28350.2141.89107.63114.45666.5614.3564.0520.0779.5939.51117.1242.28117.72
7252024-04-2582.58590.81121.21330.2650.67130.9682.58590.8120.5372.0622.1179.2941.57104.6341.95113.81
7262024-04-2695.39693.05104.29244.1163.3143.7695.39693.059.7957.5924.293.4632.193.1630.5492.48
7272024-04-27104.29802.8893.81188.845.15110.16104.29802.887.8140.998.6334.4222.9165.5623.08190.3
7282024-04-2861.34751.9581.5177.2934.8596.761.34751.956.0832.818.0952.7919.4757.3531.28145.49
7292024-04-2994.97531.2195.33244.2253.17131.7994.97531.2119.5659.2632.3996.842.16126.0957.35144.8
7302024-04-3095.56672.7492.37172.6644.82105.3495.56672.7414.662.1120.9969.3542.29134.3953.36158.16