Overview

Dataset statistics

Number of variables26
Number of observations10000
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory2.2 MiB
Average record size in memory235.0 B

Variable types

Categorical6
Text4
Numeric16

Alerts

년도 has constant value ""Constant
2종 has 1671 (16.7%) zerosZeros
3종 has 297 (3.0%) zerosZeros
4종 has 1118 (11.2%) zerosZeros
5종 has 1361 (13.6%) zerosZeros
6종 has 1864 (18.6%) zerosZeros
7종 has 4191 (41.9%) zerosZeros
8종 has 8224 (82.2%) zerosZeros
9종 has 9741 (97.4%) zerosZeros
10종 has 5013 (50.1%) zerosZeros
11종 has 9226 (92.3%) zerosZeros
12종 has 8082 (80.8%) zerosZeros

Reproduction

Analysis started2023-12-10 21:40:13.994827
Analysis finished2023-12-10 21:40:15.097015
Duration1.1 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

년도
Categorical

CONSTANT 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2022
10000 

Length

Max length4
Median length4
Mean length4
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2022
2nd row2022
3rd row2022
4th row2022
5th row2022

Common Values

ValueCountFrequency (%)
2022 10000
100.0%

Length

2023-12-11T06:40:15.191495image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T06:40:15.319428image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2022 10000
100.0%

도로종류
Categorical

Distinct4
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
지방도
3498 
일반국도
2675 
국가지원지방도
1952 
고속국도
1875 

Length

Max length7
Median length4
Mean length4.2358
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row일반국도
2nd row국가지원지방도
3rd row국가지원지방도
4th row국가지원지방도
5th row지방도

Common Values

ValueCountFrequency (%)
지방도 3498
35.0%
일반국도 2675
26.8%
국가지원지방도 1952
19.5%
고속국도 1875
18.8%

Length

2023-12-11T06:40:15.441086image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T06:40:15.614551image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
지방도 3498
35.0%
일반국도 2675
26.8%
국가지원지방도 1952
19.5%
고속국도 1875
18.8%

도로종류코드
Categorical

Distinct4
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
4
3498 
2
2675 
3
1952 
1
1875 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2
2nd row3
3rd row3
4th row3
5th row4

Common Values

ValueCountFrequency (%)
4 3498
35.0%
2 2675
26.8%
3 1952
19.5%
1 1875
18.8%

Length

2023-12-11T06:40:15.766037image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T06:40:15.898858image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
4 3498
35.0%
2 2675
26.8%
3 1952
19.5%
1 1875
18.8%

지점번호
Text

Distinct498
Distinct (%)5.0%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2023-12-11T06:40:16.301661image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length7
Median length7
Mean length6.3222
Min length5

Characters and Unicode

Total characters63222
Distinct characters11
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
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 row4802-05
2nd row70-08
3rd row57-11
4th row57-08
5th row0357-03
ValueCountFrequency (%)
10005 31
 
0.3%
0391-06 30
 
0.3%
0359-04 30
 
0.3%
56-15 29
 
0.3%
0329-02 28
 
0.3%
4306-03 28
 
0.3%
0306-07 28
 
0.3%
0306-04 27
 
0.3%
17114 27
 
0.3%
78-05 27
 
0.3%
Other values (488) 9715
97.2%
2023-12-11T06:40:16.953371image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 18193
28.8%
- 8563
13.5%
3 7677
12.1%
1 7588
12.0%
2 3995
 
6.3%
7 3560
 
5.6%
4 3254
 
5.1%
5 2968
 
4.7%
8 2921
 
4.6%
6 2616
 
4.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 54659
86.5%
Dash Punctuation 8563
 
13.5%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 18193
33.3%
3 7677
14.0%
1 7588
13.9%
2 3995
 
7.3%
7 3560
 
6.5%
4 3254
 
6.0%
5 2968
 
5.4%
8 2921
 
5.3%
6 2616
 
4.8%
9 1887
 
3.5%
Dash Punctuation
ValueCountFrequency (%)
- 8563
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 63222
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 18193
28.8%
- 8563
13.5%
3 7677
12.1%
1 7588
12.0%
2 3995
 
6.3%
7 3560
 
5.6%
4 3254
 
5.1%
5 2968
 
4.7%
8 2921
 
4.6%
6 2616
 
4.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 63222
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 18193
28.8%
- 8563
13.5%
3 7677
12.1%
1 7588
12.0%
2 3995
 
6.3%
7 3560
 
5.6%
4 3254
 
5.1%
5 2968
 
4.7%
8 2921
 
4.6%
6 2616
 
4.1%

호선명
Text

Distinct87
Distinct (%)0.9%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2023-12-11T06:40:17.266708image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length15
Median length9
Mean length9.5412
Min length1

Characters and Unicode

Total characters95412
Distinct characters64
Distinct categories6 ?
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 row일반국도 48호선
2nd row국가지원지방도 70호선
3rd row국가지원지방도 57호선
4th row국가지원지방도 57호선
5th row지방도 357호선
ValueCountFrequency (%)
지방도 3498
19.3%
일반국도 2675
 
14.8%
국가지원지방도 1952
 
10.8%
수도권제1순환고속도로 545
 
3.0%
39호선 396
 
2.2%
98호선 320
 
1.8%
56호선 288
 
1.6%
37호선 274
 
1.5%
45호선 249
 
1.4%
78호선 245
 
1.4%
Other values (78) 7683
42.4%
2023-12-11T06:40:17.694031image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
도 10615
 
11.1%
선 8125
 
8.5%
호 8125
 
8.5%
8125
 
8.5%
지 7402
 
7.8%
3 5725
 
6.0%
방 5450
 
5.7%
국 4798
 
5.0%
반 2675
 
2.8%
일 2675
 
2.8%
Other values (54) 31697
33.2%

Most occurring categories

ValueCountFrequency (%)
Other Letter 66650
69.9%
Decimal Number 20244
 
21.2%
Space Separator 8125
 
8.5%
Open Punctuation 150
 
0.2%
Close Punctuation 150
 
0.2%
Dash Punctuation 93
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
도 10615
15.9%
선 8125
12.2%
호 8125
12.2%
지 7402
11.1%
방 5450
8.2%
국 4798
 
7.2%
반 2675
 
4.0%
일 2675
 
4.0%
원 1973
 
3.0%
가 1952
 
2.9%
Other values (40) 12860
19.3%
Decimal Number
ValueCountFrequency (%)
3 5725
28.3%
7 2354
11.6%
8 2101
 
10.4%
1 2004
 
9.9%
4 1676
 
8.3%
5 1509
 
7.5%
2 1500
 
7.4%
6 1377
 
6.8%
9 1107
 
5.5%
0 891
 
4.4%
Space Separator
ValueCountFrequency (%)
8125
100.0%
Open Punctuation
ValueCountFrequency (%)
( 150
100.0%
Close Punctuation
ValueCountFrequency (%)
) 150
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 93
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 66650
69.9%
Common 28762
30.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
도 10615
15.9%
선 8125
12.2%
호 8125
12.2%
지 7402
11.1%
방 5450
8.2%
국 4798
 
7.2%
반 2675
 
4.0%
일 2675
 
4.0%
원 1973
 
3.0%
가 1952
 
2.9%
Other values (40) 12860
19.3%
Common
ValueCountFrequency (%)
8125
28.2%
3 5725
19.9%
7 2354
 
8.2%
8 2101
 
7.3%
1 2004
 
7.0%
4 1676
 
5.8%
5 1509
 
5.2%
2 1500
 
5.2%
6 1377
 
4.8%
9 1107
 
3.8%
Other values (4) 1284
 
4.5%

Most occurring blocks

ValueCountFrequency (%)
Hangul 66650
69.9%
ASCII 28762
30.1%

Most frequent character per block

Hangul
ValueCountFrequency (%)
도 10615
15.9%
선 8125
12.2%
호 8125
12.2%
지 7402
11.1%
방 5450
8.2%
국 4798
 
7.2%
반 2675
 
4.0%
일 2675
 
4.0%
원 1973
 
3.0%
가 1952
 
2.9%
Other values (40) 12860
19.3%
ASCII
ValueCountFrequency (%)
8125
28.2%
3 5725
19.9%
7 2354
 
8.2%
8 2101
 
7.3%
1 2004
 
7.0%
4 1676
 
5.8%
5 1509
 
5.2%
2 1500
 
5.2%
6 1377
 
4.8%
9 1107
 
3.8%
Other values (4) 1284
 
4.5%

호선코드
Real number (ℝ)

Distinct83
Distinct (%)0.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean167.14906
Minimum1
Maximum400
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2023-12-11T06:40:17.860603image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile6
Q146
median100
Q3325
95-th percentile372
Maximum400
Range399
Interquartile range (IQR)279

Descriptive statistics

Standard deviation138.14833
Coefficient of variation (CV)0.82649781
Kurtosis-1.5470077
Mean167.14906
Median Absolute Deviation (MAD)62
Skewness0.46932277
Sum1671490.6
Variance19084.961
MonotonicityNot monotonic
2023-12-11T06:40:18.038753image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
100.0 545
 
5.5%
39.0 396
 
4.0%
98.0 320
 
3.2%
56.0 288
 
2.9%
45.0 287
 
2.9%
37.0 274
 
2.7%
78.0 245
 
2.5%
1.0 237
 
2.4%
43.0 235
 
2.4%
38.0 224
 
2.2%
Other values (73) 6949
69.5%
ValueCountFrequency (%)
1.0 237
2.4%
3.0 157
1.6%
6.0 143
1.4%
15.0 35
 
0.4%
17.0 100
 
1.0%
17.2 23
 
0.2%
23.0 141
1.4%
29.0 44
 
0.4%
35.0 22
 
0.2%
37.0 274
2.7%
ValueCountFrequency (%)
400.0 143
1.4%
391.0 70
0.7%
387.0 144
1.4%
383.0 36
 
0.4%
379.0 17
 
0.2%
375.0 39
 
0.4%
372.0 94
0.9%
371.0 140
1.4%
368.0 53
 
0.5%
367.0 79
0.8%

상/하행
Categorical

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
하행
5002 
상행
4998 

Length

Max length2
Median length2
Mean length2
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row하행
2nd row하행
3rd row하행
4th row하행
5th row상행

Common Values

ValueCountFrequency (%)
하행 5002
50.0%
상행 4998
50.0%

Length

2023-12-11T06:40:18.194807image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T06:40:18.302543image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
하행 5002
50.0%
상행 4998
50.0%

상/하행코드
Categorical

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2
5002 
1
4998 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2
2nd row2
3rd row2
4th row2
5th row1

Common Values

ValueCountFrequency (%)
2 5002
50.0%
1 4998
50.0%

Length

2023-12-11T06:40:18.399183image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T06:40:18.481717image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2 5002
50.0%
1 4998
50.0%

시간대
Categorical

Distinct24
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
16시~17시
 
442
05시~06시
 
440
04시~05시
 
434
02시~03시
 
427
03시~04시
 
427
Other values (19)
7830 

Length

Max length7
Median length7
Mean length7
Min length7

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row17시~18시
2nd row12시~13시
3rd row22시~23시
4th row17시~18시
5th row06시~07시

Common Values

ValueCountFrequency (%)
16시~17시 442
 
4.4%
05시~06시 440
 
4.4%
04시~05시 434
 
4.3%
02시~03시 427
 
4.3%
03시~04시 427
 
4.3%
01시~02시 425
 
4.2%
15시~16시 425
 
4.2%
23시~24시 424
 
4.2%
08시~09시 423
 
4.2%
17시~18시 422
 
4.2%
Other values (14) 5711
57.1%

Length

2023-12-11T06:40:18.574122image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
16시~17시 442
 
4.4%
05시~06시 440
 
4.4%
04시~05시 434
 
4.3%
02시~03시 427
 
4.3%
03시~04시 427
 
4.3%
01시~02시 425
 
4.2%
15시~16시 425
 
4.2%
23시~24시 424
 
4.2%
08시~09시 423
 
4.2%
17시~18시 422
 
4.2%
Other values (14) 5711
57.1%

시간대코드
Real number (ℝ)

Distinct24
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean12.4431
Minimum1
Maximum24
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2023-12-11T06:40:18.691279image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile2
Q16
median12
Q318
95-th percentile23
Maximum24
Range23
Interquartile range (IQR)12

Descriptive statistics

Standard deviation6.939105
Coefficient of variation (CV)0.5576669
Kurtosis-1.2058644
Mean12.4431
Median Absolute Deviation (MAD)6
Skewness0.0059981685
Sum124431
Variance48.151178
MonotonicityNot monotonic
2023-12-11T06:40:18.826413image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=24)
ValueCountFrequency (%)
16 442
 
4.4%
5 440
 
4.4%
4 434
 
4.3%
2 427
 
4.3%
3 427
 
4.3%
1 425
 
4.2%
15 425
 
4.2%
23 424
 
4.2%
8 423
 
4.2%
17 422
 
4.2%
Other values (14) 5711
57.1%
ValueCountFrequency (%)
1 425
4.2%
2 427
4.3%
3 427
4.3%
4 434
4.3%
5 440
4.4%
6 410
4.1%
7 386
3.9%
8 423
4.2%
9 386
3.9%
10 422
4.2%
ValueCountFrequency (%)
24 416
4.2%
23 424
4.2%
22 412
4.1%
21 398
4.0%
20 404
4.0%
19 410
4.1%
18 403
4.0%
17 422
4.2%
16 442
4.4%
15 425
4.2%

지역
Text

Distinct239
Distinct (%)2.4%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2023-12-11T06:40:19.158641image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length14
Median length9
Mean length9.6649
Min length8

Characters and Unicode

Total characters96649
Distinct characters167
Distinct categories3 ?
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 row경기 김포 양촌면
2nd row경기 양평 지평면
3rd row경기 의왕 청계동
4th row경기 광주 오포읍
5th row경기 고양 일산서 송산동
ValueCountFrequency (%)
경기 9463
29.9%
화성 913
 
2.9%
파주 886
 
2.8%
안성 658
 
2.1%
여주 616
 
1.9%
양평 604
 
1.9%
용인 600
 
1.9%
포천 595
 
1.9%
양주 565
 
1.8%
고양 526
 
1.7%
Other values (289) 16238
51.3%
2023-12-11T06:40:19.613005image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
21664
22.4%
기 9665
 
10.0%
경 9507
 
9.8%
면 5308
 
5.5%
동 3896
 
4.0%
양 3275
 
3.4%
주 2896
 
3.0%
성 2183
 
2.3%
천 2071
 
2.1%
평 1705
 
1.8%
Other values (157) 34479
35.7%

Most occurring categories

ValueCountFrequency (%)
Other Letter 74054
76.6%
Space Separator 21664
 
22.4%
Decimal Number 931
 
1.0%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
기 9665
 
13.1%
경 9507
 
12.8%
면 5308
 
7.2%
동 3896
 
5.3%
양 3275
 
4.4%
주 2896
 
3.9%
성 2183
 
2.9%
천 2071
 
2.8%
평 1705
 
2.3%
읍 1545
 
2.1%
Other values (151) 32003
43.2%
Decimal Number
ValueCountFrequency (%)
1 723
77.7%
2 101
 
10.8%
4 62
 
6.7%
3 24
 
2.6%
5 21
 
2.3%
Space Separator
ValueCountFrequency (%)
21664
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 74054
76.6%
Common 22595
 
23.4%

Most frequent character per script

Hangul
ValueCountFrequency (%)
기 9665
 
13.1%
경 9507
 
12.8%
면 5308
 
7.2%
동 3896
 
5.3%
양 3275
 
4.4%
주 2896
 
3.9%
성 2183
 
2.9%
천 2071
 
2.8%
평 1705
 
2.3%
읍 1545
 
2.1%
Other values (151) 32003
43.2%
Common
ValueCountFrequency (%)
21664
95.9%
1 723
 
3.2%
2 101
 
0.4%
4 62
 
0.3%
3 24
 
0.1%
5 21
 
0.1%

Most occurring blocks

ValueCountFrequency (%)
Hangul 74054
76.6%
ASCII 22595
 
23.4%

Most frequent character per block

ASCII
ValueCountFrequency (%)
21664
95.9%
1 723
 
3.2%
2 101
 
0.4%
4 62
 
0.3%
3 24
 
0.1%
5 21
 
0.1%
Hangul
ValueCountFrequency (%)
기 9665
 
13.1%
경 9507
 
12.8%
면 5308
 
7.2%
동 3896
 
5.3%
양 3275
 
4.4%
주 2896
 
3.9%
성 2183
 
2.9%
천 2071
 
2.8%
평 1705
 
2.3%
읍 1545
 
2.1%
Other values (151) 32003
43.2%

지역코드
Real number (ℝ)

Distinct241
Distinct (%)2.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean3068112.3
Minimum1116070
Maximum3138041
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2023-12-11T06:40:19.783334image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1116070
5-th percentile2331037
Q13113031
median3121038
Q33126033
95-th percentile3138031
Maximum3138041
Range2021971
Interquartile range (IQR)13002

Descriptive statistics

Standard deviation243171.76
Coefficient of variation (CV)0.079257778
Kurtosis33.79521
Mean3068112.3
Median Absolute Deviation (MAD)5987
Skewness-5.4389152
Sum3.0681123 × 1010
Variance5.9132505 × 1010
MonotonicityNot monotonic
2023-12-11T06:40:19.976382image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
3126034 154
 
1.5%
3126033 133
 
1.3%
3128033 128
 
1.3%
3122040 127
 
1.3%
3119133 123
 
1.2%
3120035 122
 
1.2%
3124041 111
 
1.1%
3122039 111
 
1.1%
3128038 107
 
1.1%
3120012 107
 
1.1%
Other values (231) 8777
87.8%
ValueCountFrequency (%)
1116070 22
 
0.2%
1124070 20
 
0.2%
1125052 37
0.4%
2301062 44
0.4%
2303055 17
 
0.2%
2303060 59
0.6%
2305065 21
 
0.2%
2305067 15
 
0.1%
2306051 22
 
0.2%
2307056 23
 
0.2%
ValueCountFrequency (%)
3138041 41
 
0.4%
3138040 21
 
0.2%
3138039 88
0.9%
3138038 38
 
0.4%
3138037 72
0.7%
3138036 106
1.1%
3138035 43
0.4%
3138034 40
 
0.4%
3138033 21
 
0.2%
3138032 19
 
0.2%

구간명
Text

Distinct850
Distinct (%)8.5%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2023-12-11T06:40:20.374307image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length17
Median length7
Mean length8.5136
Min length6

Characters and Unicode

Total characters85136
Distinct characters202
Distinct categories5 ?
Distinct scripts3 ?
Distinct blocks3 ?
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 row김포 → 강화
2nd row지평 → 이포대교
3rd row의왕 → 과천
4th row광주 → 수지
5th row법곳IC → 송산IC
ValueCountFrequency (%)
→ 10000
33.3%
장호원 378
 
1.3%
이천 357
 
1.2%
안성 344
 
1.1%
평택 334
 
1.1%
오산 278
 
0.9%
용인 217
 
0.7%
수원 216
 
0.7%
문산 216
 
0.7%
포천 215
 
0.7%
Other values (409) 17445
58.1%
2023-12-11T06:40:20.935459image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
20000
23.5%
→ 10000
 
11.7%
C 4602
 
5.4%
I 3529
 
4.1%
천 1651
 
1.9%
산 1536
 
1.8%
평 1379
 
1.6%
양 1235
 
1.5%
일 1182
 
1.4%
원 1131
 
1.3%
Other values (192) 38891
45.7%

Most occurring categories

ValueCountFrequency (%)
Other Letter 43859
51.5%
Space Separator 20000
23.5%
Uppercase Letter 10277
 
12.1%
Math Symbol 10000
 
11.7%
Decimal Number 1000
 
1.2%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
천 1651
 
3.8%
산 1536
 
3.5%
평 1379
 
3.1%
양 1235
 
2.8%
일 1182
 
2.7%
원 1131
 
2.6%
남 1112
 
2.5%
안 950
 
2.2%
동 902
 
2.1%
성 884
 
2.0%
Other values (177) 31897
72.7%
Decimal Number
ValueCountFrequency (%)
3 218
21.8%
4 187
18.7%
7 169
16.9%
8 134
13.4%
5 94
9.4%
1 66
 
6.6%
9 46
 
4.6%
2 44
 
4.4%
6 42
 
4.2%
Uppercase Letter
ValueCountFrequency (%)
C 4602
44.8%
I 3529
34.3%
J 1073
 
10.4%
T 1073
 
10.4%
Space Separator
ValueCountFrequency (%)
20000
100.0%
Math Symbol
ValueCountFrequency (%)
→ 10000
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 43859
51.5%
Common 31000
36.4%
Latin 10277
 
12.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
천 1651
 
3.8%
산 1536
 
3.5%
평 1379
 
3.1%
양 1235
 
2.8%
일 1182
 
2.7%
원 1131
 
2.6%
남 1112
 
2.5%
안 950
 
2.2%
동 902
 
2.1%
성 884
 
2.0%
Other values (177) 31897
72.7%
Common
ValueCountFrequency (%)
20000
64.5%
→ 10000
32.3%
3 218
 
0.7%
4 187
 
0.6%
7 169
 
0.5%
8 134
 
0.4%
5 94
 
0.3%
1 66
 
0.2%
9 46
 
0.1%
2 44
 
0.1%
Latin
ValueCountFrequency (%)
C 4602
44.8%
I 3529
34.3%
J 1073
 
10.4%
T 1073
 
10.4%

Most occurring blocks

ValueCountFrequency (%)
Hangul 43859
51.5%
ASCII 31277
36.7%
Arrows 10000
 
11.7%

Most frequent character per block

ASCII
ValueCountFrequency (%)
20000
63.9%
C 4602
 
14.7%
I 3529
 
11.3%
J 1073
 
3.4%
T 1073
 
3.4%
3 218
 
0.7%
4 187
 
0.6%
7 169
 
0.5%
8 134
 
0.4%
5 94
 
0.3%
Other values (4) 198
 
0.6%
Arrows
ValueCountFrequency (%)
→ 10000
100.0%
Hangul
ValueCountFrequency (%)
천 1651
 
3.8%
산 1536
 
3.5%
평 1379
 
3.1%
양 1235
 
2.8%
일 1182
 
2.7%
원 1131
 
2.6%
남 1112
 
2.5%
안 950
 
2.2%
동 902
 
2.1%
성 884
 
2.0%
Other values (177) 31897
72.7%

1종
Real number (ℝ)

Distinct2380
Distinct (%)23.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean655.4285
Minimum0
Maximum6559
Zeros66
Zeros (%)0.7%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2023-12-11T06:40:21.134350image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile6
Q164
median222
Q3723
95-th percentile3285.4
Maximum6559
Range6559
Interquartile range (IQR)659

Descriptive statistics

Standard deviation1052.9831
Coefficient of variation (CV)1.6065567
Kurtosis6.717524
Mean655.4285
Median Absolute Deviation (MAD)201
Skewness2.5802264
Sum6554285
Variance1108773.3
MonotonicityNot monotonic
2023-12-11T06:40:21.287036image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
2 107
 
1.1%
6 90
 
0.9%
1 89
 
0.9%
4 78
 
0.8%
3 76
 
0.8%
5 73
 
0.7%
9 69
 
0.7%
10 69
 
0.7%
0 66
 
0.7%
12 64
 
0.6%
Other values (2370) 9219
92.2%
ValueCountFrequency (%)
0 66
0.7%
1 89
0.9%
2 107
1.1%
3 76
0.8%
4 78
0.8%
5 73
0.7%
6 90
0.9%
7 62
0.6%
8 63
0.6%
9 69
0.7%
ValueCountFrequency (%)
6559 1
< 0.1%
6360 1
< 0.1%
6341 1
< 0.1%
6299 1
< 0.1%
6244 1
< 0.1%
6230 1
< 0.1%
6203 1
< 0.1%
6143 2
< 0.1%
6130 1
< 0.1%
6103 1
< 0.1%

2종
Real number (ℝ)

ZEROS 

Distinct178
Distinct (%)1.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean13.0958
Minimum0
Maximum634
Zeros1671
Zeros (%)16.7%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2023-12-11T06:40:21.436325image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q11
median4
Q313
95-th percentile56
Maximum634
Range634
Interquartile range (IQR)12

Descriptive statistics

Standard deviation29.29753
Coefficient of variation (CV)2.2371699
Kurtosis124.98527
Mean13.0958
Median Absolute Deviation (MAD)4
Skewness8.7726577
Sum130958
Variance858.34526
MonotonicityNot monotonic
2023-12-11T06:40:21.601543image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 1671
16.7%
1 1303
13.0%
2 916
 
9.2%
3 793
 
7.9%
4 526
 
5.3%
5 481
 
4.8%
6 380
 
3.8%
7 337
 
3.4%
8 278
 
2.8%
9 214
 
2.1%
Other values (168) 3101
31.0%
ValueCountFrequency (%)
0 1671
16.7%
1 1303
13.0%
2 916
9.2%
3 793
7.9%
4 526
 
5.3%
5 481
 
4.8%
6 380
 
3.8%
7 337
 
3.4%
8 278
 
2.8%
9 214
 
2.1%
ValueCountFrequency (%)
634 1
< 0.1%
594 1
< 0.1%
552 1
< 0.1%
539 1
< 0.1%
535 1
< 0.1%
507 1
< 0.1%
490 1
< 0.1%
486 1
< 0.1%
432 1
< 0.1%
413 1
< 0.1%

3종
Real number (ℝ)

ZEROS 

Distinct805
Distinct (%)8.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean108.9111
Minimum0
Maximum2032
Zeros297
Zeros (%)3.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2023-12-11T06:40:21.782711image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile1
Q112
median43
Q3120
95-th percentile475
Maximum2032
Range2032
Interquartile range (IQR)108

Descriptive statistics

Standard deviation183.91966
Coefficient of variation (CV)1.6887137
Kurtosis16.733468
Mean108.9111
Median Absolute Deviation (MAD)38
Skewness3.5755625
Sum1089111
Variance33826.442
MonotonicityNot monotonic
2023-12-11T06:40:21.928216image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 369
 
3.7%
0 297
 
3.0%
2 270
 
2.7%
3 231
 
2.3%
4 225
 
2.2%
5 208
 
2.1%
6 170
 
1.7%
10 149
 
1.5%
9 143
 
1.4%
7 135
 
1.4%
Other values (795) 7803
78.0%
ValueCountFrequency (%)
0 297
3.0%
1 369
3.7%
2 270
2.7%
3 231
2.3%
4 225
2.2%
5 208
2.1%
6 170
1.7%
7 135
 
1.4%
8 128
 
1.3%
9 143
 
1.4%
ValueCountFrequency (%)
2032 1
< 0.1%
1976 1
< 0.1%
1755 1
< 0.1%
1707 1
< 0.1%
1692 1
< 0.1%
1690 1
< 0.1%
1612 1
< 0.1%
1588 1
< 0.1%
1550 1
< 0.1%
1507 1
< 0.1%

4종
Real number (ℝ)

ZEROS 

Distinct325
Distinct (%)3.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean29.4249
Minimum0
Maximum708
Zeros1118
Zeros (%)11.2%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2023-12-11T06:40:22.064854image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q12
median10
Q333
95-th percentile128
Maximum708
Range708
Interquartile range (IQR)31

Descriptive statistics

Standard deviation50.80638
Coefficient of variation (CV)1.7266458
Kurtosis18.646124
Mean29.4249
Median Absolute Deviation (MAD)9
Skewness3.6186045
Sum294249
Variance2581.2883
MonotonicityNot monotonic
2023-12-11T06:40:22.198730image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 1118
 
11.2%
1 883
 
8.8%
2 622
 
6.2%
3 477
 
4.8%
4 361
 
3.6%
5 339
 
3.4%
7 322
 
3.2%
6 300
 
3.0%
8 247
 
2.5%
9 225
 
2.2%
Other values (315) 5106
51.1%
ValueCountFrequency (%)
0 1118
11.2%
1 883
8.8%
2 622
6.2%
3 477
4.8%
4 361
 
3.6%
5 339
 
3.4%
6 300
 
3.0%
7 322
 
3.2%
8 247
 
2.5%
9 225
 
2.2%
ValueCountFrequency (%)
708 1
< 0.1%
565 1
< 0.1%
552 1
< 0.1%
527 1
< 0.1%
481 1
< 0.1%
450 1
< 0.1%
437 1
< 0.1%
436 1
< 0.1%
405 1
< 0.1%
404 1
< 0.1%

5종
Real number (ℝ)

ZEROS 

Distinct289
Distinct (%)2.9%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean24.1126
Minimum0
Maximum640
Zeros1361
Zeros (%)13.6%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2023-12-11T06:40:22.332313image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q12
median7
Q324
95-th percentile116
Maximum640
Range640
Interquartile range (IQR)22

Descriptive statistics

Standard deviation45.933481
Coefficient of variation (CV)1.9049576
Kurtosis23.499541
Mean24.1126
Median Absolute Deviation (MAD)6
Skewness4.0045201
Sum241126
Variance2109.8847
MonotonicityNot monotonic
2023-12-11T06:40:22.711694image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 1361
 
13.6%
1 1060
 
10.6%
2 730
 
7.3%
3 570
 
5.7%
4 419
 
4.2%
5 365
 
3.6%
6 345
 
3.5%
7 301
 
3.0%
8 259
 
2.6%
9 231
 
2.3%
Other values (279) 4359
43.6%
ValueCountFrequency (%)
0 1361
13.6%
1 1060
10.6%
2 730
7.3%
3 570
5.7%
4 419
 
4.2%
5 365
 
3.6%
6 345
 
3.5%
7 301
 
3.0%
8 259
 
2.6%
9 231
 
2.3%
ValueCountFrequency (%)
640 1
< 0.1%
587 1
< 0.1%
552 1
< 0.1%
540 1
< 0.1%
468 1
< 0.1%
456 1
< 0.1%
434 1
< 0.1%
423 1
< 0.1%
410 1
< 0.1%
407 1
< 0.1%

6종
Real number (ℝ)

ZEROS 

Distinct163
Distinct (%)1.6%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean13.3061
Minimum0
Maximum320
Zeros1864
Zeros (%)18.6%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2023-12-11T06:40:22.845189image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q11
median5
Q316
95-th percentile59
Maximum320
Range320
Interquartile range (IQR)15

Descriptive statistics

Standard deviation22.758181
Coefficient of variation (CV)1.710357
Kurtosis22.582045
Mean13.3061
Median Absolute Deviation (MAD)5
Skewness3.7980835
Sum133061
Variance517.9348
MonotonicityNot monotonic
2023-12-11T06:40:22.976099image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 1864
18.6%
1 1251
 
12.5%
2 799
 
8.0%
3 623
 
6.2%
5 409
 
4.1%
4 371
 
3.7%
6 344
 
3.4%
7 303
 
3.0%
8 283
 
2.8%
9 230
 
2.3%
Other values (153) 3523
35.2%
ValueCountFrequency (%)
0 1864
18.6%
1 1251
12.5%
2 799
8.0%
3 623
 
6.2%
4 371
 
3.7%
5 409
 
4.1%
6 344
 
3.4%
7 303
 
3.0%
8 283
 
2.8%
9 230
 
2.3%
ValueCountFrequency (%)
320 1
< 0.1%
288 1
< 0.1%
276 1
< 0.1%
241 2
< 0.1%
240 1
< 0.1%
226 1
< 0.1%
223 1
< 0.1%
221 2
< 0.1%
207 1
< 0.1%
195 1
< 0.1%

7종
Real number (ℝ)

ZEROS 

Distinct176
Distinct (%)1.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean7.3517
Minimum0
Maximum752
Zeros4191
Zeros (%)41.9%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2023-12-11T06:40:23.112879image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median1
Q34
95-th percentile38
Maximum752
Range752
Interquartile range (IQR)4

Descriptive statistics

Standard deviation24.848685
Coefficient of variation (CV)3.3799917
Kurtosis184.94674
Mean7.3517
Median Absolute Deviation (MAD)1
Skewness10.247948
Sum73517
Variance617.45715
MonotonicityNot monotonic
2023-12-11T06:40:23.270797image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 4191
41.9%
1 1749
17.5%
2 981
 
9.8%
3 573
 
5.7%
4 348
 
3.5%
5 229
 
2.3%
6 148
 
1.5%
7 142
 
1.4%
8 105
 
1.1%
9 102
 
1.0%
Other values (166) 1432
 
14.3%
ValueCountFrequency (%)
0 4191
41.9%
1 1749
17.5%
2 981
 
9.8%
3 573
 
5.7%
4 348
 
3.5%
5 229
 
2.3%
6 148
 
1.5%
7 142
 
1.4%
8 105
 
1.1%
9 102
 
1.0%
ValueCountFrequency (%)
752 1
< 0.1%
595 1
< 0.1%
563 1
< 0.1%
459 1
< 0.1%
438 1
< 0.1%
346 1
< 0.1%
317 1
< 0.1%
291 1
< 0.1%
267 1
< 0.1%
265 1
< 0.1%

8종
Real number (ℝ)

ZEROS 

Distinct20
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.3789
Minimum0
Maximum26
Zeros8224
Zeros (%)82.2%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2023-12-11T06:40:23.395833image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile2
Maximum26
Range26
Interquartile range (IQR)0

Descriptive statistics

Standard deviation1.2201982
Coefficient of variation (CV)3.2203701
Kurtosis76.769687
Mean0.3789
Median Absolute Deviation (MAD)0
Skewness6.8528461
Sum3789
Variance1.4888837
MonotonicityNot monotonic
2023-12-11T06:40:23.517602image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=20)
ValueCountFrequency (%)
0 8224
82.2%
1 986
 
9.9%
2 387
 
3.9%
3 151
 
1.5%
4 85
 
0.9%
5 48
 
0.5%
6 37
 
0.4%
7 37
 
0.4%
8 13
 
0.1%
9 9
 
0.1%
Other values (10) 23
 
0.2%
ValueCountFrequency (%)
0 8224
82.2%
1 986
 
9.9%
2 387
 
3.9%
3 151
 
1.5%
4 85
 
0.9%
5 48
 
0.5%
6 37
 
0.4%
7 37
 
0.4%
8 13
 
0.1%
9 9
 
0.1%
ValueCountFrequency (%)
26 1
 
< 0.1%
23 1
 
< 0.1%
20 1
 
< 0.1%
18 3
< 0.1%
16 1
 
< 0.1%
15 3
< 0.1%
13 2
 
< 0.1%
12 4
< 0.1%
11 2
 
< 0.1%
10 5
0.1%

9종
Real number (ℝ)

ZEROS 

Distinct10
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.0512
Minimum0
Maximum11
Zeros9741
Zeros (%)97.4%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2023-12-11T06:40:23.606740image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile0
Maximum11
Range11
Interquartile range (IQR)0

Descriptive statistics

Standard deviation0.42331605
Coefficient of variation (CV)8.2678916
Kurtosis208.86643
Mean0.0512
Median Absolute Deviation (MAD)0
Skewness12.953874
Sum512
Variance0.17919648
MonotonicityNot monotonic
2023-12-11T06:40:23.698414image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=10)
ValueCountFrequency (%)
0 9741
97.4%
1 158
 
1.6%
2 48
 
0.5%
3 21
 
0.2%
6 10
 
0.1%
4 8
 
0.1%
8 7
 
0.1%
7 3
 
< 0.1%
5 3
 
< 0.1%
11 1
 
< 0.1%
ValueCountFrequency (%)
0 9741
97.4%
1 158
 
1.6%
2 48
 
0.5%
3 21
 
0.2%
4 8
 
0.1%
5 3
 
< 0.1%
6 10
 
0.1%
7 3
 
< 0.1%
8 7
 
0.1%
11 1
 
< 0.1%
ValueCountFrequency (%)
11 1
 
< 0.1%
8 7
 
0.1%
7 3
 
< 0.1%
6 10
 
0.1%
5 3
 
< 0.1%
4 8
 
0.1%
3 21
 
0.2%
2 48
 
0.5%
1 158
 
1.6%
0 9741
97.4%

10종
Real number (ℝ)

ZEROS 

Distinct136
Distinct (%)1.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean5.4203
Minimum0
Maximum309
Zeros5013
Zeros (%)50.1%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2023-12-11T06:40:23.805086image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q33
95-th percentile30
Maximum309
Range309
Interquartile range (IQR)3

Descriptive statistics

Standard deviation15.886141
Coefficient of variation (CV)2.9308602
Kurtosis71.934379
Mean5.4203
Median Absolute Deviation (MAD)0
Skewness6.7449437
Sum54203
Variance252.36948
MonotonicityNot monotonic
2023-12-11T06:40:23.925721image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 5013
50.1%
1 1509
 
15.1%
2 818
 
8.2%
3 426
 
4.3%
4 268
 
2.7%
5 179
 
1.8%
6 140
 
1.4%
7 124
 
1.2%
10 96
 
1.0%
9 94
 
0.9%
Other values (126) 1333
 
13.3%
ValueCountFrequency (%)
0 5013
50.1%
1 1509
 
15.1%
2 818
 
8.2%
3 426
 
4.3%
4 268
 
2.7%
5 179
 
1.8%
6 140
 
1.4%
7 124
 
1.2%
8 93
 
0.9%
9 94
 
0.9%
ValueCountFrequency (%)
309 1
< 0.1%
299 1
< 0.1%
297 1
< 0.1%
239 1
< 0.1%
224 1
< 0.1%
213 1
< 0.1%
205 1
< 0.1%
189 1
< 0.1%
178 1
< 0.1%
165 2
< 0.1%

11종
Real number (ℝ)

ZEROS 

Distinct16
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.1435
Minimum0
Maximum19
Zeros9226
Zeros (%)92.3%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2023-12-11T06:40:24.025998image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile1
Maximum19
Range19
Interquartile range (IQR)0

Descriptive statistics

Standard deviation0.70139643
Coefficient of variation (CV)4.88778
Kurtosis167.60626
Mean0.1435
Median Absolute Deviation (MAD)0
Skewness10.353223
Sum1435
Variance0.49195695
MonotonicityNot monotonic
2023-12-11T06:40:24.134324image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=16)
ValueCountFrequency (%)
0 9226
92.3%
1 467
 
4.7%
2 181
 
1.8%
3 53
 
0.5%
4 33
 
0.3%
5 12
 
0.1%
6 7
 
0.1%
7 5
 
0.1%
10 3
 
< 0.1%
9 3
 
< 0.1%
Other values (6) 10
 
0.1%
ValueCountFrequency (%)
0 9226
92.3%
1 467
 
4.7%
2 181
 
1.8%
3 53
 
0.5%
4 33
 
0.3%
5 12
 
0.1%
6 7
 
0.1%
7 5
 
0.1%
8 3
 
< 0.1%
9 3
 
< 0.1%
ValueCountFrequency (%)
19 1
 
< 0.1%
17 1
 
< 0.1%
13 2
 
< 0.1%
12 2
 
< 0.1%
11 1
 
< 0.1%
10 3
< 0.1%
9 3
< 0.1%
8 3
< 0.1%
7 5
0.1%
6 7
0.1%

12종
Real number (ℝ)

ZEROS 

Distinct62
Distinct (%)0.6%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.9417
Minimum0
Maximum127
Zeros8082
Zeros (%)80.8%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2023-12-11T06:40:24.263276image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile4
Maximum127
Range127
Interquartile range (IQR)0

Descriptive statistics

Standard deviation4.5573433
Coefficient of variation (CV)4.8394853
Kurtosis208.20705
Mean0.9417
Median Absolute Deviation (MAD)0
Skewness11.908356
Sum9417
Variance20.769378
MonotonicityNot monotonic
2023-12-11T06:40:24.380937image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 8082
80.8%
1 805
 
8.1%
2 390
 
3.9%
3 161
 
1.6%
4 88
 
0.9%
5 82
 
0.8%
6 55
 
0.5%
7 44
 
0.4%
9 32
 
0.3%
8 31
 
0.3%
Other values (52) 230
 
2.3%
ValueCountFrequency (%)
0 8082
80.8%
1 805
 
8.1%
2 390
 
3.9%
3 161
 
1.6%
4 88
 
0.9%
5 82
 
0.8%
6 55
 
0.5%
7 44
 
0.4%
8 31
 
0.3%
9 32
 
0.3%
ValueCountFrequency (%)
127 1
< 0.1%
114 1
< 0.1%
105 1
< 0.1%
97 1
< 0.1%
83 1
< 0.1%
77 1
< 0.1%
73 1
< 0.1%
69 1
< 0.1%
62 1
< 0.1%
61 1
< 0.1%

전차종합계
Real number (ℝ)

Distinct2701
Distinct (%)27.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean858.5663
Minimum0
Maximum9816
Zeros66
Zeros (%)0.7%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2023-12-11T06:40:24.503179image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile7
Q188
median309
Q3969
95-th percentile4127.25
Maximum9816
Range9816
Interquartile range (IQR)881

Descriptive statistics

Standard deviation1348.64
Coefficient of variation (CV)1.5708047
Kurtosis7.2781957
Mean858.5663
Median Absolute Deviation (MAD)277
Skewness2.6158158
Sum8585663
Variance1818829.9
MonotonicityNot monotonic
2023-12-11T06:40:24.613003image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 84
 
0.8%
2 70
 
0.7%
3 67
 
0.7%
0 66
 
0.7%
4 60
 
0.6%
7 60
 
0.6%
6 58
 
0.6%
9 56
 
0.6%
5 54
 
0.5%
11 51
 
0.5%
Other values (2691) 9374
93.7%
ValueCountFrequency (%)
0 66
0.7%
1 84
0.8%
2 70
0.7%
3 67
0.7%
4 60
0.6%
5 54
0.5%
6 58
0.6%
7 60
0.6%
8 44
0.4%
9 56
0.6%
ValueCountFrequency (%)
9816 1
< 0.1%
9808 1
< 0.1%
9784 1
< 0.1%
9246 1
< 0.1%
9124 1
< 0.1%
8272 1
< 0.1%
8225 1
< 0.1%
8201 1
< 0.1%
8172 1
< 0.1%
8063 1
< 0.1%

Sample

년도도로종류도로종류코드지점번호호선명호선코드상/하행상/하행코드시간대시간대코드지역지역코드구간명1종2종3종4종5종6종7종8종9종10종11종12종전차종합계
117502022일반국도24802-05일반국도 48호선48.0하행217시~18시17경기 김포 양촌면3123032김포 → 강화1221201514216212000001473
164952022국가지원지방도370-08국가지원지방도 70호선70.0하행212시~13시12경기 양평 지평면3138039지평 → 이포대교78323463000000117
102672022국가지원지방도357-11국가지원지방도 57호선57.0하행222시~23시22경기 의왕 청계동3117056의왕 → 과천518339423100000570
99032022국가지원지방도357-08국가지원지방도 57호선57.0하행217시~18시17경기 광주 오포읍3125011광주 → 수지866512018721000001019
205222022지방도40357-03지방도 357호선357.0상행106시~07시6경기 고양 일산서 송산동3110459법곳IC → 송산IC10643329977642710004041582
19912022고속국도111005제2경인고속도로110.0상행100시~01시24경기 시흥 신현동3115053신천IC → 안현JCT49886023301215001711665
102682022국가지원지방도357-11국가지원지방도 57호선57.0상행123시~24시23경기 의왕 청계동3117056과천 → 의왕273221212100000302
29472022고속국도113003인천국제공항고속도로130.0상행110시~11시10인천 계양 계양1동2307060북인천IC → 청라IC80327722158000101938
40782022일반국도23803-01일반국도 38호선38.0상행109시~10시9경기 안성 공도읍3122011평택 → 안성1270461733936123205001586
13562022고속국도110019수도권제1순환고속도로100.0상행122시~23시22경기 부천 원미 중동3105162중동IC → 송내IC3771352459319712112018004384
년도도로종류도로종류코드지점번호호선명호선코드상/하행상/하행코드시간대시간대코드지역지역코드구간명1종2종3종4종5종6종7종8종9종10종11종12종전차종합계
136372022국가지원지방도386-08국가지원지방도 86호선86.0상행111시~12시11경기 양평 서종면3138035청평 → 서종IC10965000000000120
171412022국가지원지방도388-02국가지원지방도 88호선88.0하행221시~22시21경기 양평 강상면3138031화양 → 강하181324431000000216
158552022국가지원지방도398-17국가지원지방도 98호선98.0하행218시~19시18경기 파주 광탄면3120035덕양 → 광적6721020000000081
223392022지방도40333-10지방도 333호선333.0하행207시~08시7경기 여주 능서면3128032장호원 → 이천53700000000000537
219402022지방도40333-10지방도 333호선333.0상행114시~15시14경기 여주 능서면3128032이천 → 장호원72600000000000726
9672022고속국도110023수도권제1순환고속도로100.0상행121시~22시21경기 김포 고촌면3123031김포IC → 노오지JCT335329242455913160013123773
191602022지방도40345-06지방도 345호선345.0하행217시~18시17경기 여주 강천면3128038양동 → 대신401911110000054
143972022지방도40329-05지방도 329호선329.0하행208시~09시8경기 안성 일죽면3122039장호원 → 일죽IC1155371636271000301250
130512022일반국도23910-00일반국도 39호선39.0상행117시~18시17경기 시흥 은행동3115054인천 → 안양7196144070200000878
222362022지방도40313-05지방도 313호선313.0하행200시~01시24경기 평택 안중읍3107012아산만 → 평택6010000000007