Overview

Dataset statistics

Number of variables11
Number of observations307
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory29.5 KiB
Average record size in memory98.4 B

Variable types

Text1
Numeric10

Dataset

Description부산광역시_시내버스,마을버스노선별이용건수_20201231
Author부산광역시
URLhttp://data.busan.go.kr/dataSet/detail.nm?contentId=10&publicdatapk=15095329

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
교통카드건수합계 has unique valuesUnique
건수(1통행)_어린이 has 5 (1.6%) zerosZeros
건수(2통행)_청소년 has 6 (2.0%) zerosZeros
건수(2통행)_어린이 has 12 (3.9%) zerosZeros
건수(3통행)_청소년 has 7 (2.3%) zerosZeros
건수(3통행)_어린이 has 23 (7.5%) zerosZeros

Reproduction

Analysis started2023-12-10 16:14:24.661632
Analysis finished2023-12-10 16:14:37.414946
Duration12.75 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

노선
Text

UNIQUE 

Distinct307
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size2.5 KiB
2023-12-11T01:14:37.781496image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length10
Median length8
Mean length3.980456
Min length1

Characters and Unicode

Total characters1222
Distinct characters76
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

Unique307 ?
Unique (%)100.0%

Sample

1st row1
2nd row10
3rd row100
4th row100-1
5th row1000
ValueCountFrequency (%)
1 1
 
0.3%
기장군2-3 1
 
0.3%
남구10 1
 
0.3%
남구1 1
 
0.3%
기장군8(정관)출 1
 
0.3%
기장군7(예림 1
 
0.3%
기장군7(병산 1
 
0.3%
기장군6 1
 
0.3%
기장군5(월평 1
 
0.3%
부산진구10 1
 
0.3%
Other values (297) 297
96.7%
2023-12-11T01:14:38.625362image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 188
 
15.4%
구 124
 
10.1%
2 76
 
6.2%
0 64
 
5.2%
3 59
 
4.8%
8 56
 
4.6%
- 55
 
4.5%
5 45
 
3.7%
6 37
 
3.0%
7 35
 
2.9%
Other values (66) 483
39.5%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 614
50.2%
Other Letter 524
42.9%
Dash Punctuation 55
 
4.5%
Open Punctuation 13
 
1.1%
Close Punctuation 13
 
1.1%
Uppercase Letter 3
 
0.2%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
구 124
23.7%
서 32
 
6.1%
기 28
 
5.3%
장 28
 
5.3%
사 26
 
5.0%
강 24
 
4.6%
산 18
 
3.4%
정 16
 
3.1%
하 15
 
2.9%
진 14
 
2.7%
Other values (51) 199
38.0%
Decimal Number
ValueCountFrequency (%)
1 188
30.6%
2 76
12.4%
0 64
 
10.4%
3 59
 
9.6%
8 56
 
9.1%
5 45
 
7.3%
6 37
 
6.0%
7 35
 
5.7%
9 33
 
5.4%
4 21
 
3.4%
Uppercase Letter
ValueCountFrequency (%)
A 2
66.7%
B 1
33.3%
Dash Punctuation
ValueCountFrequency (%)
- 55
100.0%
Open Punctuation
ValueCountFrequency (%)
( 13
100.0%
Close Punctuation
ValueCountFrequency (%)
) 13
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 695
56.9%
Hangul 524
42.9%
Latin 3
 
0.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
구 124
23.7%
서 32
 
6.1%
기 28
 
5.3%
장 28
 
5.3%
사 26
 
5.0%
강 24
 
4.6%
산 18
 
3.4%
정 16
 
3.1%
하 15
 
2.9%
진 14
 
2.7%
Other values (51) 199
38.0%
Common
ValueCountFrequency (%)
1 188
27.1%
2 76
10.9%
0 64
 
9.2%
3 59
 
8.5%
8 56
 
8.1%
- 55
 
7.9%
5 45
 
6.5%
6 37
 
5.3%
7 35
 
5.0%
9 33
 
4.7%
Other values (3) 47
 
6.8%
Latin
ValueCountFrequency (%)
A 2
66.7%
B 1
33.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 698
57.1%
Hangul 524
42.9%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 188
26.9%
2 76
10.9%
0 64
 
9.2%
3 59
 
8.5%
8 56
 
8.0%
- 55
 
7.9%
5 45
 
6.4%
6 37
 
5.3%
7 35
 
5.0%
9 33
 
4.7%
Other values (5) 50
 
7.2%
Hangul
ValueCountFrequency (%)
구 124
23.7%
서 32
 
6.1%
기 28
 
5.3%
장 28
 
5.3%
사 26
 
5.0%
강 24
 
4.6%
산 18
 
3.4%
정 16
 
3.1%
하 15
 
2.9%
진 14
 
2.7%
Other values (51) 199
38.0%

건수(1통행)_일반
Real number (ℝ)

HIGH CORRELATION 

Distinct306
Distinct (%)99.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean897490.91
Minimum1
Maximum4644982
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size2.8 KiB
2023-12-11T01:14:38.857437image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile4281.3
Q1121488.5
median392930
Q31389725
95-th percentile3093359.5
Maximum4644982
Range4644981
Interquartile range (IQR)1268236.5

Descriptive statistics

Standard deviation1062672.7
Coefficient of variation (CV)1.1840484
Kurtosis1.2521838
Mean897490.91
Median Absolute Deviation (MAD)357258
Skewness1.4218212
Sum2.7552971 × 108
Variance1.1292733 × 1012
MonotonicityNot monotonic
2023-12-11T01:14:39.044137image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
215 2
 
0.7%
374134 1
 
0.3%
95 1
 
0.3%
663054 1
 
0.3%
833867 1
 
0.3%
3486 1
 
0.3%
4352 1
 
0.3%
438 1
 
0.3%
100084 1
 
0.3%
11135 1
 
0.3%
Other values (296) 296
96.4%
ValueCountFrequency (%)
1 1
0.3%
2 1
0.3%
44 1
0.3%
95 1
0.3%
215 2
0.7%
438 1
0.3%
999 1
0.3%
1061 1
0.3%
2125 1
0.3%
2455 1
0.3%
ValueCountFrequency (%)
4644982 1
0.3%
4629059 1
0.3%
4340171 1
0.3%
4153917 1
0.3%
3854545 1
0.3%
3853988 1
0.3%
3829500 1
0.3%
3810006 1
0.3%
3741677 1
0.3%
3651867 1
0.3%

건수(1통행)_청소년
Real number (ℝ)

HIGH CORRELATION 

Distinct303
Distinct (%)98.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean62569.212
Minimum0
Maximum418294
Zeros3
Zeros (%)1.0%
Negative0
Negative (%)0.0%
Memory size2.8 KiB
2023-12-11T01:14:39.241597image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile257.5
Q15436
median27267
Q394126
95-th percentile232055.7
Maximum418294
Range418294
Interquartile range (IQR)88690

Descriptive statistics

Standard deviation78790.284
Coefficient of variation (CV)1.2592501
Kurtosis2.8450769
Mean62569.212
Median Absolute Deviation (MAD)26163
Skewness1.7262199
Sum19208748
Variance6.2079088 × 109
MonotonicityNot monotonic
2023-12-11T01:14:39.438115image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 3
 
1.0%
7282 2
 
0.7%
134 2
 
0.7%
20773 1
 
0.3%
7228 1
 
0.3%
153119 1
 
0.3%
91521 1
 
0.3%
92504 1
 
0.3%
719 1
 
0.3%
497 1
 
0.3%
Other values (293) 293
95.4%
ValueCountFrequency (%)
0 3
1.0%
1 1
 
0.3%
10 1
 
0.3%
13 1
 
0.3%
14 1
 
0.3%
51 1
 
0.3%
64 1
 
0.3%
65 1
 
0.3%
96 1
 
0.3%
104 1
 
0.3%
ValueCountFrequency (%)
418294 1
0.3%
334418 1
0.3%
334014 1
0.3%
333998 1
0.3%
321478 1
0.3%
309711 1
0.3%
306747 1
0.3%
296383 1
0.3%
286014 1
0.3%
281321 1
0.3%

건수(1통행)_어린이
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct299
Distinct (%)97.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean12145.524
Minimum0
Maximum82973
Zeros5
Zeros (%)1.6%
Negative0
Negative (%)0.0%
Memory size2.8 KiB
2023-12-11T01:14:39.639256image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile32.9
Q11478
median7400
Q317932
95-th percentile41596.7
Maximum82973
Range82973
Interquartile range (IQR)16454

Descriptive statistics

Standard deviation13809.447
Coefficient of variation (CV)1.1369989
Kurtosis2.9217559
Mean12145.524
Median Absolute Deviation (MAD)7058
Skewness1.6110688
Sum3728676
Variance1.9070084 × 108
MonotonicityNot monotonic
2023-12-11T01:14:39.794794image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 5
 
1.6%
108 2
 
0.7%
10 2
 
0.7%
32 2
 
0.7%
20127 2
 
0.7%
3569 1
 
0.3%
74 1
 
0.3%
17310 1
 
0.3%
6458 1
 
0.3%
13111 1
 
0.3%
Other values (289) 289
94.1%
ValueCountFrequency (%)
0 5
1.6%
1 1
 
0.3%
2 1
 
0.3%
5 1
 
0.3%
10 2
 
0.7%
13 1
 
0.3%
19 1
 
0.3%
25 1
 
0.3%
31 1
 
0.3%
32 2
 
0.7%
ValueCountFrequency (%)
82973 1
0.3%
57736 1
0.3%
54586 1
0.3%
54404 1
0.3%
53921 1
0.3%
53534 1
0.3%
53529 1
0.3%
51902 1
0.3%
48192 1
0.3%
46190 1
0.3%

건수(2통행)_일반
Real number (ℝ)

HIGH CORRELATION 

Distinct306
Distinct (%)99.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean258954.32
Minimum0
Maximum1436250
Zeros2
Zeros (%)0.7%
Negative0
Negative (%)0.0%
Memory size2.8 KiB
2023-12-11T01:14:39.963199image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile783.3
Q138087
median134491
Q3405730
95-th percentile879855.3
Maximum1436250
Range1436250
Interquartile range (IQR)367643

Descriptive statistics

Standard deviation302726.23
Coefficient of variation (CV)1.1690334
Kurtosis2.1981563
Mean258954.32
Median Absolute Deviation (MAD)116984
Skewness1.5814242
Sum79498975
Variance9.1643172 × 1010
MonotonicityNot monotonic
2023-12-11T01:14:40.184959image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 2
 
0.7%
116437 1
 
0.3%
13269 1
 
0.3%
253436 1
 
0.3%
155770 1
 
0.3%
277455 1
 
0.3%
344 1
 
0.3%
608 1
 
0.3%
277 1
 
0.3%
2738 1
 
0.3%
Other values (296) 296
96.4%
ValueCountFrequency (%)
0 2
0.7%
1 1
0.3%
24 1
0.3%
73 1
0.3%
75 1
0.3%
93 1
0.3%
266 1
0.3%
277 1
0.3%
289 1
0.3%
344 1
0.3%
ValueCountFrequency (%)
1436250 1
0.3%
1386961 1
0.3%
1346028 1
0.3%
1334874 1
0.3%
1248799 1
0.3%
1200994 1
0.3%
1155015 1
0.3%
1111541 1
0.3%
1066097 1
0.3%
1013347 1
0.3%

건수(2통행)_청소년
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct295
Distinct (%)96.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean11447.567
Minimum0
Maximum61030
Zeros6
Zeros (%)2.0%
Negative0
Negative (%)0.0%
Memory size2.8 KiB
2023-12-11T01:14:40.396781image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile14.3
Q11367.5
median5812
Q318625.5
95-th percentile37622.6
Maximum61030
Range61030
Interquartile range (IQR)17258

Descriptive statistics

Standard deviation12802.036
Coefficient of variation (CV)1.1183194
Kurtosis1.4289327
Mean11447.567
Median Absolute Deviation (MAD)5497
Skewness1.3690617
Sum3514403
Variance1.6389212 × 108
MonotonicityNot monotonic
2023-12-11T01:14:40.595470image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 6
 
2.0%
1 3
 
1.0%
12 2
 
0.7%
3156 2
 
0.7%
66 2
 
0.7%
53 2
 
0.7%
2 2
 
0.7%
7152 1
 
0.3%
17616 1
 
0.3%
23 1
 
0.3%
Other values (285) 285
92.8%
ValueCountFrequency (%)
0 6
2.0%
1 3
1.0%
2 2
 
0.7%
6 1
 
0.3%
9 1
 
0.3%
12 2
 
0.7%
14 1
 
0.3%
15 1
 
0.3%
20 1
 
0.3%
23 1
 
0.3%
ValueCountFrequency (%)
61030 1
0.3%
58819 1
0.3%
57675 1
0.3%
48799 1
0.3%
47625 1
0.3%
45909 1
0.3%
44675 1
0.3%
44091 1
0.3%
42667 1
0.3%
42180 1
0.3%

건수(2통행)_어린이
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct268
Distinct (%)87.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1058.4756
Minimum0
Maximum5559
Zeros12
Zeros (%)3.9%
Negative0
Negative (%)0.0%
Memory size2.8 KiB
2023-12-11T01:14:40.788635image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile1.3
Q1149.5
median618
Q31650
95-th percentile3809.9
Maximum5559
Range5559
Interquartile range (IQR)1500.5

Descriptive statistics

Standard deviation1172.9217
Coefficient of variation (CV)1.1081235
Kurtosis1.6915468
Mean1058.4756
Median Absolute Deviation (MAD)564
Skewness1.4443534
Sum324952
Variance1375745.3
MonotonicityNot monotonic
2023-12-11T01:14:40.977751image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 12
 
3.9%
2 6
 
2.0%
1 4
 
1.3%
3 3
 
1.0%
5 3
 
1.0%
227 3
 
1.0%
4 2
 
0.7%
268 2
 
0.7%
904 2
 
0.7%
49 2
 
0.7%
Other values (258) 268
87.3%
ValueCountFrequency (%)
0 12
3.9%
1 4
 
1.3%
2 6
2.0%
3 3
 
1.0%
4 2
 
0.7%
5 3
 
1.0%
7 1
 
0.3%
8 1
 
0.3%
12 1
 
0.3%
15 1
 
0.3%
ValueCountFrequency (%)
5559 1
0.3%
5267 1
0.3%
4770 1
0.3%
4696 1
0.3%
4580 1
0.3%
4384 1
0.3%
4346 1
0.3%
4305 1
0.3%
4176 1
0.3%
4175 1
0.3%

건수(3통행)_일반
Real number (ℝ)

HIGH CORRELATION 

Distinct303
Distinct (%)98.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean45039.524
Minimum0
Maximum199714
Zeros3
Zeros (%)1.0%
Negative0
Negative (%)0.0%
Memory size2.8 KiB
2023-12-11T01:14:41.136407image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile189.6
Q19807.5
median28632
Q371274.5
95-th percentile134525.4
Maximum199714
Range199714
Interquartile range (IQR)61467

Descriptive statistics

Standard deviation45220.23
Coefficient of variation (CV)1.0040122
Kurtosis0.705039
Mean45039.524
Median Absolute Deviation (MAD)23251
Skewness1.1880037
Sum13827134
Variance2.0448692 × 109
MonotonicityNot monotonic
2023-12-11T01:14:41.352503image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 3
 
1.0%
28632 2
 
0.7%
186 2
 
0.7%
18002 1
 
0.3%
54216 1
 
0.3%
31254 1
 
0.3%
54180 1
 
0.3%
107 1
 
0.3%
134 1
 
0.3%
18 1
 
0.3%
Other values (293) 293
95.4%
ValueCountFrequency (%)
0 3
1.0%
4 1
 
0.3%
15 1
 
0.3%
18 1
 
0.3%
19 1
 
0.3%
28 1
 
0.3%
77 1
 
0.3%
107 1
 
0.3%
112 1
 
0.3%
134 1
 
0.3%
ValueCountFrequency (%)
199714 1
0.3%
183363 1
0.3%
182602 1
0.3%
181466 1
0.3%
176030 1
0.3%
168077 1
0.3%
166118 1
0.3%
165428 1
0.3%
156662 1
0.3%
156628 1
0.3%

건수(3통행)_청소년
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct278
Distinct (%)90.6%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1335.0326
Minimum0
Maximum7975
Zeros7
Zeros (%)2.3%
Negative0
Negative (%)0.0%
Memory size2.8 KiB
2023-12-11T01:14:41.560222image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile4
Q1216
median823
Q32025.5
95-th percentile3851.6
Maximum7975
Range7975
Interquartile range (IQR)1809.5

Descriptive statistics

Standard deviation1435.4163
Coefficient of variation (CV)1.075192
Kurtosis3.446723
Mean1335.0326
Median Absolute Deviation (MAD)735
Skewness1.6551446
Sum409855
Variance2060419.9
MonotonicityNot monotonic
2023-12-11T01:14:42.045326image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 7
 
2.3%
4 4
 
1.3%
5 4
 
1.3%
59 4
 
1.3%
67 2
 
0.7%
2 2
 
0.7%
735 2
 
0.7%
500 2
 
0.7%
217 2
 
0.7%
229 2
 
0.7%
Other values (268) 276
89.9%
ValueCountFrequency (%)
0 7
2.3%
1 2
 
0.7%
2 2
 
0.7%
3 2
 
0.7%
4 4
1.3%
5 4
1.3%
7 1
 
0.3%
9 1
 
0.3%
10 1
 
0.3%
11 1
 
0.3%
ValueCountFrequency (%)
7975 1
0.3%
7831 1
0.3%
7169 1
0.3%
6577 1
0.3%
5833 1
0.3%
5549 1
0.3%
5366 1
0.3%
5263 1
0.3%
4573 1
0.3%
4339 1
0.3%

건수(3통행)_어린이
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct181
Distinct (%)59.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean112.09446
Minimum0
Maximum526
Zeros23
Zeros (%)7.5%
Negative0
Negative (%)0.0%
Memory size2.8 KiB
2023-12-11T01:14:42.294965image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q118
median77
Q3185
95-th percentile328.8
Maximum526
Range526
Interquartile range (IQR)167

Descriptive statistics

Standard deviation112.99624
Coefficient of variation (CV)1.0080448
Kurtosis1.1544703
Mean112.09446
Median Absolute Deviation (MAD)67
Skewness1.2132169
Sum34413
Variance12768.151
MonotonicityNot monotonic
2023-12-11T01:14:42.510791image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 23
 
7.5%
9 6
 
2.0%
3 6
 
2.0%
1 5
 
1.6%
13 5
 
1.6%
19 4
 
1.3%
2 4
 
1.3%
51 4
 
1.3%
15 4
 
1.3%
7 4
 
1.3%
Other values (171) 242
78.8%
ValueCountFrequency (%)
0 23
7.5%
1 5
 
1.6%
2 4
 
1.3%
3 6
 
2.0%
4 2
 
0.7%
5 3
 
1.0%
7 4
 
1.3%
8 2
 
0.7%
9 6
 
2.0%
10 3
 
1.0%
ValueCountFrequency (%)
526 1
0.3%
517 1
0.3%
498 1
0.3%
487 1
0.3%
472 1
0.3%
440 1
0.3%
427 1
0.3%
393 1
0.3%
357 1
0.3%
350 1
0.3%

교통카드건수합계
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct307
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1290152.7
Minimum1
Maximum6491475
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size2.8 KiB
2023-12-11T01:14:42.712454image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile5892.1
Q1195517.5
median623059
Q31994327.5
95-th percentile4373390.8
Maximum6491475
Range6491474
Interquartile range (IQR)1798810

Descriptive statistics

Standard deviation1502116.5
Coefficient of variation (CV)1.1642937
Kurtosis1.3061023
Mean1290152.7
Median Absolute Deviation (MAD)544120
Skewness1.4264072
Sum3.9607686 × 108
Variance2.2563541 × 1012
MonotonicityNot monotonic
2023-12-11T01:14:42.932982image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
536988 1
 
0.3%
17887 1
 
0.3%
1532088 1
 
0.3%
974219 1
 
0.3%
1314005 1
 
0.3%
4746 1
 
0.3%
5832 1
 
0.3%
752 1
 
0.3%
127096 1
 
0.3%
124 1
 
0.3%
Other values (297) 297
96.7%
ValueCountFrequency (%)
1 1
0.3%
2 1
0.3%
45 1
0.3%
124 1
0.3%
314 1
0.3%
328 1
0.3%
752 1
0.3%
1229 1
0.3%
1491 1
0.3%
2612 1
0.3%
ValueCountFrequency (%)
6491475 1
0.3%
6482016 1
0.3%
6236166 1
0.3%
5929082 1
0.3%
5802246 1
0.3%
5614442 1
0.3%
5426389 1
0.3%
5404469 1
0.3%
5169615 1
0.3%
5161817 1
0.3%

Interactions

2023-12-11T01:14:35.728432image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T01:14:25.183520image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T01:14:26.435390image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T01:14:27.782043image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T01:14:28.971961image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T01:14:30.327015image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T01:14:31.184421image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T01:14:32.081969image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T01:14:33.180670image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T01:14:34.398485image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T01:14:35.830903image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T01:14:25.309276image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T01:14:26.545739image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T01:14:27.914768image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T01:14:29.072428image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T01:14:30.400423image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T01:14:31.256332image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T01:14:32.192348image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T01:14:33.280061image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T01:14:34.487873image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T01:14:35.945585image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T01:14:25.415481image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T01:14:26.669850image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T01:14:28.052312image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T01:14:29.465709image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T01:14:30.473196image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T01:14:31.330764image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T01:14:32.300972image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T01:14:33.383929image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T01:14:34.575576image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T01:14:36.050641image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T01:14:25.535177image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T01:14:26.796415image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T01:14:28.170264image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T01:14:29.595306image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T01:14:30.577071image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T01:14:31.402761image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T01:14:32.406712image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T01:14:33.492892image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T01:14:34.658370image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T01:14:36.205272image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T01:14:25.671119image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T01:14:26.938071image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T01:14:28.328557image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T01:14:29.730433image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T01:14:30.677866image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T01:14:31.492376image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T01:14:32.536751image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T01:14:33.659525image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T01:14:34.759509image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T01:14:36.328772image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T01:14:25.804641image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T01:14:27.086314image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T01:14:28.461282image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T01:14:29.837784image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T01:14:30.762957image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T01:14:31.579284image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T01:14:32.658260image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T01:14:33.785641image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T01:14:34.851876image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T01:14:36.461812image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T01:14:25.931226image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T01:14:27.219572image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T01:14:28.555559image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T01:14:29.923742image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T01:14:30.843973image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T01:14:31.664312image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T01:14:32.771618image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T01:14:33.908344image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T01:14:34.949854image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T01:14:36.582217image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T01:14:26.075257image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T01:14:27.371902image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T01:14:28.671230image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T01:14:30.017939image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T01:14:30.931261image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T01:14:31.758477image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T01:14:32.871444image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T01:14:34.036733image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T01:14:35.371171image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T01:14:36.730556image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T01:14:26.214793image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T01:14:27.521471image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T01:14:28.773949image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T01:14:30.151976image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T01:14:31.019803image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T01:14:31.862315image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T01:14:32.987912image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T01:14:34.167748image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T01:14:35.503592image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T01:14:36.960283image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T01:14:26.329557image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T01:14:27.648550image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T01:14:28.865847image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T01:14:30.238803image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T01:14:31.097333image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T01:14:31.970256image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T01:14:33.084286image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T01:14:34.284033image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T01:14:35.617725image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-11T01:14:43.077622image/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)_일반1.0000.7960.7830.9520.7870.9180.9250.8100.9010.995
건수(1통행)_청소년0.7961.0000.8500.7330.9000.8010.7170.7360.8120.789
건수(1통행)_어린이0.7830.8501.0000.7540.7360.8190.7370.7190.8310.799
건수(2통행)_일반0.9520.7330.7541.0000.8000.9080.9480.8560.9050.967
건수(2통행)_청소년0.7870.9000.7360.8001.0000.8070.8270.7990.8180.825
건수(2통행)_어린이0.9180.8010.8190.9080.8071.0000.9210.8640.9250.923
건수(3통행)_일반0.9250.7170.7370.9480.8270.9211.0000.8690.9320.931
건수(3통행)_청소년0.8100.7360.7190.8560.7990.8640.8691.0000.8850.827
건수(3통행)_어린이0.9010.8120.8310.9050.8180.9250.9320.8851.0000.916
교통카드건수합계0.9950.7890.7990.9670.8250.9230.9310.8270.9161.000
2023-12-11T01:14:43.290858image/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)_일반1.0000.9620.9250.9800.9300.9430.9490.8670.9350.997
건수(1통행)_청소년0.9621.0000.9410.9360.9400.9280.9070.8880.9160.962
건수(1통행)_어린이0.9250.9411.0000.8990.8960.9510.8900.8400.9280.924
건수(2통행)_일반0.9800.9360.8991.0000.9570.9510.9770.9030.9400.990
건수(2통행)_청소년0.9300.9400.8960.9571.0000.9470.9400.9590.9210.946
건수(2통행)_어린이0.9430.9280.9510.9510.9471.0000.9370.8870.9640.950
건수(3통행)_일반0.9490.9070.8900.9770.9400.9371.0000.9270.9480.965
건수(3통행)_청소년0.8670.8880.8400.9030.9590.8870.9271.0000.8920.890
건수(3통행)_어린이0.9350.9160.9280.9400.9210.9640.9480.8921.0000.942
교통카드건수합계0.9970.9620.9240.9900.9460.9500.9650.8900.9421.000

Missing values

2023-12-11T01:14:37.137096image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-11T01:14:37.330430image/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
0137413420773314511643737443981800230946536988
1101932743212792305835422683258929399743738842492855484
210010211875789185102219117322592399598761161358364
3100-1144923199949141633587351425213966050616681872000087
4100051897915831313213327735304371505334535690619
510011838932712407487525115197251150398651317902504921
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노선건수(1통행)_일반건수(1통행)_청소년건수(1통행)_어린이건수(2통행)_일반건수(2통행)_청소년건수(2통행)_어린이건수(3통행)_일반건수(3통행)_청소년건수(3통행)_어린이교통카드건수합계
297하버트란스3719643897311243005039
298해운대10141543377215483728710179798051729195250
299해운대243986312609497311203129582842863271340602103
300해운대3B코21514275101920328
301해운대구3214161846254526840631563342225652950322806
302해운대구3-1426149333651387514153990405413836581939663732
303해운대구3-2162428216424895527842564221138841319258558
304해운대구7106950830720112584091811952272109149591
305해운대구843759132143811955315353687621561587
306해운대구97880729047231790339466448211719105415