Overview

Dataset statistics

Number of variables11
Number of observations319
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory30.7 KiB
Average record size in memory98.4 B

Variable types

Text1
Numeric10

Dataset

Description부산광역시 연간 시내버스 마을버스 노선 별 총 이용 건수에 대한 데이터로 1통행, 2통행, 3통행별 일반, 청소년, 어린이별 이용건수를 제공합니다.
Author부산광역시
URLhttps://www.data.go.kr/data/15095329/fileData.do

Alerts

건수(1통행)_일반 is highly overall correlated with 건수(1통행)_청소년 and 8 other fieldsHigh correlation
건수(1통행)_청소년 is highly overall correlated with 건수(1통행)_일반 and 8 other fieldsHigh correlation
건수(1통행)_어린이 is highly overall correlated with 건수(1통행)_일반 and 8 other fieldsHigh correlation
건수(2통행)_일반 is highly overall correlated with 건수(1통행)_일반 and 8 other fieldsHigh correlation
건수(2통행)_청소년 is highly overall correlated with 건수(1통행)_일반 and 8 other fieldsHigh correlation
건수(2통행)_어린이 is highly overall correlated with 건수(1통행)_일반 and 8 other fieldsHigh correlation
건수(3통행)_일반 is highly overall correlated with 건수(1통행)_일반 and 8 other fieldsHigh correlation
건수(3통행)_청소년 is highly overall correlated with 건수(1통행)_일반 and 8 other fieldsHigh correlation
건수(3통행)_어린이 is highly overall correlated with 건수(1통행)_일반 and 8 other fieldsHigh correlation
교통카드건수합계 is highly overall correlated with 건수(1통행)_일반 and 8 other fieldsHigh correlation
노선 has unique valuesUnique
건수(1통행)_일반 has unique valuesUnique
건수(1통행)_청소년 has unique valuesUnique
건수(2통행)_일반 has unique valuesUnique
교통카드건수합계 has unique valuesUnique
건수(2통행)_청소년 has 4 (1.3%) zerosZeros
건수(2통행)_어린이 has 9 (2.8%) zerosZeros
건수(3통행)_청소년 has 5 (1.6%) zerosZeros
건수(3통행)_어린이 has 22 (6.9%) zerosZeros

Reproduction

Analysis started2023-12-12 06:12:17.958688
Analysis finished2023-12-12 06:12:29.979944
Duration12.02 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

노선
Text

UNIQUE 

Distinct319
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size2.6 KiB
2023-12-12T15:12:30.350249image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length10
Median length8
Mean length4.3291536
Min length1

Characters and Unicode

Total characters1381
Distinct characters82
Distinct categories6 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique319 ?
Unique (%)100.0%

Sample

1st row10
2nd row100
3rd row1000(급행)
4th row1000(심야)
5th row100-1
ValueCountFrequency (%)
10 1
 
0.3%
남구2 1
 
0.3%
남구1(오전 1
 
0.3%
남구1 1
 
0.3%
기장군7(예림 1
 
0.3%
기장군7(병산 1
 
0.3%
기장군6 1
 
0.3%
기장군5(월평 1
 
0.3%
기장군2-3 1
 
0.3%
기장군10(신명 1
 
0.3%
Other values (309) 309
96.9%
2023-12-12T15:12:30.958420image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 205
 
14.8%
128
 
9.3%
2 83
 
6.0%
0 76
 
5.5%
3 62
 
4.5%
- 60
 
4.3%
8 58
 
4.2%
5 44
 
3.2%
) 41
 
3.0%
( 41
 
3.0%
Other values (72) 583
42.2%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 659
47.7%
Other Letter 576
41.7%
Dash Punctuation 60
 
4.3%
Close Punctuation 41
 
3.0%
Open Punctuation 41
 
3.0%
Uppercase Letter 4
 
0.3%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
128
22.2%
33
 
5.7%
28
 
4.9%
25
 
4.3%
24
 
4.2%
23
 
4.0%
18
 
3.1%
16
 
2.8%
15
 
2.6%
15
 
2.6%
Other values (57) 251
43.6%
Decimal Number
ValueCountFrequency (%)
1 205
31.1%
2 83
12.6%
0 76
 
11.5%
3 62
 
9.4%
8 58
 
8.8%
5 44
 
6.7%
6 38
 
5.8%
7 36
 
5.5%
9 34
 
5.2%
4 23
 
3.5%
Uppercase Letter
ValueCountFrequency (%)
A 2
50.0%
B 2
50.0%
Dash Punctuation
ValueCountFrequency (%)
- 60
100.0%
Close Punctuation
ValueCountFrequency (%)
) 41
100.0%
Open Punctuation
ValueCountFrequency (%)
( 41
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 801
58.0%
Hangul 576
41.7%
Latin 4
 
0.3%

Most frequent character per script

Hangul
ValueCountFrequency (%)
128
22.2%
33
 
5.7%
28
 
4.9%
25
 
4.3%
24
 
4.2%
23
 
4.0%
18
 
3.1%
16
 
2.8%
15
 
2.6%
15
 
2.6%
Other values (57) 251
43.6%
Common
ValueCountFrequency (%)
1 205
25.6%
2 83
10.4%
0 76
 
9.5%
3 62
 
7.7%
- 60
 
7.5%
8 58
 
7.2%
5 44
 
5.5%
) 41
 
5.1%
( 41
 
5.1%
6 38
 
4.7%
Other values (3) 93
11.6%
Latin
ValueCountFrequency (%)
A 2
50.0%
B 2
50.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 805
58.3%
Hangul 576
41.7%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 205
25.5%
2 83
10.3%
0 76
 
9.4%
3 62
 
7.7%
- 60
 
7.5%
8 58
 
7.2%
5 44
 
5.5%
) 41
 
5.1%
( 41
 
5.1%
6 38
 
4.7%
Other values (5) 97
12.0%
Hangul
ValueCountFrequency (%)
128
22.2%
33
 
5.7%
28
 
4.9%
25
 
4.3%
24
 
4.2%
23
 
4.0%
18
 
3.1%
16
 
2.8%
15
 
2.6%
15
 
2.6%
Other values (57) 251
43.6%

건수(1통행)_일반
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct319
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean909718.59
Minimum4
Maximum4572116
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size2.9 KiB
2023-12-12T15:12:31.120793image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum4
5-th percentile7490
Q1108030.5
median394674
Q31415491
95-th percentile3342119.2
Maximum4572116
Range4572112
Interquartile range (IQR)1307460.5

Descriptive statistics

Standard deviation1101940.5
Coefficient of variation (CV)1.2112982
Kurtosis1.0746611
Mean909718.59
Median Absolute Deviation (MAD)358819
Skewness1.4143419
Sum2.9020023 × 108
Variance1.2142728 × 1012
MonotonicityNot monotonic
2023-12-12T15:12:31.258376image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
2080493 1
 
0.3%
1110618 1
 
0.3%
341364 1
 
0.3%
70815 1
 
0.3%
488451 1
 
0.3%
4375 1
 
0.3%
369 1
 
0.3%
107699 1
 
0.3%
11050 1
 
0.3%
44263 1
 
0.3%
Other values (309) 309
96.9%
ValueCountFrequency (%)
4 1
0.3%
23 1
0.3%
193 1
0.3%
369 1
0.3%
470 1
0.3%
722 1
0.3%
1315 1
0.3%
1877 1
0.3%
2218 1
0.3%
2746 1
0.3%
ValueCountFrequency (%)
4572116 1
0.3%
4487024 1
0.3%
4260560 1
0.3%
4190379 1
0.3%
4156045 1
0.3%
4137408 1
0.3%
4136923 1
0.3%
3987743 1
0.3%
3726124 1
0.3%
3685918 1
0.3%

건수(1통행)_청소년
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct319
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean80566.586
Minimum0
Maximum555893
Zeros1
Zeros (%)0.3%
Negative0
Negative (%)0.0%
Memory size2.9 KiB
2023-12-12T15:12:31.381105image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile285.8
Q15689
median37663
Q3123944.5
95-th percentile306648.9
Maximum555893
Range555893
Interquartile range (IQR)118255.5

Descriptive statistics

Standard deviation104651.58
Coefficient of variation (CV)1.2989452
Kurtosis2.9937268
Mean80566.586
Median Absolute Deviation (MAD)35426
Skewness1.7704563
Sum25700741
Variance1.0951953 × 1010
MonotonicityNot monotonic
2023-12-12T15:12:31.491882image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
306390 1
 
0.3%
79088 1
 
0.3%
46569 1
 
0.3%
9918 1
 
0.3%
66969 1
 
0.3%
1023 1
 
0.3%
27 1
 
0.3%
9469 1
 
0.3%
4257 1
 
0.3%
1172 1
 
0.3%
Other values (309) 309
96.9%
ValueCountFrequency (%)
0 1
0.3%
3 1
0.3%
5 1
0.3%
10 1
0.3%
27 1
0.3%
33 1
0.3%
36 1
0.3%
69 1
0.3%
105 1
0.3%
121 1
0.3%
ValueCountFrequency (%)
555893 1
0.3%
455930 1
0.3%
446766 1
0.3%
435931 1
0.3%
422544 1
0.3%
414790 1
0.3%
407841 1
0.3%
406271 1
0.3%
400326 1
0.3%
383202 1
0.3%

건수(1통행)_어린이
Real number (ℝ)

HIGH CORRELATION 

Distinct312
Distinct (%)97.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean16944.125
Minimum0
Maximum132487
Zeros3
Zeros (%)0.9%
Negative0
Negative (%)0.0%
Memory size2.9 KiB
2023-12-12T15:12:31.915568image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile33.9
Q11149.5
median8866
Q324280.5
95-th percentile59689.1
Maximum132487
Range132487
Interquartile range (IQR)23131

Descriptive statistics

Standard deviation20856.091
Coefficient of variation (CV)1.2308745
Kurtosis4.2424863
Mean16944.125
Median Absolute Deviation (MAD)8650
Skewness1.8559464
Sum5405176
Variance4.3497655 × 108
MonotonicityNot monotonic
2023-12-12T15:12:32.035438image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 3
 
0.9%
19 3
 
0.9%
55 2
 
0.6%
15 2
 
0.6%
12740 2
 
0.6%
11563 1
 
0.3%
10831 1
 
0.3%
2190 1
 
0.3%
15390 1
 
0.3%
386 1
 
0.3%
Other values (302) 302
94.7%
ValueCountFrequency (%)
0 3
0.9%
2 1
 
0.3%
8 1
 
0.3%
10 1
 
0.3%
15 2
0.6%
16 1
 
0.3%
17 1
 
0.3%
19 3
0.9%
30 1
 
0.3%
31 1
 
0.3%
ValueCountFrequency (%)
132487 1
0.3%
98993 1
0.3%
90423 1
0.3%
83032 1
0.3%
81390 1
0.3%
78566 1
0.3%
77225 1
0.3%
77181 1
0.3%
75013 1
0.3%
74259 1
0.3%

건수(2통행)_일반
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct319
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean256251.42
Minimum0
Maximum1500633
Zeros1
Zeros (%)0.3%
Negative0
Negative (%)0.0%
Memory size2.9 KiB
2023-12-12T15:12:32.151200image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile1186.9
Q134205
median124742
Q3383490
95-th percentile900630.5
Maximum1500633
Range1500633
Interquartile range (IQR)349285

Descriptive statistics

Standard deviation305889.73
Coefficient of variation (CV)1.1937094
Kurtosis1.9297338
Mean256251.42
Median Absolute Deviation (MAD)111405
Skewness1.5526113
Sum81744204
Variance9.3568526 × 1010
MonotonicityNot monotonic
2023-12-12T15:12:32.272410image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
552536 1
 
0.3%
218334 1
 
0.3%
111785 1
 
0.3%
19655 1
 
0.3%
157101 1
 
0.3%
612 1
 
0.3%
57 1
 
0.3%
14025 1
 
0.3%
1830 1
 
0.3%
13337 1
 
0.3%
Other values (309) 309
96.9%
ValueCountFrequency (%)
0 1
0.3%
4 1
0.3%
8 1
0.3%
57 1
0.3%
184 1
0.3%
190 1
0.3%
191 1
0.3%
332 1
0.3%
358 1
0.3%
585 1
0.3%
ValueCountFrequency (%)
1500633 1
0.3%
1311685 1
0.3%
1279329 1
0.3%
1262973 1
0.3%
1189127 1
0.3%
1186071 1
0.3%
1171011 1
0.3%
1143189 1
0.3%
1103068 1
0.3%
1086221 1
0.3%

건수(2통행)_청소년
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct313
Distinct (%)98.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean13987.498
Minimum0
Maximum75922
Zeros4
Zeros (%)1.3%
Negative0
Negative (%)0.0%
Memory size2.9 KiB
2023-12-12T15:12:32.382019image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile40
Q11371
median7535
Q321271
95-th percentile45109
Maximum75922
Range75922
Interquartile range (IQR)19900

Descriptive statistics

Standard deviation15912.256
Coefficient of variation (CV)1.1376055
Kurtosis1.4784239
Mean13987.498
Median Absolute Deviation (MAD)7208
Skewness1.3892724
Sum4462012
Variance2.5319988 × 108
MonotonicityNot monotonic
2023-12-12T15:12:32.492495image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 4
 
1.3%
40 2
 
0.6%
27 2
 
0.6%
6483 2
 
0.6%
534 1
 
0.3%
9823 1
 
0.3%
2758 1
 
0.3%
13506 1
 
0.3%
17 1
 
0.3%
467 1
 
0.3%
Other values (303) 303
95.0%
ValueCountFrequency (%)
0 4
1.3%
2 1
 
0.3%
4 1
 
0.3%
5 1
 
0.3%
8 1
 
0.3%
10 1
 
0.3%
12 1
 
0.3%
17 1
 
0.3%
19 1
 
0.3%
20 1
 
0.3%
ValueCountFrequency (%)
75922 1
0.3%
72581 1
0.3%
65145 1
0.3%
65044 1
0.3%
64218 1
0.3%
61554 1
0.3%
61162 1
0.3%
58327 1
0.3%
49947 1
0.3%
49928 1
0.3%

건수(2통행)_어린이
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct281
Distinct (%)88.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1303.0627
Minimum0
Maximum6823
Zeros9
Zeros (%)2.8%
Negative0
Negative (%)0.0%
Memory size2.9 KiB
2023-12-12T15:12:32.601458image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile2
Q1167
median832
Q31961.5
95-th percentile4616.1
Maximum6823
Range6823
Interquartile range (IQR)1794.5

Descriptive statistics

Standard deviation1501.8869
Coefficient of variation (CV)1.1525822
Kurtosis1.9594629
Mean1303.0627
Median Absolute Deviation (MAD)738
Skewness1.5368494
Sum415677
Variance2255664.3
MonotonicityNot monotonic
2023-12-12T15:12:32.712674image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 9
 
2.8%
2 6
 
1.9%
6 4
 
1.3%
3 4
 
1.3%
1 4
 
1.3%
53 3
 
0.9%
179 3
 
0.9%
13 3
 
0.9%
372 2
 
0.6%
35 2
 
0.6%
Other values (271) 279
87.5%
ValueCountFrequency (%)
0 9
2.8%
1 4
1.3%
2 6
1.9%
3 4
1.3%
4 2
 
0.6%
5 1
 
0.3%
6 4
1.3%
9 1
 
0.3%
10 2
 
0.6%
11 2
 
0.6%
ValueCountFrequency (%)
6823 1
0.3%
6607 1
0.3%
6456 1
0.3%
6255 1
0.3%
6223 1
0.3%
5906 1
0.3%
5557 1
0.3%
5533 1
0.3%
5425 2
0.6%
5262 1
0.3%

건수(3통행)_일반
Real number (ℝ)

HIGH CORRELATION 

Distinct317
Distinct (%)99.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean45417.561
Minimum0
Maximum208087
Zeros2
Zeros (%)0.6%
Negative0
Negative (%)0.0%
Memory size2.9 KiB
2023-12-12T15:12:32.839298image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile417.3
Q18492.5
median29059
Q369678.5
95-th percentile140564.4
Maximum208087
Range208087
Interquartile range (IQR)61186

Descriptive statistics

Standard deviation47053.032
Coefficient of variation (CV)1.0360097
Kurtosis0.79554144
Mean45417.561
Median Absolute Deviation (MAD)24523
Skewness1.2234142
Sum14488202
Variance2.2139879 × 109
MonotonicityNot monotonic
2023-12-12T15:12:32.951649image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 2
 
0.6%
420 2
 
0.6%
247 1
 
0.3%
443 1
 
0.3%
21113 1
 
0.3%
22028 1
 
0.3%
3639 1
 
0.3%
31372 1
 
0.3%
251 1
 
0.3%
46 1
 
0.3%
Other values (307) 307
96.2%
ValueCountFrequency (%)
0 2
0.6%
1 1
0.3%
46 1
0.3%
58 1
0.3%
74 1
0.3%
89 1
0.3%
90 1
0.3%
152 1
0.3%
206 1
0.3%
217 1
0.3%
ValueCountFrequency (%)
208087 1
0.3%
206642 1
0.3%
194260 1
0.3%
178382 1
0.3%
178354 1
0.3%
171127 1
0.3%
169913 1
0.3%
166825 1
0.3%
165559 1
0.3%
162987 1
0.3%

건수(3통행)_청소년
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct283
Distinct (%)88.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1743.7053
Minimum0
Maximum13631
Zeros5
Zeros (%)1.6%
Negative0
Negative (%)0.0%
Memory size2.9 KiB
2023-12-12T15:12:33.066729image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile8.8
Q1224
median1037
Q32587.5
95-th percentile5291.2
Maximum13631
Range13631
Interquartile range (IQR)2363.5

Descriptive statistics

Standard deviation2001.1148
Coefficient of variation (CV)1.1476221
Kurtosis5.8425023
Mean1743.7053
Median Absolute Deviation (MAD)948
Skewness1.9961988
Sum556242
Variance4004460.6
MonotonicityNot monotonic
2023-12-12T15:12:33.199756image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 5
 
1.6%
7 4
 
1.3%
20 4
 
1.3%
117 3
 
0.9%
1820 2
 
0.6%
1897 2
 
0.6%
791 2
 
0.6%
6 2
 
0.6%
171 2
 
0.6%
794 2
 
0.6%
Other values (273) 291
91.2%
ValueCountFrequency (%)
0 5
1.6%
1 1
 
0.3%
2 1
 
0.3%
3 1
 
0.3%
5 2
 
0.6%
6 2
 
0.6%
7 4
1.3%
9 2
 
0.6%
10 1
 
0.3%
12 2
 
0.6%
ValueCountFrequency (%)
13631 1
0.3%
11288 1
0.3%
8744 1
0.3%
8586 1
0.3%
8309 1
0.3%
7907 1
0.3%
7746 1
0.3%
7189 1
0.3%
6876 1
0.3%
6771 1
0.3%

건수(3통행)_어린이
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct198
Distinct (%)62.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean131.62382
Minimum0
Maximum636
Zeros22
Zeros (%)6.9%
Negative0
Negative (%)0.0%
Memory size2.9 KiB
2023-12-12T15:12:33.318073image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q119
median89
Q3201
95-th percentile413.3
Maximum636
Range636
Interquartile range (IQR)182

Descriptive statistics

Standard deviation136.886
Coefficient of variation (CV)1.0399789
Kurtosis0.95964593
Mean131.62382
Median Absolute Deviation (MAD)81
Skewness1.208884
Sum41988
Variance18737.776
MonotonicityNot monotonic
2023-12-12T15:12:33.435341image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 22
 
6.9%
1 12
 
3.8%
3 6
 
1.9%
2 5
 
1.6%
22 5
 
1.6%
5 4
 
1.3%
7 4
 
1.3%
77 4
 
1.3%
41 3
 
0.9%
36 3
 
0.9%
Other values (188) 251
78.7%
ValueCountFrequency (%)
0 22
6.9%
1 12
3.8%
2 5
 
1.6%
3 6
 
1.9%
4 3
 
0.9%
5 4
 
1.3%
6 2
 
0.6%
7 4
 
1.3%
8 3
 
0.9%
10 1
 
0.3%
ValueCountFrequency (%)
636 1
0.3%
619 1
0.3%
595 1
0.3%
552 1
0.3%
502 1
0.3%
485 1
0.3%
474 2
0.6%
471 1
0.3%
470 1
0.3%
449 1
0.3%

교통카드건수합계
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct319
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1326064.2
Minimum4
Maximum6662068
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size2.9 KiB
2023-12-12T15:12:33.565787image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum4
5-th percentile9803.9
Q1167251.5
median605243
Q32068251
95-th percentile4774898.4
Maximum6662068
Range6662064
Interquartile range (IQR)1900999.5

Descriptive statistics

Standard deviation1578476
Coefficient of variation (CV)1.1903466
Kurtosis1.1290465
Mean1326064.2
Median Absolute Deviation (MAD)554239
Skewness1.4162518
Sum4.2301447 × 108
Variance2.4915864 × 1012
MonotonicityNot monotonic
2023-12-12T15:12:33.744422image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
3149157 1
 
0.3%
1472480 1
 
0.3%
544188 1
 
0.3%
109377 1
 
0.3%
775453 1
 
0.3%
6676 1
 
0.3%
516 1
 
0.3%
138835 1
 
0.3%
19561 1
 
0.3%
64509 1
 
0.3%
Other values (309) 309
96.9%
ValueCountFrequency (%)
4 1
0.3%
34 1
0.3%
203 1
0.3%
516 1
0.3%
785 1
0.3%
1018 1
0.3%
2758 1
0.3%
2808 1
0.3%
3080 1
0.3%
4970 1
0.3%
ValueCountFrequency (%)
6662068 1
0.3%
6350550 1
0.3%
6162725 1
0.3%
6112255 1
0.3%
5979111 1
0.3%
5935074 1
0.3%
5934732 1
0.3%
5558334 1
0.3%
5552128 1
0.3%
5481708 1
0.3%

Interactions

2023-12-12T15:12:28.515139image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:12:18.396072image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:12:19.414255image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:12:20.489277image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:12:21.639561image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:12:22.826281image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:12:23.914568image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:12:25.295380image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:12:26.248240image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:12:27.367266image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:12:28.627151image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:12:18.480149image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:12:19.508162image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:12:20.586662image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:12:21.750588image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:12:22.930155image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:12:24.042956image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:12:25.371186image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:12:26.337808image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:12:27.467250image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:12:28.728600image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:12:18.581226image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:12:19.600636image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:12:20.699272image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:12:21.866132image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:12:23.041381image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:12:24.154320image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:12:25.461264image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:12:26.431386image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:12:27.590613image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:12:28.866581image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:12:18.677955image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:12:19.714119image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:12:20.809827image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:12:21.991193image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:12:23.139540image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:12:24.270967image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:12:25.557604image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:12:26.533414image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:12:27.707859image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:12:28.984562image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:12:18.783101image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:12:19.832577image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:12:20.917856image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:12:22.116513image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:12:23.244802image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:12:24.394984image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:12:25.658915image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:12:26.648882image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:12:27.839852image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:12:29.095787image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:12:18.886514image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:12:19.939374image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:12:21.057042image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:12:22.226098image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:12:23.342488image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:12:24.517130image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:12:25.775135image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:12:26.770036image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:12:27.979021image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:12:29.201519image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:12:18.991632image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:12:20.059685image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:12:21.199424image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:12:22.355139image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:12:23.452820image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:12:24.643416image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:12:25.882981image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:12:26.892371image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:12:28.096276image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:12:29.311688image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:12:19.091505image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:12:20.157326image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:12:21.297882image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:12:22.482875image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:12:23.559349image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:12:24.739300image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:12:25.977833image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:12:27.012542image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:12:28.193397image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:12:29.435842image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:12:19.194863image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:12:20.270948image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:12:21.406668image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:12:22.605714image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:12:23.666343image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:12:24.841581image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:12:26.074461image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:12:27.118468image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:12:28.313726image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:12:29.540387image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:12:19.321713image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:12:20.376863image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:12:21.523305image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:12:22.727359image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:12:23.769224image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:12:25.205482image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:12:26.163212image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:12:27.251617image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:12:28.409466image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-12T15:12:33.866064image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
건수(1통행)_일반건수(1통행)_청소년건수(1통행)_어린이건수(2통행)_일반건수(2통행)_청소년건수(2통행)_어린이건수(3통행)_일반건수(3통행)_청소년건수(3통행)_어린이교통카드건수합계
건수(1통행)_일반1.0000.8670.7700.9470.8760.8810.8990.5860.8910.988
건수(1통행)_청소년0.8671.0000.8630.8600.8920.8830.8220.6530.8610.884
건수(1통행)_어린이0.7700.8631.0000.7070.7810.8100.7500.7790.7790.764
건수(2통행)_일반0.9470.8600.7071.0000.9010.8950.9240.6290.8870.951
건수(2통행)_청소년0.8760.8920.7810.9011.0000.9110.8940.7580.8820.880
건수(2통행)_어린이0.8810.8830.8100.8950.9111.0000.9100.6660.9060.910
건수(3통행)_일반0.8990.8220.7500.9240.8940.9101.0000.7340.9030.905
건수(3통행)_청소년0.5860.6530.7790.6290.7580.6660.7341.0000.6810.643
건수(3통행)_어린이0.8910.8610.7790.8870.8820.9060.9030.6811.0000.900
교통카드건수합계0.9880.8840.7640.9510.8800.9100.9050.6430.9001.000
2023-12-12T15:12:33.999758image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
건수(1통행)_일반건수(1통행)_청소년건수(1통행)_어린이건수(2통행)_일반건수(2통행)_청소년건수(2통행)_어린이건수(3통행)_일반건수(3통행)_청소년건수(3통행)_어린이교통카드건수합계
건수(1통행)_일반1.0000.9580.9320.9820.9280.9440.9520.8550.9250.997
건수(1통행)_청소년0.9581.0000.9420.9370.9370.9270.9110.8800.9050.961
건수(1통행)_어린이0.9320.9421.0000.9050.8830.9600.8850.8080.9340.932
건수(2통행)_일반0.9820.9370.9051.0000.9590.9450.9780.8930.9190.990
건수(2통행)_청소년0.9280.9370.8830.9591.0000.9310.9490.9530.8890.947
건수(2통행)_어린이0.9440.9270.9600.9450.9311.0000.9260.8520.9570.949
건수(3통행)_일반0.9520.9110.8850.9780.9490.9261.0000.9220.9100.966
건수(3통행)_청소년0.8550.8800.8080.8930.9530.8520.9221.0000.8350.879
건수(3통행)_어린이0.9250.9050.9340.9190.8890.9570.9100.8351.0000.928
교통카드건수합계0.9970.9610.9320.9900.9470.9490.9660.8790.9281.000

Missing values

2023-12-12T15:12:29.683927image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-12T15:12:29.894600image/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

노선건수(1통행)_일반건수(1통행)_청소년건수(1통행)_어린이건수(2통행)_일반건수(2통행)_청소년건수(2통행)_어린이건수(3통행)_일반건수(3통행)_청소년건수(3통행)_어린이교통카드건수합계
01020804933063904968755253642617366210761557653923149157
11001110618790881338021833497009253927210301331472480
21000(급행)41198716316342010784744304391358742957558512
31000(심야)6258218273182491760128623074174
4100-11407263128441215083418841635814166114321362131980362
51001(급행)2310568126565159445782263094620665293130632603120569
61001(심야)62570304010182333502106523175385
71002(급행)1107321690876490344459191081134449561627771594259
81002(심야)381171886194219173266719045102
91003(급행)205630499861198753504781494613043299211851202577065
노선건수(1통행)_일반건수(1통행)_청소년건수(1통행)_어린이건수(2통행)_일반건수(2통행)_청소년건수(2통행)_어린이건수(3통행)_일반건수(3통행)_청소년건수(3통행)_어린이교통카드건수합계
309영도구77575236756921286426031741153111722127437
310중구169733754317196411946311927911595342919131141041820
311해운대1010895937381499319321368186751523014155441
312해운대249799718493793912937749256563071486656691023
313해운대3-1477713437392216317285913775105549326161480782324
314해운대구3176784704463495565028843551788834848267350
315해운대구3-21821352872666766240332413051606633422299908
316해운대구7222761807438455599018634371500835320308351
317해운대구8417732237722136454916831801611862295
318해운대구9667642393565153046966238141901589803