Overview

Dataset statistics

Number of variables3
Number of observations43
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory1.2 KiB
Average record size in memory28.1 B

Variable types

Categorical1
Text1
Numeric1

Dataset

Description대구교통공사의 2023년 10월 31일 기준 운수영업, 열차운행, 시설이용, 일반현황, 기타 등 분야별 고객의 소리 등록 현황에 대한 자료입니다.
Author대구교통공사
URLhttps://www.data.go.kr/data/15060929/fileData.do

Alerts

등록 has 2 (4.7%) zerosZeros

Reproduction

Analysis started2023-12-12 10:03:57.209976
Analysis finished2023-12-12 10:03:57.540882
Duration0.33 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

분야
Categorical

Distinct5
Distinct (%)11.6%
Missing0
Missing (%)0.0%
Memory size476.0 B
운수영업
13 
시설이용
11 
열차운행
10 
일반현황
8 
기타
 
1

Length

Max length4
Median length4
Mean length3.9534884
Min length2

Unique

Unique1 ?
Unique (%)2.3%

Sample

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

Common Values

ValueCountFrequency (%)
운수영업 13
30.2%
시설이용 11
25.6%
열차운행 10
23.3%
일반현황 8
18.6%
기타 1
 
2.3%

Length

2023-12-12T19:03:57.609755image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T19:03:57.755681image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
운수영업 13
30.2%
시설이용 11
25.6%
열차운행 10
23.3%
일반현황 8
18.6%
기타 1
 
2.3%

상세분야
Text

Distinct39
Distinct (%)90.7%
Missing0
Missing (%)0.0%
Memory size476.0 B
2023-12-12T19:03:57.968236image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length7
Median length6
Mean length3.744186
Min length2

Characters and Unicode

Total characters161
Distinct characters84
Distinct categories4 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique38 ?
Unique (%)88.4%

Sample

1st row운임제도
2nd row이용질서
3rd row승차권
4th row친절
5th row불친절
ValueCountFrequency (%)
기타 5
 
11.4%
부정승차 1
 
2.3%
afc기기 1
 
2.3%
열차사고/지연 1
 
2.3%
편의시설 1
 
2.3%
장애인시설물 1
 
2.3%
안내제표 1
 
2.3%
승강설비 1
 
2.3%
역사환경 1
 
2.3%
화장실 1
 
2.3%
Other values (30) 30
68.2%
2023-12-12T19:03:58.387836image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
안 9
 
5.6%
기 8
 
5.0%
타 6
 
3.7%
사 6
 
3.7%
차 6
 
3.7%
내 6
 
3.7%
전 5
 
3.1%
설 4
 
2.5%
/ 3
 
1.9%
시 3
 
1.9%
Other values (74) 105
65.2%

Most occurring categories

ValueCountFrequency (%)
Other Letter 154
95.7%
Other Punctuation 3
 
1.9%
Uppercase Letter 3
 
1.9%
Space Separator 1
 
0.6%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
안 9
 
5.8%
기 8
 
5.2%
타 6
 
3.9%
사 6
 
3.9%
차 6
 
3.9%
내 6
 
3.9%
전 5
 
3.2%
설 4
 
2.6%
시 3
 
1.9%
고 3
 
1.9%
Other values (69) 98
63.6%
Uppercase Letter
ValueCountFrequency (%)
A 1
33.3%
F 1
33.3%
C 1
33.3%
Other Punctuation
ValueCountFrequency (%)
/ 3
100.0%
Space Separator
ValueCountFrequency (%)
1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 154
95.7%
Common 4
 
2.5%
Latin 3
 
1.9%

Most frequent character per script

Hangul
ValueCountFrequency (%)
안 9
 
5.8%
기 8
 
5.2%
타 6
 
3.9%
사 6
 
3.9%
차 6
 
3.9%
내 6
 
3.9%
전 5
 
3.2%
설 4
 
2.6%
시 3
 
1.9%
고 3
 
1.9%
Other values (69) 98
63.6%
Latin
ValueCountFrequency (%)
A 1
33.3%
F 1
33.3%
C 1
33.3%
Common
ValueCountFrequency (%)
/ 3
75.0%
1
 
25.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 154
95.7%
ASCII 7
 
4.3%

Most frequent character per block

Hangul
ValueCountFrequency (%)
안 9
 
5.8%
기 8
 
5.2%
타 6
 
3.9%
사 6
 
3.9%
차 6
 
3.9%
내 6
 
3.9%
전 5
 
3.2%
설 4
 
2.6%
시 3
 
1.9%
고 3
 
1.9%
Other values (69) 98
63.6%
ASCII
ValueCountFrequency (%)
/ 3
42.9%
1
 
14.3%
A 1
 
14.3%
F 1
 
14.3%
C 1
 
14.3%

등록
Real number (ℝ)

ZEROS 

Distinct28
Distinct (%)65.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean26.372093
Minimum0
Maximum214
Zeros2
Zeros (%)4.7%
Negative0
Negative (%)0.0%
Memory size519.0 B
2023-12-12T19:03:58.551726image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile1.1
Q16
median11
Q334.5
95-th percentile75.7
Maximum214
Range214
Interquartile range (IQR)28.5

Descriptive statistics

Standard deviation39.993466
Coefficient of variation (CV)1.5165071
Kurtosis12.763072
Mean26.372093
Median Absolute Deviation (MAD)9
Skewness3.322882
Sum1134
Variance1599.4773
MonotonicityNot monotonic
2023-12-12T19:03:58.709573image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=28)
ValueCountFrequency (%)
6 5
 
11.6%
7 4
 
9.3%
3 4
 
9.3%
4 2
 
4.7%
0 2
 
4.7%
35 2
 
4.7%
11 2
 
4.7%
24 2
 
4.7%
9 1
 
2.3%
25 1
 
2.3%
Other values (18) 18
41.9%
ValueCountFrequency (%)
0 2
 
4.7%
1 1
 
2.3%
2 1
 
2.3%
3 4
9.3%
4 2
 
4.7%
6 5
11.6%
7 4
9.3%
9 1
 
2.3%
11 2
 
4.7%
12 1
 
2.3%
ValueCountFrequency (%)
214 1
2.3%
150 1
2.3%
76 1
2.3%
73 1
2.3%
49 1
2.3%
43 1
2.3%
40 1
2.3%
39 1
2.3%
37 1
2.3%
35 2
4.7%

Interactions

2023-12-12T19:03:57.335896image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-12T19:03:58.823530image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
분야상세분야등록
분야1.0000.0000.630
상세분야0.0001.0000.000
등록0.6300.0001.000
2023-12-12T19:03:58.925941image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
등록분야
등록1.0000.481
분야0.4811.000

Missing values

2023-12-12T19:03:57.439679image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-12T19:03:57.514057image/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

분야상세분야등록
0운수영업운임제도29
1운수영업이용질서34
2운수영업승차권4
3운수영업친절76
4운수영업불친절2
5운수영업행선지안내7
6운수영업유실물150
7운수영업이용안내35
8운수영업부정승차7
9운수영업임대사업1
분야상세분야등록
33시설이용기타24
34일반현황홈페이지6
35일반현황홍보0
36일반현황인력채용11
37일반현황견학7
38일반현황부서/직원안내0
39일반현황자료요청3
40일반현황타기관12
41일반현황기타7
42기타기타214