Overview

Dataset statistics

Number of variables5
Number of observations1022
Missing cells0
Missing cells (%)0.0%
Duplicate rows70
Duplicate rows (%)6.8%
Total size in memory41.0 KiB
Average record size in memory41.1 B

Variable types

Text3
Numeric1
Categorical1

Dataset

Description충청북도 제천시 시내버스정류장현황- 충청북도 제천시 시내버스 정류장의 정거장명, 지번주소, 위도, 경도 등의 항목을 제공합니다.
Author충청북도 제천시
URLhttps://www.data.go.kr/data/15059658/fileData.do

Alerts

데이터기준일자 has constant value ""Constant
Dataset has 70 (6.8%) duplicate rowsDuplicates

Reproduction

Analysis started2024-05-04 07:36:19.575159
Analysis finished2024-05-04 07:36:21.508932
Duration1.93 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

정거장명
Text

Distinct685
Distinct (%)67.0%
Missing0
Missing (%)0.0%
Memory size8.1 KiB
2024-05-04T07:36:21.941525image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length22
Median length20
Mean length6.1516634
Min length2

Characters and Unicode

Total characters6287
Distinct characters347
Distinct categories7 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique544 ?
Unique (%)53.2%

Sample

1st row공전3리입구
2nd row구곡3리경로당앞
3rd row구곡3리 굴탄대교앞
4th row구곡리
5th row구곡리
ValueCountFrequency (%)
앞 58
 
4.2%
장락동 30
 
2.2%
입구 25
 
1.8%
아파트 19
 
1.4%
무도리 16
 
1.2%
시곡리 15
 
1.1%
구룡리 12
 
0.9%
방향 12
 
0.9%
도화리 12
 
0.9%
월림리 12
 
0.9%
Other values (717) 1170
84.7%
2024-05-04T07:36:23.257813image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
리 497
 
7.9%
375
 
6.0%
동 212
 
3.4%
) 203
 
3.2%
( 203
 
3.2%
구 121
 
1.9%
앞 116
 
1.8%
장 101
 
1.6%
곡 85
 
1.4%
입 83
 
1.3%
Other values (337) 4291
68.3%

Most occurring categories

ValueCountFrequency (%)
Other Letter 5344
85.0%
Space Separator 375
 
6.0%
Close Punctuation 203
 
3.2%
Open Punctuation 203
 
3.2%
Decimal Number 149
 
2.4%
Other Punctuation 11
 
0.2%
Uppercase Letter 2
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
리 497
 
9.3%
동 212
 
4.0%
구 121
 
2.3%
앞 116
 
2.2%
장 101
 
1.9%
곡 85
 
1.6%
입 83
 
1.6%
아 81
 
1.5%
산 80
 
1.5%
전 74
 
1.4%
Other values (321) 3894
72.9%
Decimal Number
ValueCountFrequency (%)
1 54
36.2%
2 44
29.5%
3 26
17.4%
4 12
 
8.1%
5 4
 
2.7%
8 4
 
2.7%
0 2
 
1.3%
7 2
 
1.3%
9 1
 
0.7%
Other Punctuation
ValueCountFrequency (%)
. 7
63.6%
, 4
36.4%
Uppercase Letter
ValueCountFrequency (%)
U 1
50.0%
C 1
50.0%
Space Separator
ValueCountFrequency (%)
375
100.0%
Close Punctuation
ValueCountFrequency (%)
) 203
100.0%
Open Punctuation
ValueCountFrequency (%)
( 203
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 5344
85.0%
Common 941
 
15.0%
Latin 2
 
< 0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
리 497
 
9.3%
동 212
 
4.0%
구 121
 
2.3%
앞 116
 
2.2%
장 101
 
1.9%
곡 85
 
1.6%
입 83
 
1.6%
아 81
 
1.5%
산 80
 
1.5%
전 74
 
1.4%
Other values (321) 3894
72.9%
Common
ValueCountFrequency (%)
375
39.9%
) 203
21.6%
( 203
21.6%
1 54
 
5.7%
2 44
 
4.7%
3 26
 
2.8%
4 12
 
1.3%
. 7
 
0.7%
5 4
 
0.4%
, 4
 
0.4%
Other values (4) 9
 
1.0%
Latin
ValueCountFrequency (%)
U 1
50.0%
C 1
50.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 5344
85.0%
ASCII 943
 
15.0%

Most frequent character per block

Hangul
ValueCountFrequency (%)
리 497
 
9.3%
동 212
 
4.0%
구 121
 
2.3%
앞 116
 
2.2%
장 101
 
1.9%
곡 85
 
1.6%
입 83
 
1.6%
아 81
 
1.5%
산 80
 
1.5%
전 74
 
1.4%
Other values (321) 3894
72.9%
ASCII
ValueCountFrequency (%)
375
39.8%
) 203
21.5%
( 203
21.5%
1 54
 
5.7%
2 44
 
4.7%
3 26
 
2.8%
4 12
 
1.3%
. 7
 
0.7%
5 4
 
0.4%
, 4
 
0.4%
Other values (6) 11
 
1.2%

지번주소
Text

Distinct880
Distinct (%)86.1%
Missing0
Missing (%)0.0%
Memory size8.1 KiB
2024-05-04T07:36:24.100359image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length25
Median length23
Mean length19.944227
Min length9

Characters and Unicode

Total characters20383
Distinct characters133
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique751 ?
Unique (%)73.5%

Sample

1st row충청북도 제천시 봉양읍 공전리 82-1
2nd row충청북도 제천시 봉양읍 구곡리 1095-1
3rd row충청북도 제천시 봉양읍 구곡리 1397-3
4th row충청북도 제천시 봉양읍 구곡리 162-2
5th row충청북도 제천시 봉양읍 구곡리 162-2
ValueCountFrequency (%)
충청북도 1020
22.0%
제천시 1019
22.0%
봉양읍 182
 
3.9%
송학면 96
 
2.1%
금성면 75
 
1.6%
백운면 73
 
1.6%
청풍면 70
 
1.5%
수산면 60
 
1.3%
장락동 36
 
0.8%
덕산면 34
 
0.7%
Other values (978) 1966
42.5%
2024-05-04T07:36:25.460227image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
3625
17.8%
청 1111
 
5.5%
도 1098
 
5.4%
천 1061
 
5.2%
제 1052
 
5.2%
시 1039
 
5.1%
북 1021
 
5.0%
충 1020
 
5.0%
1 764
 
3.7%
- 745
 
3.7%
Other values (123) 7847
38.5%

Most occurring categories

ValueCountFrequency (%)
Other Letter 12058
59.2%
Decimal Number 3955
 
19.4%
Space Separator 3625
 
17.8%
Dash Punctuation 745
 
3.7%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
청 1111
 
9.2%
도 1098
 
9.1%
천 1061
 
8.8%
제 1052
 
8.7%
시 1039
 
8.6%
북 1021
 
8.5%
충 1020
 
8.5%
리 617
 
5.1%
면 430
 
3.6%
동 374
 
3.1%
Other values (111) 3235
26.8%
Decimal Number
ValueCountFrequency (%)
1 764
19.3%
2 541
13.7%
3 436
11.0%
5 395
10.0%
4 389
9.8%
6 327
8.3%
8 289
 
7.3%
0 288
 
7.3%
7 275
 
7.0%
9 251
 
6.3%
Space Separator
ValueCountFrequency (%)
3625
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 745
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 12058
59.2%
Common 8325
40.8%

Most frequent character per script

Hangul
ValueCountFrequency (%)
청 1111
 
9.2%
도 1098
 
9.1%
천 1061
 
8.8%
제 1052
 
8.7%
시 1039
 
8.6%
북 1021
 
8.5%
충 1020
 
8.5%
리 617
 
5.1%
면 430
 
3.6%
동 374
 
3.1%
Other values (111) 3235
26.8%
Common
ValueCountFrequency (%)
3625
43.5%
1 764
 
9.2%
- 745
 
8.9%
2 541
 
6.5%
3 436
 
5.2%
5 395
 
4.7%
4 389
 
4.7%
6 327
 
3.9%
8 289
 
3.5%
0 288
 
3.5%
Other values (2) 526
 
6.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 12058
59.2%
ASCII 8325
40.8%

Most frequent character per block

ASCII
ValueCountFrequency (%)
3625
43.5%
1 764
 
9.2%
- 745
 
8.9%
2 541
 
6.5%
3 436
 
5.2%
5 395
 
4.7%
4 389
 
4.7%
6 327
 
3.9%
8 289
 
3.5%
0 288
 
3.5%
Other values (2) 526
 
6.3%
Hangul
ValueCountFrequency (%)
청 1111
 
9.2%
도 1098
 
9.1%
천 1061
 
8.8%
제 1052
 
8.7%
시 1039
 
8.6%
북 1021
 
8.5%
충 1020
 
8.5%
리 617
 
5.1%
면 430
 
3.6%
동 374
 
3.1%
Other values (111) 3235
26.8%

위도
Text

Distinct874
Distinct (%)85.5%
Missing0
Missing (%)0.0%
Memory size8.1 KiB
2024-05-04T07:36:26.524839image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length9
Median length9
Mean length8.7573386
Min length6

Characters and Unicode

Total characters8950
Distinct characters12
Distinct categories3 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique746 ?
Unique (%)73.0%

Sample

1st row37.106137
2nd row37.092249
3rd row37.094171
4th row37.100523
5th row37.100523
ValueCountFrequency (%)
37.127834 5
 
0.5%
37.173841 4
 
0.4%
36.934858 4
 
0.4%
36.999043 4
 
0.4%
36.914524 3
 
0.3%
37.146005 3
 
0.3%
37.084395 3
 
0.3%
37.121046 3
 
0.3%
37.099246 3
 
0.3%
37.053863 3
 
0.3%
Other values (864) 987
96.6%
2024-05-04T07:36:28.122770image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
3 1571
17.6%
7 1368
15.3%
1 1145
12.8%
. 1021
11.4%
2 604
 
6.7%
6 590
 
6.6%
9 578
 
6.5%
4 557
 
6.2%
0 513
 
5.7%
5 503
 
5.6%
Other values (2) 500
 
5.6%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 7928
88.6%
Other Punctuation 1021
 
11.4%
Dash Punctuation 1
 
< 0.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
3 1571
19.8%
7 1368
17.3%
1 1145
14.4%
2 604
 
7.6%
6 590
 
7.4%
9 578
 
7.3%
4 557
 
7.0%
0 513
 
6.5%
5 503
 
6.3%
8 499
 
6.3%
Other Punctuation
ValueCountFrequency (%)
. 1021
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 8950
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
3 1571
17.6%
7 1368
15.3%
1 1145
12.8%
. 1021
11.4%
2 604
 
6.7%
6 590
 
6.6%
9 578
 
6.5%
4 557
 
6.2%
0 513
 
5.7%
5 503
 
5.6%
Other values (2) 500
 
5.6%

Most occurring blocks

ValueCountFrequency (%)
ASCII 8950
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
3 1571
17.6%
7 1368
15.3%
1 1145
12.8%
. 1021
11.4%
2 604
 
6.7%
6 590
 
6.6%
9 578
 
6.5%
4 557
 
6.2%
0 513
 
5.7%
5 503
 
5.6%
Other values (2) 500
 
5.6%

경도
Real number (ℝ)

Distinct877
Distinct (%)85.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean128.17255
Minimum127.9526
Maximum128.32484
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size9.1 KiB
2024-05-04T07:36:28.766619image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum127.9526
5-th percentile128.01794
Q1128.12761
median128.1943
Q3128.21919
95-th percentile128.2631
Maximum128.32484
Range0.372243
Interquartile range (IQR)0.09158175

Descriptive statistics

Standard deviation0.069807359
Coefficient of variation (CV)0.00054463581
Kurtosis0.59801435
Mean128.17255
Median Absolute Deviation (MAD)0.0349935
Skewness-0.83001924
Sum130992.34
Variance0.0048730673
MonotonicityNot monotonic
2024-05-04T07:36:29.342121image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
128.213863 5
 
0.5%
128.177217 4
 
0.4%
128.168086 4
 
0.4%
128.196156 4
 
0.4%
128.199777 3
 
0.3%
128.102712 3
 
0.3%
128.247881 3
 
0.3%
128.160461 3
 
0.3%
128.102532 3
 
0.3%
128.177631 3
 
0.3%
Other values (867) 987
96.6%
ValueCountFrequency (%)
127.952598 1
0.1%
127.954355 2
0.2%
127.960707 2
0.2%
127.960912 1
0.1%
127.97109 2
0.2%
127.97216 1
0.1%
127.979134 1
0.1%
127.979179 1
0.1%
127.980741 1
0.1%
127.98322 1
0.1%
ValueCountFrequency (%)
128.324841 1
0.1%
128.322224 1
0.1%
128.319216 1
0.1%
128.318147 1
0.1%
128.316062 1
0.1%
128.315408 1
0.1%
128.310762 2
0.2%
128.309295 1
0.1%
128.301371 1
0.1%
128.300906 1
0.1%

데이터기준일자
Categorical

CONSTANT 

Distinct1
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size8.1 KiB
2024-05-01
1022 

Length

Max length10
Median length10
Mean length10
Min length10

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2024-05-01
2nd row2024-05-01
3rd row2024-05-01
4th row2024-05-01
5th row2024-05-01

Common Values

ValueCountFrequency (%)
2024-05-01 1022
100.0%

Length

2024-05-04T07:36:29.877904image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-04T07:36:30.145092image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2024-05-01 1022
100.0%

Interactions

2024-05-04T07:36:20.214334image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Missing values

2024-05-04T07:36:20.606057image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-05-04T07:36:21.308829image/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

정거장명지번주소위도경도데이터기준일자
0공전3리입구충청북도 제천시 봉양읍 공전리 82-137.106137128.0849082024-05-01
1구곡3리경로당앞충청북도 제천시 봉양읍 구곡리 1095-137.092249128.0853872024-05-01
2구곡3리 굴탄대교앞충청북도 제천시 봉양읍 구곡리 1397-337.094171128.0826562024-05-01
3구곡리충청북도 제천시 봉양읍 구곡리 162-237.100523128.1064132024-05-01
4구곡리충청북도 제천시 봉양읍 구곡리 162-237.100523128.1064132024-05-01
5구곡리충청북도 제천시 봉양읍 구곡리 52637.088514128.1027512024-05-01
6구곡리충청북도 제천시 봉양읍구곡리 572-137.088595128.1025492024-05-01
7구곡리(구곡1리 마을회관 앞)충청북도 제천시 봉양읍 구곡리 562-137.089999128.1051152024-05-01
8구곡리(구곡1리 마을회관 앞)충청북도 제천시 봉양읍 구곡리 562-137.089999128.1051152024-05-01
9구곡리충청북도 제천시 봉양읍 구곡리 807-237.086732128.1002512024-05-01
정거장명지번주소위도경도데이터기준일자
1012옥전 자연휴양림충청북도 제천시 봉양읍 옥전리 29237.1766128.08962024-05-01
1013옥전 자연휴양림충청북도 제천시 봉양읍 옥전리 29237.1766128.08962024-05-01
1014옥전리충청북도 제천시 봉양읍 옥전리 41737.183128.07732024-05-01
1015옥전리충청북도 제천시 봉양읍 옥전리 41737.183128.07732024-05-01
1016청룡학사 후문 입구충청북도 제천시 신월동 57937.1792128.19592024-05-01
1017송수골충청북도 제천시 연박리 1202-537.1322128.09782024-05-01
1018안모산충청북도 제천시 모산동 207-437.1755128.21142024-05-01
1019강저제1공원충청북도 제천시 강제동 73237.1208128.20612024-05-01
1020정암마을 입구충청북도 제천시 시곡리 142337.1899128.28192024-05-01
1021덕곡리충청북도 제천시 덕곡리 557-336.9382128.11712024-05-01

Duplicate rows

Most frequently occurring

정거장명지번주소위도경도데이터기준일자# duplicates
31성내리충청북도 제천시 금성면 성내리 171-337.030273128.1776312024-05-013
0강저택지충청북도 제천시 강제동 80737.121734128.2032232024-05-012
1강제동충청북도 제천시 강제동 580-737.1248128.19472024-05-012
2강제주공3단지입구충청북도 제천시 강제동 90137.120304128.2018352024-05-012
3거문골충청북도 제천시 백운면 운학리 34037.216774128.0043812024-05-012
4고명동충청북도 제천시 고명동 695-1537.122973128.2306622024-05-012
5고명동(한천)충청북도 제천시 고명동 87937.119713128.2428512024-05-012
6교리충청북도 제천시 청풍면 교리 2137.016318128.1805092024-05-012
7구곡리충청북도 제천시 봉양읍 구곡리 162-237.100523128.1064132024-05-012
8구곡리(구곡1리 마을회관 앞)충청북도 제천시 봉양읍 구곡리 562-137.089999128.1051152024-05-012