Overview

Dataset statistics

Number of variables4
Number of observations51
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory1.8 KiB
Average record size in memory36.6 B

Variable types

Categorical1
Text1
Numeric2

Dataset

Description시군별로 버스운행정보 서비스를 제공하기 위해 정류장에 설치된 버스정보안내기 수량과 버스에 설치하는 버스통합단말기 현황 정보
URLhttps://www.data.go.kr/data/15089732/fileData.do

Alerts

지자체 has unique valuesUnique
버스통합단말기 has 2 (3.9%) zerosZeros

Reproduction

Analysis started2023-12-12 15:59:02.570799
Analysis finished2023-12-12 15:59:03.321811
Duration0.75 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

광역
Categorical

Distinct7
Distinct (%)13.7%
Missing0
Missing (%)0.0%
Memory size540.0 B
경상남도
11 
경상북도
11 
전라북도
10 
전라남도
8 
충청북도
5 
Other values (2)
6 

Length

Max length4
Median length4
Mean length3.9411765
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row강원도
2nd row강원도
3rd row강원도
4th row충청남도
5th row충청남도

Common Values

ValueCountFrequency (%)
경상남도 11
21.6%
경상북도 11
21.6%
전라북도 10
19.6%
전라남도 8
15.7%
충청북도 5
9.8%
강원도 3
 
5.9%
충청남도 3
 
5.9%

Length

2023-12-13T00:59:03.389295image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T00:59:03.507194image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
경상남도 11
21.6%
경상북도 11
21.6%
전라북도 10
19.6%
전라남도 8
15.7%
충청북도 5
9.8%
강원도 3
 
5.9%
충청남도 3
 
5.9%

지자체
Text

UNIQUE 

Distinct51
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size540.0 B
2023-12-13T00:59:03.766411image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length3
Median length3
Mean length3
Min length3

Characters and Unicode

Total characters153
Distinct characters59
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique51 ?
Unique (%)100.0%

Sample

1st row양양군
2nd row태백시
3rd row홍천군
4th row논산시
5th row부여군
ValueCountFrequency (%)
양양군 1
 
2.0%
장흥군 1
 
2.0%
해남군 1
 
2.0%
거창군 1
 
2.0%
고성군 1
 
2.0%
남해군 1
 
2.0%
산청군 1
 
2.0%
의령군 1
 
2.0%
창녕군 1
 
2.0%
하동군 1
 
2.0%
Other values (41) 41
80.4%
2023-12-13T00:59:04.179781image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
군 42
27.5%
시 10
 
6.5%
진 5
 
3.3%
성 5
 
3.3%
양 4
 
2.6%
창 4
 
2.6%
고 4
 
2.6%
산 4
 
2.6%
안 4
 
2.6%
주 4
 
2.6%
Other values (49) 67
43.8%

Most occurring categories

ValueCountFrequency (%)
Other Letter 153
100.0%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
군 42
27.5%
시 10
 
6.5%
진 5
 
3.3%
성 5
 
3.3%
양 4
 
2.6%
창 4
 
2.6%
고 4
 
2.6%
산 4
 
2.6%
안 4
 
2.6%
주 4
 
2.6%
Other values (49) 67
43.8%

Most occurring scripts

ValueCountFrequency (%)
Hangul 153
100.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
군 42
27.5%
시 10
 
6.5%
진 5
 
3.3%
성 5
 
3.3%
양 4
 
2.6%
창 4
 
2.6%
고 4
 
2.6%
산 4
 
2.6%
안 4
 
2.6%
주 4
 
2.6%
Other values (49) 67
43.8%

Most occurring blocks

ValueCountFrequency (%)
Hangul 153
100.0%

Most frequent character per block

Hangul
ValueCountFrequency (%)
군 42
27.5%
시 10
 
6.5%
진 5
 
3.3%
성 5
 
3.3%
양 4
 
2.6%
창 4
 
2.6%
고 4
 
2.6%
산 4
 
2.6%
안 4
 
2.6%
주 4
 
2.6%
Other values (49) 67
43.8%

버스정보안내기
Real number (ℝ)

Distinct33
Distinct (%)64.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean33.647059
Minimum3
Maximum260
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size591.0 B
2023-12-13T00:59:04.324106image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum3
5-th percentile6.5
Q114
median21
Q333.5
95-th percentile110
Maximum260
Range257
Interquartile range (IQR)19.5

Descriptive statistics

Standard deviation43.05105
Coefficient of variation (CV)1.2794893
Kurtosis15.967285
Mean33.647059
Median Absolute Deviation (MAD)8
Skewness3.6747483
Sum1716
Variance1853.3929
MonotonicityNot monotonic
2023-12-13T00:59:04.444977image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=33)
ValueCountFrequency (%)
14 5
 
9.8%
16 5
 
9.8%
13 4
 
7.8%
10 2
 
3.9%
25 2
 
3.9%
22 2
 
3.9%
32 2
 
3.9%
11 2
 
3.9%
34 2
 
3.9%
23 2
 
3.9%
Other values (23) 23
45.1%
ValueCountFrequency (%)
3 1
 
2.0%
4 1
 
2.0%
6 1
 
2.0%
7 1
 
2.0%
10 2
 
3.9%
11 2
 
3.9%
13 4
7.8%
14 5
9.8%
16 5
9.8%
17 1
 
2.0%
ValueCountFrequency (%)
260 1
2.0%
153 1
2.0%
124 1
2.0%
96 1
2.0%
66 1
2.0%
59 1
2.0%
58 1
2.0%
53 1
2.0%
46 1
2.0%
40 1
2.0%

버스통합단말기
Real number (ℝ)

ZEROS 

Distinct36
Distinct (%)70.6%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean32.254902
Minimum0
Maximum164
Zeros2
Zeros (%)3.9%
Negative0
Negative (%)0.0%
Memory size591.0 B
2023-12-13T00:59:04.571470image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile10
Q117.5
median24
Q339
95-th percentile67
Maximum164
Range164
Interquartile range (IQR)21.5

Descriptive statistics

Standard deviation27.158677
Coefficient of variation (CV)0.84200153
Kurtosis11.588926
Mean32.254902
Median Absolute Deviation (MAD)11
Skewness2.9328764
Sum1645
Variance737.59373
MonotonicityNot monotonic
2023-12-13T00:59:04.692293image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=36)
ValueCountFrequency (%)
23 5
 
9.8%
11 4
 
7.8%
24 3
 
5.9%
17 2
 
3.9%
33 2
 
3.9%
40 2
 
3.9%
26 2
 
3.9%
0 2
 
3.9%
38 2
 
3.9%
28 1
 
2.0%
Other values (26) 26
51.0%
ValueCountFrequency (%)
0 2
3.9%
9 1
 
2.0%
11 4
7.8%
12 1
 
2.0%
13 1
 
2.0%
14 1
 
2.0%
16 1
 
2.0%
17 2
3.9%
18 1
 
2.0%
19 1
 
2.0%
ValueCountFrequency (%)
164 1
2.0%
115 1
2.0%
72 1
2.0%
62 1
2.0%
60 1
2.0%
53 1
2.0%
52 1
2.0%
49 1
2.0%
44 1
2.0%
42 1
2.0%

Interactions

2023-12-13T00:59:02.950524image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T00:59:02.730926image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T00:59:03.055805image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T00:59:02.833282image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-13T00:59:04.772836image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
광역지자체버스정보안내기버스통합단말기
광역1.0001.0000.5530.349
지자체1.0001.0001.0001.000
버스정보안내기0.5531.0001.0000.964
버스통합단말기0.3491.0000.9641.000
2023-12-13T00:59:04.860277image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
버스정보안내기버스통합단말기광역
버스정보안내기1.0000.4150.214
버스통합단말기0.4151.0000.117
광역0.2140.1171.000

Missing values

2023-12-13T00:59:03.179334image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-13T00:59:03.277667image/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

광역지자체버스정보안내기버스통합단말기
0강원도양양군3417
1강원도태백시1824
2강원도홍천군338
3충청남도논산시26060
4충청남도부여군4042
5충청남도당진시9672
6충청북도단양군2321
7충청북도음성군5330
8충청북도진천군1023
9충청북도영동군726
광역지자체버스정보안내기버스통합단말기
41경상북도고령군1424
42경상북도군위군1311
43경상북도문경시1440
44경상북도봉화군2217
45경상북도청도군1723
46경상북도의성군4626
47경상북도성주군2752
48경상북도상주시2544
49경상북도영주시5962
50경상북도울진군1423