Overview

Dataset statistics

Number of variables18
Number of observations10000
Missing cells0
Missing cells (%)0.0%
Duplicate rows43
Duplicate rows (%)0.4%
Total size in memory1.6 MiB
Average record size in memory168.0 B

Variable types

Text1
Categorical1
Numeric16

Alerts

Dataset has 43 (0.4%) duplicate rowsDuplicates
3시간이후 is highly overall correlated with 6시간이후 and 13 other fieldsHigh correlation
6시간이후 is highly overall correlated with 3시간이후 and 13 other fieldsHigh correlation
9시간이후 is highly overall correlated with 3시간이후 and 14 other fieldsHigh correlation
12시간이후 is highly overall correlated with 3시간이후 and 14 other fieldsHigh correlation
15시간이후 is highly overall correlated with 3시간이후 and 14 other fieldsHigh correlation
18시간이후 is highly overall correlated with 3시간이후 and 14 other fieldsHigh correlation
21시간이후 is highly overall correlated with 3시간이후 and 14 other fieldsHigh correlation
24시간이후 is highly overall correlated with 3시간이후 and 14 other fieldsHigh correlation
27시간이후 is highly overall correlated with 3시간이후 and 14 other fieldsHigh correlation
30시간이후 is highly overall correlated with 3시간이후 and 14 other fieldsHigh correlation
33시간이후 is highly overall correlated with 3시간이후 and 14 other fieldsHigh correlation
36시간이후 is highly overall correlated with 3시간이후 and 14 other fieldsHigh correlation
39시간이후 is highly overall correlated with 3시간이후 and 14 other fieldsHigh correlation
42시간이후 is highly overall correlated with 3시간이후 and 14 other fieldsHigh correlation
45시간이후 is highly overall correlated with 3시간이후 and 14 other fieldsHigh correlation
48시간이후 is highly overall correlated with 9시간이후 and 12 other fieldsHigh correlation
3시간이후 has 578 (5.8%) zerosZeros
6시간이후 has 521 (5.2%) zerosZeros
9시간이후 has 442 (4.4%) zerosZeros
12시간이후 has 317 (3.2%) zerosZeros
15시간이후 has 258 (2.6%) zerosZeros
18시간이후 has 394 (3.9%) zerosZeros
21시간이후 has 580 (5.8%) zerosZeros
24시간이후 has 557 (5.6%) zerosZeros
27시간이후 has 597 (6.0%) zerosZeros
30시간이후 has 565 (5.7%) zerosZeros
33시간이후 has 475 (4.8%) zerosZeros
36시간이후 has 913 (9.1%) zerosZeros
39시간이후 has 791 (7.9%) zerosZeros
42시간이후 has 837 (8.4%) zerosZeros
45시간이후 has 1093 (10.9%) zerosZeros
48시간이후 has 955 (9.6%) zerosZeros

Reproduction

Analysis started2023-12-10 21:02:12.700181
Analysis finished2023-12-10 21:02:56.218952
Duration43.52 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

Distinct225
Distinct (%)2.2%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2023-12-11T06:02:56.458458image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length14
Median length14
Mean length14
Min length14

Characters and Unicode

Total characters140000
Distinct characters13
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2019-12-31 00시
2nd row2019-12-23 00시
3rd row2020-03-14 00시
4th row2020-03-15 00시
5th row2019-03-16 00시
ValueCountFrequency (%)
00시 10000
50.0%
2019-12-31 1794
 
9.0%
2020-02-26 42
 
0.2%
2020-03-16 41
 
0.2%
2020-03-15 41
 
0.2%
2019-01-19 41
 
0.2%
2019-03-16 41
 
0.2%
2019-11-16 41
 
0.2%
2019-12-03 41
 
0.2%
2020-03-31 41
 
0.2%
Other values (216) 7877
39.4%
2023-12-11T06:02:57.014965image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 39412
28.2%
1 21281
15.2%
2 20694
14.8%
- 20000
14.3%
10000
 
7.1%
10000
 
7.1%
9 8079
 
5.8%
3 5244
 
3.7%
8 2089
 
1.5%
4 813
 
0.6%
Other values (3) 2388
 
1.7%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 100000
71.4%
Dash Punctuation 20000
 
14.3%
Space Separator 10000
 
7.1%
Other Letter 10000
 
7.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 39412
39.4%
1 21281
21.3%
2 20694
20.7%
9 8079
 
8.1%
3 5244
 
5.2%
8 2089
 
2.1%
4 813
 
0.8%
7 808
 
0.8%
5 800
 
0.8%
6 780
 
0.8%
Dash Punctuation
ValueCountFrequency (%)
- 20000
100.0%
Space Separator
ValueCountFrequency (%)
10000
100.0%
Other Letter
ValueCountFrequency (%)
10000
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 130000
92.9%
Hangul 10000
 
7.1%

Most frequent character per script

Common
ValueCountFrequency (%)
0 39412
30.3%
1 21281
16.4%
2 20694
15.9%
- 20000
15.4%
10000
 
7.7%
9 8079
 
6.2%
3 5244
 
4.0%
8 2089
 
1.6%
4 813
 
0.6%
7 808
 
0.6%
Other values (2) 1580
 
1.2%
Hangul
ValueCountFrequency (%)
10000
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 130000
92.9%
Hangul 10000
 
7.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 39412
30.3%
1 21281
16.4%
2 20694
15.9%
- 20000
15.4%
10000
 
7.7%
9 8079
 
6.2%
3 5244
 
4.0%
8 2089
 
1.6%
4 813
 
0.6%
7 808
 
0.6%
Other values (2) 1580
 
1.2%
Hangul
ValueCountFrequency (%)
10000
100.0%

지점명
Categorical

Distinct43
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
경기도 부천시
 
242
경기도 양평군
 
240
경기도 군포시
 
239
경기도 수원시 장안구
 
239
경기도 성남시 분당구
 
238
Other values (38)
8802 

Length

Max length12
Median length7
Mean length8.6294
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row경기도 안양시 만안구
2nd row경기도 군포시
3rd row경기도 안성시
4th row경기도 남양주시
5th row경기도 동두천시

Common Values

ValueCountFrequency (%)
경기도 부천시 242
 
2.4%
경기도 양평군 240
 
2.4%
경기도 군포시 239
 
2.4%
경기도 수원시 장안구 239
 
2.4%
경기도 성남시 분당구 238
 
2.4%
경기도 고양시 일산서구 237
 
2.4%
경기도 안성시 237
 
2.4%
경기도 하남시 237
 
2.4%
경기도 평택시 236
 
2.4%
경기도 수원시 팔달구 236
 
2.4%
Other values (33) 7619
76.2%

Length

2023-12-11T06:02:57.230261image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
경기도 10000
42.1%
수원시 942
 
4.0%
용인시 700
 
3.0%
고양시 697
 
2.9%
성남시 694
 
2.9%
안양시 464
 
2.0%
안산시 458
 
1.9%
부천시 242
 
1.0%
양평군 240
 
1.0%
장안구 239
 
1.0%
Other values (39) 9051
38.1%

3시간이후
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct41
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean-4.3697
Minimum-26
Maximum14
Zeros578
Zeros (%)5.8%
Negative6300
Negative (%)63.0%
Memory size166.0 KiB
2023-12-11T06:02:57.404613image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum-26
5-th percentile-18
Q1-11
median-3
Q32
95-th percentile7
Maximum14
Range40
Interquartile range (IQR)13

Descriptive statistics

Standard deviation8.1719214
Coefficient of variation (CV)-1.8701333
Kurtosis-0.87619915
Mean-4.3697
Median Absolute Deviation (MAD)6
Skewness-0.31644522
Sum-43697
Variance66.7803
MonotonicityNot monotonic
2023-12-11T06:02:57.565459image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=41)
ValueCountFrequency (%)
-17 639
 
6.4%
-2 598
 
6.0%
0 578
 
5.8%
-1 551
 
5.5%
1 534
 
5.3%
-3 530
 
5.3%
-4 486
 
4.9%
2 457
 
4.6%
-15 454
 
4.5%
3 442
 
4.4%
Other values (31) 4731
47.3%
ValueCountFrequency (%)
-26 2
 
< 0.1%
-25 1
 
< 0.1%
-24 3
 
< 0.1%
-23 5
 
0.1%
-22 8
 
0.1%
-21 49
 
0.5%
-20 97
 
1.0%
-19 177
 
1.8%
-18 303
3.0%
-17 639
6.4%
ValueCountFrequency (%)
14 14
 
0.1%
13 30
 
0.3%
12 35
 
0.4%
11 48
 
0.5%
10 86
 
0.9%
9 111
 
1.1%
8 145
1.5%
7 212
2.1%
6 271
2.7%
5 338
3.4%

6시간이후
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct40
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean-5.247
Minimum-25
Maximum14
Zeros521
Zeros (%)5.2%
Negative6774
Negative (%)67.7%
Memory size166.0 KiB
2023-12-11T06:02:57.760378image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum-25
5-th percentile-19
Q1-11
median-4
Q31
95-th percentile7
Maximum14
Range39
Interquartile range (IQR)12

Descriptive statistics

Standard deviation8.2832513
Coefficient of variation (CV)-1.5786642
Kurtosis-0.89345328
Mean-5.247
Median Absolute Deviation (MAD)6
Skewness-0.34433651
Sum-52470
Variance68.612252
MonotonicityNot monotonic
2023-12-11T06:02:57.959117image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=40)
ValueCountFrequency (%)
-2 618
 
6.2%
-19 611
 
6.1%
-1 580
 
5.8%
-3 567
 
5.7%
-18 543
 
5.4%
0 521
 
5.2%
-4 487
 
4.9%
1 482
 
4.8%
2 457
 
4.6%
3 414
 
4.1%
Other values (30) 4720
47.2%
ValueCountFrequency (%)
-25 1
 
< 0.1%
-24 1
 
< 0.1%
-23 5
 
0.1%
-22 9
 
0.1%
-21 133
 
1.3%
-20 181
 
1.8%
-19 611
6.1%
-18 543
5.4%
-17 227
 
2.3%
-16 291
2.9%
ValueCountFrequency (%)
14 1
 
< 0.1%
13 6
 
0.1%
12 27
 
0.3%
11 28
 
0.3%
10 40
 
0.4%
9 107
1.1%
8 185
1.8%
7 171
1.7%
6 195
1.9%
5 247
2.5%

9시간이후
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct40
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean-3.6317
Minimum-24
Maximum15
Zeros442
Zeros (%)4.4%
Negative5463
Negative (%)54.6%
Memory size166.0 KiB
2023-12-11T06:02:58.144163image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum-24
5-th percentile-19
Q1-9
median-1
Q33
95-th percentile9
Maximum15
Range39
Interquartile range (IQR)12

Descriptive statistics

Standard deviation9.1240989
Coefficient of variation (CV)-2.5123493
Kurtosis-0.85385143
Mean-3.6317
Median Absolute Deviation (MAD)6
Skewness-0.50472925
Sum-36317
Variance83.24918
MonotonicityNot monotonic
2023-12-11T06:02:58.330848image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=40)
ValueCountFrequency (%)
-18 1050
 
10.5%
3 600
 
6.0%
2 574
 
5.7%
1 549
 
5.5%
4 508
 
5.1%
-1 469
 
4.7%
-2 448
 
4.5%
0 442
 
4.4%
5 398
 
4.0%
-19 353
 
3.5%
Other values (30) 4609
46.1%
ValueCountFrequency (%)
-24 41
 
0.4%
-23 43
 
0.4%
-22 2
 
< 0.1%
-21 93
 
0.9%
-20 253
 
2.5%
-19 353
 
3.5%
-18 1050
10.5%
-17 12
 
0.1%
-16 86
 
0.9%
-15 58
 
0.6%
ValueCountFrequency (%)
15 1
 
< 0.1%
14 4
 
< 0.1%
13 25
 
0.2%
12 52
 
0.5%
11 104
 
1.0%
10 142
1.4%
9 208
2.1%
8 275
2.8%
7 341
3.4%
6 314
3.1%

12시간이후
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct38
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.9734
Minimum-19
Maximum19
Zeros317
Zeros (%)3.2%
Negative3714
Negative (%)37.1%
Memory size166.0 KiB
2023-12-11T06:02:58.526709image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum-19
5-th percentile-13
Q1-5
median3
Q37
95-th percentile14
Maximum19
Range38
Interquartile range (IQR)12

Descriptive statistics

Standard deviation8.7367457
Coefficient of variation (CV)8.9754938
Kurtosis-0.92899277
Mean0.9734
Median Absolute Deviation (MAD)6
Skewness-0.33115844
Sum9734
Variance76.330726
MonotonicityNot monotonic
2023-12-11T06:02:58.720282image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=38)
ValueCountFrequency (%)
-12 792
 
7.9%
-13 616
 
6.2%
3 550
 
5.5%
4 543
 
5.4%
5 519
 
5.2%
7 483
 
4.8%
6 478
 
4.8%
2 462
 
4.6%
1 439
 
4.4%
8 431
 
4.3%
Other values (28) 4687
46.9%
ValueCountFrequency (%)
-19 1
 
< 0.1%
-17 49
 
0.5%
-16 14
 
0.1%
-15 136
 
1.4%
-14 238
 
2.4%
-13 616
6.2%
-12 792
7.9%
-11 123
 
1.2%
-10 39
 
0.4%
-9 51
 
0.5%
ValueCountFrequency (%)
19 3
 
< 0.1%
18 32
 
0.3%
17 57
 
0.6%
16 125
 
1.2%
15 136
1.4%
14 149
1.5%
13 283
2.8%
12 293
2.9%
11 320
3.2%
10 276
2.8%

15시간이후
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct37
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2.7957
Minimum-16
Maximum20
Zeros258
Zeros (%)2.6%
Negative3295
Negative (%)33.0%
Memory size166.0 KiB
2023-12-11T06:02:58.871628image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum-16
5-th percentile-11
Q1-3
median4
Q39
95-th percentile16
Maximum20
Range36
Interquartile range (IQR)12

Descriptive statistics

Standard deviation8.2797112
Coefficient of variation (CV)2.9615879
Kurtosis-0.94815146
Mean2.7957
Median Absolute Deviation (MAD)6
Skewness-0.16682131
Sum27957
Variance68.553617
MonotonicityNot monotonic
2023-12-11T06:02:59.030749image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=37)
ValueCountFrequency (%)
-9 996
 
10.0%
5 590
 
5.9%
4 569
 
5.7%
3 538
 
5.4%
6 502
 
5.0%
2 426
 
4.3%
8 402
 
4.0%
-11 402
 
4.0%
7 388
 
3.9%
9 388
 
3.9%
Other values (27) 4799
48.0%
ValueCountFrequency (%)
-16 4
 
< 0.1%
-15 13
 
0.1%
-14 19
 
0.2%
-13 42
 
0.4%
-12 46
 
0.5%
-11 402
4.0%
-10 298
 
3.0%
-9 996
10.0%
-8 194
 
1.9%
-7 60
 
0.6%
ValueCountFrequency (%)
20 7
 
0.1%
19 52
 
0.5%
18 129
 
1.3%
17 133
 
1.3%
16 185
1.8%
15 273
2.7%
14 282
2.8%
13 270
2.7%
12 329
3.3%
11 336
3.4%

18시간이후
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct39
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1.2842
Minimum-20
Maximum18
Zeros394
Zeros (%)3.9%
Negative3918
Negative (%)39.2%
Memory size166.0 KiB
2023-12-11T06:02:59.205797image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum-20
5-th percentile-10
Q1-5
median2
Q37
95-th percentile13
Maximum18
Range38
Interquartile range (IQR)12

Descriptive statistics

Standard deviation7.4063024
Coefficient of variation (CV)5.76725
Kurtosis-0.89355387
Mean1.2842
Median Absolute Deviation (MAD)6
Skewness-0.051905006
Sum12842
Variance54.853316
MonotonicityNot monotonic
2023-12-11T06:02:59.376077image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=39)
ValueCountFrequency (%)
-9 652
 
6.5%
-8 649
 
6.5%
3 622
 
6.2%
2 568
 
5.7%
4 511
 
5.1%
5 504
 
5.0%
1 494
 
4.9%
0 394
 
3.9%
10 382
 
3.8%
-1 376
 
3.8%
Other values (29) 4848
48.5%
ValueCountFrequency (%)
-20 1
 
< 0.1%
-19 13
 
0.1%
-18 10
 
0.1%
-17 12
 
0.1%
-16 3
 
< 0.1%
-15 8
 
0.1%
-14 20
 
0.2%
-13 49
 
0.5%
-12 128
1.3%
-11 73
0.7%
ValueCountFrequency (%)
18 3
 
< 0.1%
17 23
 
0.2%
16 67
 
0.7%
15 129
 
1.3%
14 194
1.9%
13 215
2.1%
12 299
3.0%
11 343
3.4%
10 382
3.8%
9 295
2.9%

21시간이후
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct38
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean-0.5164
Minimum-22
Maximum15
Zeros580
Zeros (%)5.8%
Negative4858
Negative (%)48.6%
Memory size166.0 KiB
2023-12-11T06:02:59.793969image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum-22
5-th percentile-10
Q1-6
median0
Q34
95-th percentile10
Maximum15
Range37
Interquartile range (IQR)10

Descriptive statistics

Standard deviation6.3766604
Coefficient of variation (CV)-12.348297
Kurtosis-0.63606447
Mean-0.5164
Median Absolute Deviation (MAD)5
Skewness-0.037776261
Sum-5164
Variance40.661797
MonotonicityNot monotonic
2023-12-11T06:02:59.931406image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=38)
ValueCountFrequency (%)
-6 863
 
8.6%
-7 664
 
6.6%
1 614
 
6.1%
-8 581
 
5.8%
0 580
 
5.8%
2 571
 
5.7%
3 515
 
5.1%
-1 482
 
4.8%
-2 462
 
4.6%
4 441
 
4.4%
Other values (28) 4227
42.3%
ValueCountFrequency (%)
-22 1
 
< 0.1%
-21 6
 
0.1%
-20 6
 
0.1%
-19 8
 
0.1%
-18 13
 
0.1%
-17 9
 
0.1%
-16 18
 
0.2%
-15 38
0.4%
-14 69
0.7%
-13 72
0.7%
ValueCountFrequency (%)
15 3
 
< 0.1%
14 19
 
0.2%
13 54
 
0.5%
12 113
 
1.1%
11 183
1.8%
10 201
2.0%
9 277
2.8%
8 341
3.4%
7 401
4.0%
6 401
4.0%

24시간이후
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct40
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean-1.9132
Minimum-23
Maximum16
Zeros557
Zeros (%)5.6%
Negative5701
Negative (%)57.0%
Memory size166.0 KiB
2023-12-11T06:03:00.085245image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum-23
5-th percentile-12
Q1-7
median-2
Q33
95-th percentile8
Maximum16
Range39
Interquartile range (IQR)10

Descriptive statistics

Standard deviation6.2696728
Coefficient of variation (CV)-3.2770608
Kurtosis-0.46831068
Mean-1.9132
Median Absolute Deviation (MAD)5
Skewness-0.070159452
Sum-19132
Variance39.308797
MonotonicityNot monotonic
2023-12-11T06:03:00.213175image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=40)
ValueCountFrequency (%)
-7 900
 
9.0%
-8 653
 
6.5%
-1 627
 
6.3%
1 620
 
6.2%
-2 602
 
6.0%
2 560
 
5.6%
0 557
 
5.6%
-3 499
 
5.0%
3 431
 
4.3%
4 429
 
4.3%
Other values (30) 4122
41.2%
ValueCountFrequency (%)
-23 1
 
< 0.1%
-22 4
 
< 0.1%
-21 8
 
0.1%
-20 9
 
0.1%
-19 17
 
0.2%
-18 12
 
0.1%
-17 36
0.4%
-16 59
0.6%
-15 86
0.9%
-14 79
0.8%
ValueCountFrequency (%)
16 7
 
0.1%
15 16
 
0.2%
14 5
 
0.1%
13 8
 
0.1%
12 22
 
0.2%
11 58
 
0.6%
10 120
1.2%
9 197
2.0%
8 242
2.4%
7 273
2.7%

27시간이후
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct39
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean-2.5325
Minimum-24
Maximum14
Zeros597
Zeros (%)6.0%
Negative6342
Negative (%)63.4%
Memory size166.0 KiB
2023-12-11T06:03:00.329819image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum-24
5-th percentile-13
Q1-6
median-3
Q31
95-th percentile7
Maximum14
Range38
Interquartile range (IQR)7

Descriptive statistics

Standard deviation5.9281918
Coefficient of variation (CV)-2.3408457
Kurtosis0.092866143
Mean-2.5325
Median Absolute Deviation (MAD)4
Skewness-0.19215514
Sum-25325
Variance35.143458
MonotonicityNot monotonic
2023-12-11T06:03:00.438412image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=39)
ValueCountFrequency (%)
-6 900
 
9.0%
-5 704
 
7.0%
-2 652
 
6.5%
-1 629
 
6.3%
0 597
 
6.0%
-3 585
 
5.9%
-4 579
 
5.8%
1 575
 
5.8%
-7 572
 
5.7%
-8 460
 
4.6%
Other values (29) 3747
37.5%
ValueCountFrequency (%)
-24 2
 
< 0.1%
-23 2
 
< 0.1%
-22 4
 
< 0.1%
-21 16
 
0.2%
-20 24
 
0.2%
-19 30
 
0.3%
-18 46
0.5%
-17 66
0.7%
-16 74
0.7%
-15 89
0.9%
ValueCountFrequency (%)
14 1
 
< 0.1%
13 10
 
0.1%
12 17
 
0.2%
11 21
 
0.2%
10 87
 
0.9%
9 109
 
1.1%
8 222
2.2%
7 219
2.2%
6 275
2.8%
5 319
3.2%

30시간이후
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct38
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean-2.9577
Minimum-25
Maximum12
Zeros565
Zeros (%)5.7%
Negative6834
Negative (%)68.3%
Memory size166.0 KiB
2023-12-11T06:03:00.557971image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum-25
5-th percentile-13
Q1-6
median-3
Q31
95-th percentile7
Maximum12
Range37
Interquartile range (IQR)7

Descriptive statistics

Standard deviation5.6771589
Coefficient of variation (CV)-1.9194506
Kurtosis0.3636008
Mean-2.9577
Median Absolute Deviation (MAD)3
Skewness-0.22730052
Sum-29577
Variance32.230134
MonotonicityNot monotonic
2023-12-11T06:03:00.664730image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=38)
ValueCountFrequency (%)
-5 1078
 
10.8%
-4 749
 
7.5%
-6 728
 
7.3%
-2 690
 
6.9%
-7 650
 
6.5%
-3 643
 
6.4%
-1 636
 
6.4%
0 565
 
5.7%
1 431
 
4.3%
2 405
 
4.0%
Other values (28) 3425
34.2%
ValueCountFrequency (%)
-25 2
 
< 0.1%
-24 1
 
< 0.1%
-23 2
 
< 0.1%
-22 10
 
0.1%
-21 27
 
0.3%
-20 15
 
0.1%
-19 30
 
0.3%
-18 61
0.6%
-17 58
0.6%
-16 81
0.8%
ValueCountFrequency (%)
12 2
 
< 0.1%
11 9
 
0.1%
10 34
 
0.3%
9 121
 
1.2%
8 198
2.0%
7 180
1.8%
6 197
2.0%
5 285
2.9%
4 357
3.6%
3 382
3.8%

33시간이후
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct40
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean-0.9566
Minimum-24
Maximum15
Zeros475
Zeros (%)4.8%
Negative5475
Negative (%)54.8%
Memory size166.0 KiB
2023-12-11T06:03:00.772135image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum-24
5-th percentile-10
Q1-5
median-1
Q33
95-th percentile9
Maximum15
Range39
Interquartile range (IQR)8

Descriptive statistics

Standard deviation5.9683397
Coefficient of variation (CV)-6.2391174
Kurtosis0.127914
Mean-0.9566
Median Absolute Deviation (MAD)4
Skewness-0.19383112
Sum-9566
Variance35.621079
MonotonicityNot monotonic
2023-12-11T06:03:00.875969image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=40)
ValueCountFrequency (%)
-3 947
 
9.5%
-4 836
 
8.4%
-2 594
 
5.9%
-6 570
 
5.7%
3 563
 
5.6%
4 532
 
5.3%
1 527
 
5.3%
2 527
 
5.3%
-5 514
 
5.1%
-1 493
 
4.9%
Other values (30) 3897
39.0%
ValueCountFrequency (%)
-24 1
 
< 0.1%
-23 1
 
< 0.1%
-22 5
 
0.1%
-21 8
 
0.1%
-20 24
0.2%
-19 25
0.2%
-18 42
0.4%
-17 19
0.2%
-16 29
0.3%
-15 34
0.3%
ValueCountFrequency (%)
15 1
 
< 0.1%
14 11
 
0.1%
13 28
 
0.3%
12 54
 
0.5%
11 87
 
0.9%
10 173
1.7%
9 231
2.3%
8 292
2.9%
7 285
2.9%
6 329
3.3%

36시간이후
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct38
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean3.3238
Minimum-17
Maximum20
Zeros913
Zeros (%)9.1%
Negative2377
Negative (%)23.8%
Memory size166.0 KiB
2023-12-11T06:03:00.977890image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum-17
5-th percentile-6
Q10
median3
Q38
95-th percentile14
Maximum20
Range37
Interquartile range (IQR)8

Descriptive statistics

Standard deviation6.2051756
Coefficient of variation (CV)1.866892
Kurtosis-0.044993147
Mean3.3238
Median Absolute Deviation (MAD)4
Skewness-0.041349972
Sum33238
Variance38.504204
MonotonicityNot monotonic
2023-12-11T06:03:01.098033image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=38)
ValueCountFrequency (%)
1 1207
 
12.1%
0 913
 
9.1%
4 528
 
5.3%
-1 519
 
5.2%
3 491
 
4.9%
5 480
 
4.8%
8 473
 
4.7%
2 472
 
4.7%
7 442
 
4.4%
6 439
 
4.4%
Other values (28) 4036
40.4%
ValueCountFrequency (%)
-17 4
 
< 0.1%
-16 13
 
0.1%
-15 26
 
0.3%
-14 40
0.4%
-13 37
0.4%
-12 36
0.4%
-11 24
 
0.2%
-10 29
 
0.3%
-9 83
0.8%
-8 76
0.8%
ValueCountFrequency (%)
20 3
 
< 0.1%
19 18
 
0.2%
18 32
 
0.3%
17 48
 
0.5%
16 101
 
1.0%
15 159
1.6%
14 218
2.2%
13 254
2.5%
12 290
2.9%
11 297
3.0%

39시간이후
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct37
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean4.6886
Minimum-15
Maximum21
Zeros791
Zeros (%)7.9%
Negative1663
Negative (%)16.6%
Memory size166.0 KiB
2023-12-11T06:03:01.210906image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum-15
5-th percentile-5
Q11
median4
Q39
95-th percentile16
Maximum21
Range36
Interquartile range (IQR)8

Descriptive statistics

Standard deviation6.2768758
Coefficient of variation (CV)1.3387527
Kurtosis-0.22760886
Mean4.6886
Median Absolute Deviation (MAD)4
Skewness0.11665282
Sum46886
Variance39.39917
MonotonicityNot monotonic
2023-12-11T06:03:01.325790image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=37)
ValueCountFrequency (%)
1 1034
 
10.3%
2 879
 
8.8%
0 791
 
7.9%
4 547
 
5.5%
5 543
 
5.4%
3 481
 
4.8%
6 477
 
4.8%
9 411
 
4.1%
8 398
 
4.0%
10 397
 
4.0%
Other values (27) 4042
40.4%
ValueCountFrequency (%)
-15 9
 
0.1%
-14 16
 
0.2%
-13 12
 
0.1%
-12 28
 
0.3%
-11 35
 
0.4%
-10 50
0.5%
-9 60
0.6%
-8 23
 
0.2%
-7 61
0.6%
-6 98
1.0%
ValueCountFrequency (%)
21 11
 
0.1%
20 13
 
0.1%
19 41
 
0.4%
18 92
 
0.9%
17 187
1.9%
16 202
2.0%
15 253
2.5%
14 273
2.7%
13 297
3.0%
12 283
2.8%

42시간이후
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct40
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2.9027
Minimum-20
Maximum19
Zeros837
Zeros (%)8.4%
Negative2626
Negative (%)26.3%
Memory size166.0 KiB
2023-12-11T06:03:01.455121image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum-20
5-th percentile-7
Q1-1
median2
Q37
95-th percentile13
Maximum19
Range39
Interquartile range (IQR)8

Descriptive statistics

Standard deviation6.1267925
Coefficient of variation (CV)2.1107219
Kurtosis0.063585432
Mean2.9027
Median Absolute Deviation (MAD)4
Skewness-0.080096435
Sum29027
Variance37.537586
MonotonicityNot monotonic
2023-12-11T06:03:01.573476image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=40)
ValueCountFrequency (%)
1 1253
 
12.5%
0 837
 
8.4%
-1 743
 
7.4%
2 624
 
6.2%
5 506
 
5.1%
3 497
 
5.0%
4 490
 
4.9%
6 382
 
3.8%
8 368
 
3.7%
7 365
 
3.6%
Other values (30) 3935
39.4%
ValueCountFrequency (%)
-20 1
 
< 0.1%
-19 7
 
0.1%
-18 9
 
0.1%
-17 19
 
0.2%
-16 8
 
0.1%
-15 6
 
0.1%
-14 25
0.2%
-13 16
 
0.2%
-12 40
0.4%
-11 60
0.6%
ValueCountFrequency (%)
19 1
 
< 0.1%
18 14
 
0.1%
17 23
 
0.2%
16 72
 
0.7%
15 148
1.5%
14 178
1.8%
13 236
2.4%
12 358
3.6%
11 319
3.2%
10 360
3.6%

45시간이후
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct40
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.8244
Minimum-23
Maximum16
Zeros1093
Zeros (%)10.9%
Negative3977
Negative (%)39.8%
Memory size166.0 KiB
2023-12-11T06:03:01.681026image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum-23
5-th percentile-9
Q1-2
median0
Q35
95-th percentile10
Maximum16
Range39
Interquartile range (IQR)7

Descriptive statistics

Standard deviation5.7373214
Coefficient of variation (CV)6.9593903
Kurtosis0.54358089
Mean0.8244
Median Absolute Deviation (MAD)3
Skewness-0.31798611
Sum8244
Variance32.916856
MonotonicityNot monotonic
2023-12-11T06:03:01.794958image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=40)
ValueCountFrequency (%)
0 1093
 
10.9%
-1 1092
 
10.9%
1 797
 
8.0%
-2 678
 
6.8%
2 563
 
5.6%
3 542
 
5.4%
4 465
 
4.7%
7 450
 
4.5%
5 429
 
4.3%
-3 408
 
4.1%
Other values (30) 3483
34.8%
ValueCountFrequency (%)
-23 1
 
< 0.1%
-22 4
 
< 0.1%
-21 6
 
0.1%
-20 8
 
0.1%
-19 15
 
0.1%
-18 8
 
0.1%
-17 6
 
0.1%
-16 8
 
0.1%
-15 35
0.4%
-14 55
0.5%
ValueCountFrequency (%)
16 15
 
0.1%
15 31
 
0.3%
14 24
 
0.2%
13 50
 
0.5%
12 107
 
1.1%
11 175
 
1.8%
10 252
2.5%
9 307
3.1%
8 363
3.6%
7 450
4.5%

48시간이후
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct42
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean-0.5221
Minimum-25
Maximum16
Zeros955
Zeros (%)9.6%
Negative4881
Negative (%)48.8%
Memory size166.0 KiB
2023-12-11T06:03:01.899534image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum-25
5-th percentile-11
Q1-3
median0
Q33
95-th percentile8
Maximum16
Range41
Interquartile range (IQR)6

Descriptive statistics

Standard deviation5.7055733
Coefficient of variation (CV)-10.928124
Kurtosis0.8206934
Mean-0.5221
Median Absolute Deviation (MAD)3
Skewness-0.49489827
Sum-5221
Variance32.553567
MonotonicityNot monotonic
2023-12-11T06:03:01.999632image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=42)
ValueCountFrequency (%)
-1 1127
 
11.3%
0 955
 
9.6%
-2 867
 
8.7%
1 782
 
7.8%
2 608
 
6.1%
-3 575
 
5.8%
4 507
 
5.1%
3 468
 
4.7%
5 433
 
4.3%
-4 377
 
3.8%
Other values (32) 3301
33.0%
ValueCountFrequency (%)
-25 1
 
< 0.1%
-24 1
 
< 0.1%
-23 4
 
< 0.1%
-22 10
 
0.1%
-21 16
 
0.2%
-20 8
 
0.1%
-19 6
 
0.1%
-18 10
 
0.1%
-17 13
 
0.1%
-16 58
0.6%
ValueCountFrequency (%)
16 2
 
< 0.1%
15 30
 
0.3%
14 29
 
0.3%
13 15
 
0.1%
12 20
 
0.2%
11 53
 
0.5%
10 97
 
1.0%
9 199
2.0%
8 275
2.8%
7 288
2.9%

Interactions

2023-12-11T06:02:53.901169image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:02:22.023845image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:02:24.517527image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:02:26.344134image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:02:28.703934image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:02:30.741807image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:02:32.555243image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:02:34.728261image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:02:36.487938image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:02:38.653079image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:02:41.147796image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:02:43.242000image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:02:45.269036image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:02:47.488363image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:02:49.438655image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:02:51.591299image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:02:54.033719image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:02:22.192062image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:02:24.647928image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:02:26.455678image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:02:28.815223image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:02:30.849971image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:02:32.657072image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:02:34.844980image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:02:36.593389image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:02:38.804047image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:02:41.265724image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:02:43.397332image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:02:45.392900image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:02:47.606379image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:02:49.587607image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
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2023-12-11T06:02:34.498187image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:02:36.278267image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:02:38.394038image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:02:40.883229image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:02:43.044292image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:02:45.059839image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:02:47.249910image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:02:49.224580image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:02:51.358651image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:02:53.670404image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:02:55.684309image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:02:24.382363image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:02:26.265305image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:02:28.593500image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:02:30.650367image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:02:32.459653image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:02:34.635127image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:02:36.393529image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:02:38.538716image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:02:41.023493image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:02:43.150104image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:02:45.173860image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:02:47.381616image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:02:49.345418image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:02:51.477304image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:02:53.804324image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-11T06:03:02.086825image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
지점명3시간이후6시간이후9시간이후12시간이후15시간이후18시간이후21시간이후24시간이후27시간이후30시간이후33시간이후36시간이후39시간이후42시간이후45시간이후48시간이후
지점명1.0000.3880.3410.4100.3490.3600.3170.3480.3220.3020.2700.2730.2010.1190.2160.2420.279
3시간이후0.3881.0000.9580.9270.8740.8500.8400.8160.7880.7450.7230.7390.7310.7180.6600.6320.635
6시간이후0.3410.9581.0000.9330.8750.8580.8470.8070.7890.7630.7340.7530.7300.7180.6380.6400.623
9시간이후0.4100.9270.9331.0000.9410.9090.8840.8600.8360.8180.7980.8280.8130.7810.7200.7140.675
12시간이후0.3490.8740.8750.9411.0000.9730.9240.8910.8560.8270.8010.8320.8460.8180.7470.7420.707
15시간이후0.3600.8500.8580.9090.9731.0000.9480.9070.8760.8450.8220.8390.8530.8270.7640.7490.719
18시간이후0.3170.8400.8470.8840.9240.9481.0000.9550.9110.8790.8570.8670.8600.8340.7890.7640.736
21시간이후0.3480.8160.8070.8600.8910.9070.9551.0000.9520.9210.9010.8910.8650.8270.7960.7810.760
24시간이후0.3220.7880.7890.8360.8560.8760.9110.9521.0000.9640.9210.8910.8530.8160.7810.7810.770
27시간이후0.3020.7450.7630.8180.8270.8450.8790.9210.9641.0000.9530.9220.8610.8370.8020.8030.791
30시간이후0.2700.7230.7340.7980.8010.8220.8570.9010.9210.9531.0000.9530.8800.8480.8270.8210.823
33시간이후0.2730.7390.7530.8280.8320.8390.8670.8910.8910.9220.9531.0000.9480.9110.8870.8890.876
36시간이후0.2010.7310.7300.8130.8460.8530.8600.8650.8530.8610.8800.9481.0000.9670.9280.9090.887
39시간이후0.1190.7180.7180.7810.8180.8270.8340.8270.8160.8370.8480.9110.9671.0000.9560.9290.902
42시간이후0.2160.6600.6380.7200.7470.7640.7890.7960.7810.8020.8270.8870.9280.9561.0000.9620.938
45시간이후0.2420.6320.6400.7140.7420.7490.7640.7810.7810.8030.8210.8890.9090.9290.9621.0000.974
48시간이후0.2790.6350.6230.6750.7070.7190.7360.7600.7700.7910.8230.8760.8870.9020.9380.9741.000
2023-12-11T06:03:02.265462image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
3시간이후6시간이후9시간이후12시간이후15시간이후18시간이후21시간이후24시간이후27시간이후30시간이후33시간이후36시간이후39시간이후42시간이후45시간이후48시간이후지점명
3시간이후1.0000.9780.9500.8880.8540.8410.8050.7820.7180.6480.6590.6070.6020.5680.5020.4520.137
6시간이후0.9781.0000.9610.8970.8670.8580.8210.7950.7290.6580.6650.6150.6120.5780.5090.4570.124
9시간이후0.9500.9611.0000.9560.9250.9160.8820.8520.7890.7220.7360.6860.6790.6420.5750.5220.154
12시간이후0.8880.8970.9561.0000.9790.9570.9140.8790.8190.7570.7640.7300.7210.6750.6040.5490.128
15시간이후0.8540.8670.9250.9791.0000.9740.9310.8940.8380.7780.7840.7600.7510.7050.6350.5770.131
18시간이후0.8410.8580.9160.9570.9741.0000.9630.9270.8760.8180.8190.7800.7710.7400.6700.6150.114
21시간이후0.8050.8210.8820.9140.9310.9631.0000.9710.9290.8730.8590.7950.7770.7560.7000.6510.127
24시간이후0.7820.7950.8520.8790.8940.9270.9711.0000.9650.9110.8810.7940.7670.7460.7010.6570.116
27시간이후0.7180.7290.7890.8190.8380.8760.9290.9651.0000.9610.9220.8240.7850.7720.7410.7040.091
30시간이후0.6480.6580.7220.7570.7780.8180.8730.9110.9611.0000.9500.8470.8010.7950.7810.7500.096
33시간이후0.6590.6650.7360.7640.7840.8190.8590.8810.9220.9501.0000.9250.8820.8750.8540.8170.097
36시간이후0.6070.6150.6860.7300.7600.7800.7950.7940.8240.8470.9251.0000.9670.9360.8910.8430.070
39시간이후0.6020.6120.6790.7210.7510.7710.7770.7670.7850.8010.8820.9671.0000.9550.9000.8490.032
42시간이후0.5680.5780.6420.6750.7050.7400.7560.7460.7720.7950.8750.9360.9551.0000.9520.9040.076
45시간이후0.5020.5090.5750.6040.6350.6700.7000.7010.7410.7810.8540.8910.9000.9521.0000.9620.086
48시간이후0.4520.4570.5220.5490.5770.6150.6510.6570.7040.7500.8170.8430.8490.9040.9621.0000.099
지점명0.1370.1240.1540.1280.1310.1140.1270.1160.0910.0960.0970.0700.0320.0760.0860.0991.000

Missing values

2023-12-11T06:02:55.853221image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-11T06:02:56.116851image/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

발표시각지점명3시간이후6시간이후9시간이후12시간이후15시간이후18시간이후21시간이후24시간이후27시간이후30시간이후33시간이후36시간이후39시간이후42시간이후45시간이후48시간이후
31102019-12-31 00시경기도 안양시 만안구-17-18-18-12-9-8-6-7-5-4-312211
42232019-12-23 00시경기도 군포시44423421-1-1058532
7122020-03-14 00시경기도 안성시-6-714750-1-2-30440-4-6
6562020-03-15 00시경기도 남양주시-1-22452-2-3-2-4046420
71502019-03-16 00시경기도 동두천시-1-31665320-127101042
71082019-03-17 00시경기도 부천시332687653141010977
37702019-12-31 00시경기도 포천시-20-19-23-14-10-10-9-12-10-8-7-30-1-2-3
34642019-12-31 00시경기도 용인시 수지구-15-19-18-12-9-8-6-7-6-5-31110-1
36292019-12-31 00시경기도 이천시-15-16-18-12-8-8-7-8-7-7-6-101-1-1
11302020-03-04 00시경기도 동두천시0-3-3-2-2-5-4-6-7-8-52630-2
발표시각지점명3시간이후6시간이후9시간이후12시간이후15시간이후18시간이후21시간이후24시간이후27시간이후30시간이후33시간이후36시간이후39시간이후42시간이후45시간이후48시간이후
54642019-11-24 00시경기도 고양시 일산동구869131393-3-6-7-11-23311
67302019-03-26 00시경기도 안산시 단원구128141511310281412852
56452019-11-20 00시경기도 동두천시-6-7-5052-2-3-4-5079632
72452019-03-14 00시경기도 시흥시-4-2367630-1-1199612
23382019-12-31 00시경기도 김포시-19-21-20-15-12-10-8-8-6-6-5010-1-1
39502019-12-30 00시경기도 이천시333630-9-12-16-16-18-12-8-8-7-8
89792019-02-02 00시경기도 의왕시-3-4-22430223464330
54602019-11-25 00시경기도 화성시-7-9-7-511322251012754
92732019-01-26 00시경기도 양평군-11-12-8-20-3-4-8-10-12-9020-4-6
91142019-01-30 00시경기도 하남시-5-6-35632-2-3-7-5-3-3-4-8-11

Duplicate rows

Most frequently occurring

발표시각지점명3시간이후6시간이후9시간이후12시간이후15시간이후18시간이후21시간이후24시간이후27시간이후30시간이후33시간이후36시간이후39시간이후42시간이후45시간이후48시간이후# duplicates
92019-12-31 00시경기도 군포시-17-19-18-14-9-8-6-7-5-4-31211148
132019-12-31 00시경기도 부천시-15-18-18-14-10-5-6-6-4-4-21321146
332019-12-31 00시경기도 용인시 수지구-15-19-18-12-9-8-6-7-6-5-31110-146
142019-12-31 00시경기도 성남시 분당구-15-17-18-13-9-8-6-7-6-5-31210045
322019-12-31 00시경기도 용인시 기흥구-15-18-18-12-9-9-6-7-6-5-41110-145
412019-12-31 00시경기도 하남시-16-12-18-13-9-5-7-8-7-6-51210-145
62019-12-31 00시경기도 광명시-17-18-18-13-9-9-8-6-4-3-21102244
152019-12-31 00시경기도 성남시 수정구-17-16-18-13-9-7-6-8-7-5-41210-144
192019-12-31 00시경기도 수원시 장안구-17-19-18-12-9-9-6-7-5-5-31210044
202019-12-31 00시경기도 수원시 팔달구-17-19-19-13-11-9-7-7-6-5-4021-1-144