Overview

Dataset statistics

Number of variables11
Number of observations201
Missing cells23
Missing cells (%)1.0%
Duplicate rows7
Duplicate rows (%)3.5%
Total size in memory18.0 KiB
Average record size in memory91.7 B

Variable types

Categorical4
Text4
Numeric3

Alerts

Dataset has 7 (3.5%) duplicate rowsDuplicates
특이사항 is highly overall correlated with 소재지우편번호 and 5 other fieldsHigh correlation
시군명 is highly overall correlated with 소재지우편번호 and 5 other fieldsHigh correlation
시설유형 is highly overall correlated with 소재지우편번호 and 3 other fieldsHigh correlation
관리기관명 is highly overall correlated with 소재지우편번호 and 5 other fieldsHigh correlation
소재지우편번호 is highly overall correlated with WGS84위도 and 4 other fieldsHigh correlation
WGS84위도 is highly overall correlated with 소재지우편번호 and 3 other fieldsHigh correlation
WGS84경도 is highly overall correlated with 시군명 and 2 other fieldsHigh correlation
시설유형 is highly imbalanced (74.9%)Imbalance
특이사항 is highly imbalanced (76.0%)Imbalance
소재지우편번호 has 4 (2.0%) missing valuesMissing
소재지도로명주소 has 17 (8.5%) missing valuesMissing

Reproduction

Analysis started2024-04-29 13:17:25.942758
Analysis finished2024-04-29 13:17:29.278978
Duration3.34 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

시군명
Categorical

HIGH CORRELATION 

Distinct30
Distinct (%)14.9%
Missing0
Missing (%)0.0%
Memory size1.7 KiB
평택시
38 
고양시
34 
남양주시
25 
여주시
19 
파주시
18 
Other values (25)
67 

Length

Max length4
Median length3
Mean length3.1343284
Min length3

Unique

Unique10 ?
Unique (%)5.0%

Sample

1st row가평군
2nd row가평군
3rd row가평군
4th row고양시
5th row고양시

Common Values

ValueCountFrequency (%)
평택시 38
18.9%
고양시 34
16.9%
남양주시 25
12.4%
여주시 19
9.5%
파주시 18
9.0%
양주시 8
 
4.0%
포천시 7
 
3.5%
안산시 6
 
3.0%
광명시 5
 
2.5%
구리시 4
 
2.0%
Other values (20) 37
18.4%

Length

2024-04-29T22:17:29.345237image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
평택시 38
18.9%
고양시 34
16.9%
남양주시 25
12.4%
여주시 19
9.5%
파주시 18
9.0%
양주시 8
 
4.0%
포천시 7
 
3.5%
안산시 6
 
3.0%
광명시 5
 
2.5%
구리시 4
 
2.0%
Other values (20) 37
18.4%

시설명
Text

Distinct154
Distinct (%)76.6%
Missing0
Missing (%)0.0%
Memory size1.7 KiB
2024-04-29T22:17:29.606200image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length14
Median length11
Mean length6.3283582
Min length3

Characters and Unicode

Total characters1272
Distinct characters152
Distinct categories6 ?
Distinct scripts3 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique142 ?
Unique (%)70.6%

Sample

1st row㈜진흥고속(현리)차고지
2nd row㈜진흥고속(가평)차고지
3rd row㈜진흥고속(청평)차고지
4th row주원교통
5th row(주)여산교통
ValueCountFrequency (%)
버스차고지 31
 
14.0%
차고지 7
 
3.2%
㈜명성 6
 
2.7%
버스공영차고지 5
 
2.3%
공영차고지 4
 
1.8%
화영운수 3
 
1.4%
합)신일여객 3
 
1.4%
신성교통㈜ 3
 
1.4%
경원여객 3
 
1.4%
태화상운 3
 
1.4%
Other values (147) 153
69.2%
2024-04-29T22:17:30.004389image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
고 99
 
7.8%
차 80
 
6.3%
지 80
 
6.3%
스 51
 
4.0%
버 50
 
3.9%
) 40
 
3.1%
( 40
 
3.1%
관 37
 
2.9%
영 37
 
2.9%
광 36
 
2.8%
Other values (142) 722
56.8%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1131
88.9%
Close Punctuation 40
 
3.1%
Open Punctuation 40
 
3.1%
Other Symbol 33
 
2.6%
Space Separator 25
 
2.0%
Uppercase Letter 3
 
0.2%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
고 99
 
8.8%
차 80
 
7.1%
지 80
 
7.1%
스 51
 
4.5%
버 50
 
4.4%
관 37
 
3.3%
영 37
 
3.3%
광 36
 
3.2%
주 35
 
3.1%
여 32
 
2.8%
Other values (134) 594
52.5%
Uppercase Letter
ValueCountFrequency (%)
T 1
33.3%
R 1
33.3%
B 1
33.3%
Space Separator
ValueCountFrequency (%)
20
80.0%
　 5
 
20.0%
Close Punctuation
ValueCountFrequency (%)
) 40
100.0%
Open Punctuation
ValueCountFrequency (%)
( 40
100.0%
Other Symbol
ValueCountFrequency (%)
㈜ 33
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1164
91.5%
Common 105
 
8.3%
Latin 3
 
0.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
고 99
 
8.5%
차 80
 
6.9%
지 80
 
6.9%
스 51
 
4.4%
버 50
 
4.3%
관 37
 
3.2%
영 37
 
3.2%
광 36
 
3.1%
주 35
 
3.0%
㈜ 33
 
2.8%
Other values (135) 626
53.8%
Common
ValueCountFrequency (%)
) 40
38.1%
( 40
38.1%
20
19.0%
　 5
 
4.8%
Latin
ValueCountFrequency (%)
T 1
33.3%
R 1
33.3%
B 1
33.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1131
88.9%
ASCII 103
 
8.1%
None 38
 
3.0%

Most frequent character per block

Hangul
ValueCountFrequency (%)
고 99
 
8.8%
차 80
 
7.1%
지 80
 
7.1%
스 51
 
4.5%
버 50
 
4.4%
관 37
 
3.3%
영 37
 
3.3%
광 36
 
3.2%
주 35
 
3.1%
여 32
 
2.8%
Other values (134) 594
52.5%
ASCII
ValueCountFrequency (%)
) 40
38.8%
( 40
38.8%
20
19.4%
T 1
 
1.0%
R 1
 
1.0%
B 1
 
1.0%
None
ValueCountFrequency (%)
㈜ 33
86.8%
　 5
 
13.2%

시설유형
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct4
Distinct (%)2.0%
Missing0
Missing (%)0.0%
Memory size1.7 KiB
버스차고지
185 
차고지
 
8
공영차고지
 
7
<NA>
 
1

Length

Max length5
Median length5
Mean length4.9154229
Min length3

Unique

Unique1 ?
Unique (%)0.5%

Sample

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

Common Values

ValueCountFrequency (%)
버스차고지 185
92.0%
차고지 8
 
4.0%
공영차고지 7
 
3.5%
<NA> 1
 
0.5%

Length

2024-04-29T22:17:30.137165image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-29T22:17:30.243901image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
버스차고지 185
92.0%
차고지 8
 
4.0%
공영차고지 7
 
3.5%
na 1
 
0.5%

소재지우편번호
Real number (ℝ)

HIGH CORRELATION  MISSING 

Distinct138
Distinct (%)70.1%
Missing4
Missing (%)2.0%
Infinite0
Infinite (%)0.0%
Mean13364.173
Minimum10020
Maximum18511
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.9 KiB
2024-04-29T22:17:30.366594image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum10020
5-th percentile10256.6
Q110944
median12420
Q315881
95-th percentile17876
Maximum18511
Range8491
Interquartile range (IQR)4937

Descriptive statistics

Standard deviation2797.2828
Coefficient of variation (CV)0.20931208
Kurtosis-1.1602738
Mean13364.173
Median Absolute Deviation (MAD)1883
Skewness0.60666792
Sum2632742
Variance7824791.2
MonotonicityNot monotonic
2024-04-29T22:17:30.516690image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
17865 6
 
3.0%
12668 5
 
2.5%
10315 4
 
2.0%
12666 4
 
2.0%
17741 4
 
2.0%
17724 3
 
1.5%
12611 3
 
1.5%
10317 3
 
1.5%
12188 3
 
1.5%
12160 3
 
1.5%
Other values (128) 159
79.1%
(Missing) 4
 
2.0%
ValueCountFrequency (%)
10020 1
0.5%
10023 1
0.5%
10219 1
0.5%
10220 1
0.5%
10226 2
1.0%
10247 1
0.5%
10250 1
0.5%
10251 2
1.0%
10258 1
0.5%
10261 2
1.0%
ValueCountFrequency (%)
18511 1
 
0.5%
18128 1
 
0.5%
17998 2
 
1.0%
17947 1
 
0.5%
17934 1
 
0.5%
17927 2
 
1.0%
17878 1
 
0.5%
17876 2
 
1.0%
17868 1
 
0.5%
17865 6
3.0%

소재지도로명주소
Text

MISSING 

Distinct148
Distinct (%)80.4%
Missing17
Missing (%)8.5%
Memory size1.7 KiB
2024-04-29T22:17:30.762044image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length28
Median length24.5
Mean length19.081522
Min length14

Characters and Unicode

Total characters3511
Distinct characters165
Distinct categories6 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique119 ?
Unique (%)64.7%

Sample

1st row경기도 가평군 조종면 청군로 1294
2nd row경기도 가평군 가평읍 가화로 51
3rd row경기도 가평군 청평면 청평중앙로 54
4th row경기도 고양시 덕양구 호국로1430번길 37
5th row경기도 고양시 덕양구 호국로1430번길 37
ValueCountFrequency (%)
경기도 184
 
22.0%
평택시 35
 
4.2%
고양시 31
 
3.7%
남양주시 21
 
2.5%
파주시 20
 
2.4%
일산동구 18
 
2.1%
여주시 14
 
1.7%
양주시 8
 
1.0%
점동면 8
 
1.0%
일산서구 7
 
0.8%
Other values (335) 492
58.7%
2024-04-29T22:17:31.149499image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
654
18.6%
도 197
 
5.6%
경 190
 
5.4%
기 186
 
5.3%
시 185
 
5.3%
로 156
 
4.4%
1 148
 
4.2%
2 84
 
2.4%
주 76
 
2.2%
양 71
 
2.0%
Other values (155) 1564
44.5%

Most occurring categories

ValueCountFrequency (%)
Other Letter 2152
61.3%
Decimal Number 664
 
18.9%
Space Separator 654
 
18.6%
Dash Punctuation 39
 
1.1%
Close Punctuation 1
 
< 0.1%
Open Punctuation 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
도 197
 
9.2%
경 190
 
8.8%
기 186
 
8.6%
시 185
 
8.6%
로 156
 
7.2%
주 76
 
3.5%
양 71
 
3.3%
길 66
 
3.1%
구 56
 
2.6%
평 49
 
2.3%
Other values (141) 920
42.8%
Decimal Number
ValueCountFrequency (%)
1 148
22.3%
2 84
12.7%
3 67
10.1%
6 66
9.9%
5 61
9.2%
4 58
 
8.7%
0 53
 
8.0%
8 46
 
6.9%
7 44
 
6.6%
9 37
 
5.6%
Space Separator
ValueCountFrequency (%)
654
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 39
100.0%
Close Punctuation
ValueCountFrequency (%)
) 1
100.0%
Open Punctuation
ValueCountFrequency (%)
( 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 2152
61.3%
Common 1359
38.7%

Most frequent character per script

Hangul
ValueCountFrequency (%)
도 197
 
9.2%
경 190
 
8.8%
기 186
 
8.6%
시 185
 
8.6%
로 156
 
7.2%
주 76
 
3.5%
양 71
 
3.3%
길 66
 
3.1%
구 56
 
2.6%
평 49
 
2.3%
Other values (141) 920
42.8%
Common
ValueCountFrequency (%)
654
48.1%
1 148
 
10.9%
2 84
 
6.2%
3 67
 
4.9%
6 66
 
4.9%
5 61
 
4.5%
4 58
 
4.3%
0 53
 
3.9%
8 46
 
3.4%
7 44
 
3.2%
Other values (4) 78
 
5.7%

Most occurring blocks

ValueCountFrequency (%)
Hangul 2152
61.3%
ASCII 1359
38.7%

Most frequent character per block

ASCII
ValueCountFrequency (%)
654
48.1%
1 148
 
10.9%
2 84
 
6.2%
3 67
 
4.9%
6 66
 
4.9%
5 61
 
4.5%
4 58
 
4.3%
0 53
 
3.9%
8 46
 
3.4%
7 44
 
3.2%
Other values (4) 78
 
5.7%
Hangul
ValueCountFrequency (%)
도 197
 
9.2%
경 190
 
8.8%
기 186
 
8.6%
시 185
 
8.6%
로 156
 
7.2%
주 76
 
3.5%
양 71
 
3.3%
길 66
 
3.1%
구 56
 
2.6%
평 49
 
2.3%
Other values (141) 920
42.8%

소재지지번주소
Text

Distinct165
Distinct (%)82.1%
Missing0
Missing (%)0.0%
Memory size1.7 KiB
2024-04-29T22:17:31.382304image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length26
Median length23
Mean length20.656716
Min length14

Characters and Unicode

Total characters4152
Distinct characters166
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

Unique136 ?
Unique (%)67.7%

Sample

1st row경기도 가평군 조종면 현리 296-12번지
2nd row경기도 가평군 가평읍 대곡리 168-9번지
3rd row경기도 가평군 청평면 청평리 432-48번지
4th row경기도 고양시 덕양구 대자동 171번지
5th row경기도 고양시 덕양구 대자동 171번지
ValueCountFrequency (%)
경기도 201
 
21.7%
평택시 38
 
4.1%
고양시 31
 
3.3%
남양주시 25
 
2.7%
파주시 20
 
2.2%
여주시 19
 
2.0%
일산동구 18
 
1.9%
식사동 10
 
1.1%
화도읍 9
 
1.0%
점동면 9
 
1.0%
Other values (368) 548
59.1%
2024-04-29T22:17:31.743955image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
727
 
17.5%
도 220
 
5.3%
기 203
 
4.9%
경 202
 
4.9%
시 200
 
4.8%
동 162
 
3.9%
지 152
 
3.7%
번 151
 
3.6%
1 143
 
3.4%
- 141
 
3.4%
Other values (156) 1851
44.6%

Most occurring categories

ValueCountFrequency (%)
Other Letter 2543
61.2%
Decimal Number 741
 
17.8%
Space Separator 727
 
17.5%
Dash Punctuation 141
 
3.4%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
도 220
 
8.7%
기 203
 
8.0%
경 202
 
7.9%
시 200
 
7.9%
동 162
 
6.4%
지 152
 
6.0%
번 151
 
5.9%
리 80
 
3.1%
양 78
 
3.1%
주 76
 
3.0%
Other values (144) 1019
40.1%
Decimal Number
ValueCountFrequency (%)
1 143
19.3%
2 107
14.4%
3 91
12.3%
5 67
9.0%
4 64
8.6%
8 62
8.4%
7 60
8.1%
9 56
 
7.6%
6 51
 
6.9%
0 40
 
5.4%
Space Separator
ValueCountFrequency (%)
727
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 141
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 2543
61.2%
Common 1609
38.8%

Most frequent character per script

Hangul
ValueCountFrequency (%)
도 220
 
8.7%
기 203
 
8.0%
경 202
 
7.9%
시 200
 
7.9%
동 162
 
6.4%
지 152
 
6.0%
번 151
 
5.9%
리 80
 
3.1%
양 78
 
3.1%
주 76
 
3.0%
Other values (144) 1019
40.1%
Common
ValueCountFrequency (%)
727
45.2%
1 143
 
8.9%
- 141
 
8.8%
2 107
 
6.7%
3 91
 
5.7%
5 67
 
4.2%
4 64
 
4.0%
8 62
 
3.9%
7 60
 
3.7%
9 56
 
3.5%
Other values (2) 91
 
5.7%

Most occurring blocks

ValueCountFrequency (%)
Hangul 2543
61.2%
ASCII 1609
38.8%

Most frequent character per block

ASCII
ValueCountFrequency (%)
727
45.2%
1 143
 
8.9%
- 141
 
8.8%
2 107
 
6.7%
3 91
 
5.7%
5 67
 
4.2%
4 64
 
4.0%
8 62
 
3.9%
7 60
 
3.7%
9 56
 
3.5%
Other values (2) 91
 
5.7%
Hangul
ValueCountFrequency (%)
도 220
 
8.7%
기 203
 
8.0%
경 202
 
7.9%
시 200
 
7.9%
동 162
 
6.4%
지 152
 
6.0%
번 151
 
5.9%
리 80
 
3.1%
양 78
 
3.1%
주 76
 
3.0%
Other values (144) 1019
40.1%

WGS84위도
Real number (ℝ)

HIGH CORRELATION 

Distinct164
Distinct (%)81.6%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean37.483155
Minimum36.949414
Maximum38.105217
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.9 KiB
2024-04-29T22:17:31.885983image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum36.949414
5-th percentile37.008801
Q137.232579
median37.586156
Q337.716399
95-th percentile37.895891
Maximum38.105217
Range1.1558028
Interquartile range (IQR)0.48381925

Descriptive statistics

Standard deviation0.30223318
Coefficient of variation (CV)0.0080631733
Kurtosis-1.1978643
Mean37.483155
Median Absolute Deviation (MAD)0.2186903
Skewness-0.25808073
Sum7534.1142
Variance0.091344892
MonotonicityNot monotonic
2024-04-29T22:17:32.047765image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
37.012215 5
 
2.5%
37.0526571 3
 
1.5%
37.0522643 3
 
1.5%
37.16762737 3
 
1.5%
37.6655005497 3
 
1.5%
37.749123 2
 
1.0%
37.6555538 2
 
1.0%
37.7389299 2
 
1.0%
37.7729839 2
 
1.0%
37.7457398 2
 
1.0%
Other values (154) 174
86.6%
ValueCountFrequency (%)
36.9494144 1
0.5%
36.957276 1
0.5%
36.9604144 1
0.5%
36.9851644 1
0.5%
36.9894946 1
0.5%
36.9935189 1
0.5%
36.9963502 1
0.5%
36.9999141 1
0.5%
37.003608 1
0.5%
37.0082191 1
0.5%
ValueCountFrequency (%)
38.10521716 1
0.5%
38.0676985 1
0.5%
38.057366 1
0.5%
37.95534123 1
0.5%
37.95512292 1
0.5%
37.95129131 1
0.5%
37.9457935 1
0.5%
37.9036908 1
0.5%
37.89874581 2
1.0%
37.8958906 1
0.5%

WGS84경도
Real number (ℝ)

HIGH CORRELATION 

Distinct164
Distinct (%)81.6%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean127.07524
Minimum126.54223
Maximum127.68685
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.9 KiB
2024-04-29T22:17:32.180285image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum126.54223
5-th percentile126.74259
Q1126.84673
median127.07536
Q3127.21663
95-th percentile127.65742
Maximum127.68685
Range1.144614
Interquartile range (IQR)0.3698978

Descriptive statistics

Standard deviation0.26738751
Coefficient of variation (CV)0.0021041669
Kurtosis-0.10399033
Mean127.07524
Median Absolute Deviation (MAD)0.1858605
Skewness0.66402755
Sum25542.122
Variance0.071496081
MonotonicityNot monotonic
2024-04-29T22:17:32.303780image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
127.1378615 5
 
2.5%
127.0723693 3
 
1.5%
127.1147176 3
 
1.5%
127.6678035 3
 
1.5%
127.3024824138 3
 
1.5%
127.218503 2
 
1.0%
127.1828622 2
 
1.0%
127.2147505 2
 
1.0%
126.7337394 2
 
1.0%
127.2052505 2
 
1.0%
Other values (154) 174
86.6%
ValueCountFrequency (%)
126.5422341 1
0.5%
126.5632849 1
0.5%
126.6261394 1
0.5%
126.7106888 1
0.5%
126.7207391 1
0.5%
126.7308558 1
0.5%
126.7337394 2
1.0%
126.7385218 1
0.5%
126.7418539 1
0.5%
126.742587 2
1.0%
ValueCountFrequency (%)
127.6868481 1
 
0.5%
127.6717606 2
1.0%
127.6678035 3
1.5%
127.6619394 1
 
0.5%
127.6595475 1
 
0.5%
127.658559 2
1.0%
127.6574188 2
1.0%
127.6511597 1
 
0.5%
127.64845 2
1.0%
127.6395659 2
1.0%

관리기관명
Categorical

HIGH CORRELATION 

Distinct50
Distinct (%)24.9%
Missing0
Missing (%)0.0%
Memory size1.7 KiB
평택시청
38 
고양시청
34 
여주시청
19 
파주시청
18 
KD운송그룹
12 
Other values (45)
80 

Length

Max length15
Median length4
Mean length4.761194
Min length3

Unique

Unique26 ?
Unique (%)12.9%

Sample

1st row가평군청
2nd row가평군청
3rd row가평군청
4th row고양시청
5th row고양시청

Common Values

ValueCountFrequency (%)
평택시청 38
18.9%
고양시청 34
16.9%
여주시청 19
 
9.5%
파주시청 18
 
9.0%
KD운송그룹 12
 
6.0%
광명시청 5
 
2.5%
선진시내버스 4
 
2.0%
경기도 구리시청 4
 
2.0%
수원시 4
 
2.0%
시흥도시공사 3
 
1.5%
Other values (40) 60
29.9%

Length

2024-04-29T22:17:32.427881image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
평택시청 38
17.8%
고양시청 34
16.0%
여주시청 19
 
8.9%
파주시청 18
 
8.5%
kd운송그룹 12
 
5.6%
경기도 9
 
4.2%
광명시청 5
 
2.3%
선진시내버스 4
 
1.9%
구리시청 4
 
1.9%
수원시 4
 
1.9%
Other values (44) 66
31.0%

연락처
Text

Distinct102
Distinct (%)51.3%
Missing2
Missing (%)1.0%
Memory size1.7 KiB
2024-04-29T22:17:32.630157image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length13
Median length12
Mean length12.170854
Min length9

Characters and Unicode

Total characters2422
Distinct characters11
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique74 ?
Unique (%)37.2%

Sample

1st row031-580-2291
2nd row031-580-2291
3rd row031-580-2291
4th row031-8075-2927
5th row031-8075-2927
ValueCountFrequency (%)
031-8075-2927 21
 
10.6%
02-3436-6366 12
 
6.0%
031-8075-2928 12
 
6.0%
031-940-5296 11
 
5.5%
031-8082-6627 8
 
4.0%
031-541-1988 5
 
2.5%
031-228-2282 4
 
2.0%
032-883-5111 3
 
1.5%
031-580-2291 3
 
1.5%
031-719-8390 3
 
1.5%
Other values (92) 117
58.8%
2024-04-29T22:17:33.008027image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
- 396
16.4%
0 337
13.9%
3 281
11.6%
1 271
11.2%
2 235
9.7%
6 197
8.1%
8 193
8.0%
5 160
6.6%
9 139
 
5.7%
7 125
 
5.2%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 2026
83.6%
Dash Punctuation 396
 
16.4%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 337
16.6%
3 281
13.9%
1 271
13.4%
2 235
11.6%
6 197
9.7%
8 193
9.5%
5 160
7.9%
9 139
6.9%
7 125
 
6.2%
4 88
 
4.3%
Dash Punctuation
ValueCountFrequency (%)
- 396
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 2422
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
- 396
16.4%
0 337
13.9%
3 281
11.6%
1 271
11.2%
2 235
9.7%
6 197
8.1%
8 193
8.0%
5 160
6.6%
9 139
 
5.7%
7 125
 
5.2%

Most occurring blocks

ValueCountFrequency (%)
ASCII 2422
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
- 396
16.4%
0 337
13.9%
3 281
11.6%
1 271
11.2%
2 235
9.7%
6 197
8.1%
8 193
8.0%
5 160
6.6%
9 139
 
5.7%
7 125
 
5.2%

특이사항
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct7
Distinct (%)3.5%
Missing0
Missing (%)0.0%
Memory size1.7 KiB
<NA>
177 
전세버스
19 
마을버스차고지(2, 2-2, 7, 7-1번)
 
1
시내버스차고지 (51, 75, 75-1, 78, 1115-6, 1650, 1680, G1690번)
 
1
마을버스차고지(5, 5-1, 8번)
 
1
Other values (2)
 
2

Length

Max length54
Median length4
Mean length4.5920398
Min length4

Unique

Unique5 ?
Unique (%)2.5%

Sample

1st row<NA>
2nd row<NA>
3rd row<NA>
4th row<NA>
5th row<NA>

Common Values

ValueCountFrequency (%)
<NA> 177
88.1%
전세버스 19
 
9.5%
마을버스차고지(2, 2-2, 7, 7-1번) 1
 
0.5%
시내버스차고지 (51, 75, 75-1, 78, 1115-6, 1650, 1680, G1690번) 1
 
0.5%
마을버스차고지(5, 5-1, 8번) 1
 
0.5%
마을버스차고지(6, 6-1, 6-2번) 1
 
0.5%
면적(68058㎡)+주차면수(581면) 1
 
0.5%

Length

2024-04-29T22:17:33.153465image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-29T22:17:33.282192image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 177
81.9%
전세버스 19
 
8.8%
6-2번 1
 
0.5%
6-1 1
 
0.5%
마을버스차고지(6 1
 
0.5%
8번 1
 
0.5%
5-1 1
 
0.5%
마을버스차고지(5 1
 
0.5%
g1690번 1
 
0.5%
1680 1
 
0.5%
Other values (12) 12
 
5.6%

Interactions

2024-04-29T22:17:28.678156image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-29T22:17:28.144342image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-29T22:17:28.421765image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-29T22:17:28.754630image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-29T22:17:28.266405image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-29T22:17:28.503493image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-29T22:17:28.836121image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-29T22:17:28.342345image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-29T22:17:28.593117image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-04-29T22:17:33.374774image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
시군명시설유형소재지우편번호WGS84위도WGS84경도관리기관명특이사항
시군명1.0001.0000.9980.9510.9601.0001.000
시설유형1.0001.0000.7240.3450.0001.000NaN
소재지우편번호0.9980.7241.0000.9200.8760.9981.000
WGS84위도0.9510.3450.9201.0000.7380.9540.736
WGS84경도0.9600.0000.8760.7381.0000.9561.000
관리기관명1.0001.0000.9980.9540.9561.0001.000
특이사항1.000NaN1.0000.7361.0001.0001.000
2024-04-29T22:17:33.684837image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
특이사항시군명시설유형관리기관명
특이사항1.0000.9261.0000.926
시군명0.9261.0000.9320.940
시설유형1.0000.9321.0000.875
관리기관명0.9260.9400.8751.000
2024-04-29T22:17:33.766000image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
소재지우편번호WGS84위도WGS84경도시군명시설유형관리기관명특이사항
소재지우편번호1.000-0.8570.3660.9330.5770.8770.926
WGS84위도-0.8571.000-0.2960.6340.2160.6110.585
WGS84경도0.366-0.2961.0000.6610.0000.6170.926
시군명0.9330.6340.6611.0000.9320.9400.926
시설유형0.5770.2160.0000.9321.0000.8751.000
관리기관명0.8770.6110.6170.9400.8751.0000.926
특이사항0.9260.5850.9260.9261.0000.9261.000

Missing values

2024-04-29T22:17:28.946197image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-04-29T22:17:29.088433image/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.
2024-04-29T22:17:29.203965image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
The correlation heatmap measures nullity correlation: how strongly the presence or absence of one variable affects the presence of another.

Sample

시군명시설명시설유형소재지우편번호소재지도로명주소소재지지번주소WGS84위도WGS84경도관리기관명연락처특이사항
0가평군㈜진흥고속(현리)차고지버스차고지12437경기도 가평군 조종면 청군로 1294경기도 가평군 조종면 현리 296-12번지37.819771127.34617가평군청031-580-2291<NA>
1가평군㈜진흥고속(가평)차고지버스차고지12420경기도 가평군 가평읍 가화로 51경기도 가평군 가평읍 대곡리 168-9번지37.82459127.515466가평군청031-580-2291<NA>
2가평군㈜진흥고속(청평)차고지버스차고지12452경기도 가평군 청평면 청평중앙로 54경기도 가평군 청평면 청평리 432-48번지37.738117127.420856가평군청031-580-2291<NA>
3고양시주원교통버스차고지10277경기도 고양시 덕양구 호국로1430번길 37경기도 고양시 덕양구 대자동 171번지37.679771126.896028고양시청031-8075-2927<NA>
4고양시(주)여산교통버스차고지10277경기도 고양시 덕양구 호국로1430번길 37경기도 고양시 덕양구 대자동 171번지37.679771126.896028고양시청031-8075-2927<NA>
5고양시(주)대덕운수버스차고지10316경기도 고양시 일산동구 사리현로 12경기도 고양시 일산동구 식사동 249-9번지37.688075126.820737고양시청031-8075-2927<NA>
6고양시(주)화정교통버스차고지10315경기도 고양시 일산동구 사리현로 23경기도 고양시 일산동구 식사동 251-1번지37.688763126.822731고양시청031-8075-2927<NA>
7고양시㈜성우교통버스차고지10315경기도 고양시 일산동구 사리현로 23경기도 고양시 일산동구 식사동 251-1번지37.688573126.822368고양시청031-8075-2927<NA>
8고양시자안운수버스차고지10315경기도 고양시 일산동구 사리현로 19경기도 고양시 일산동구 식사동 250-6번지37.688798126.822209고양시청031-8075-2927<NA>
9고양시한진교통버스차고지10261경기도 고양시 일산동구 공릉천로 106경기도 고양시 일산동구 사리현동 240번지37.688798126.822209고양시청031-8075-2927<NA>
시군명시설명시설유형소재지우편번호소재지도로명주소소재지지번주소WGS84위도WGS84경도관리기관명연락처특이사항
191포천시설운동차고지버스차고지11161경기도 포천시 호국로883번길 9경기도 포천시 설운동 70-25번지37.844754127.157645선진시내버스,포천상운031-541-1988<NA>
192포천시신북면차고지버스차고지11138경기도 포천시 신북면 신평로 150-17경기도 포천시 신북면 신평리 137번지37.945794127.225047포천교통031-534-7731<NA>
193포천시하성북리차고지버스차고지11151경기도 포천시 군내면 청성로33번길 32경기도 포천시 군내면 하성북리 540-4번지37.903691127.216632선진시내버스031-541-1988<NA>
194포천시도평리차고지버스차고지11110경기도 포천시 이동면 화동로 2411경기도 포천시 이동면 도평리 166-8번지38.057366127.385025선진시내버스031-541-1988<NA>
195포천시아트홀차고지버스차고지11151경기도 포천시 군내면 청성로 112경기도 포천시 군내면 하성북리 618번지37.895891127.21055선진시내버스031-541-1988<NA>
196포천시내촌차고지버스차고지11188경기도 포천시 내촌면 금강로2634번길 33경기도 포천시 내촌면 소학리 425-6번지37.804846127.250242선진시내버스031-541-1988<NA>
197포천시산정호수차고지버스차고지11103<NA>경기도 포천시 영북면 산정리 75-538.067698127.325173포천교통031-534-7731<NA>
198하남시상산곡동공영차고지차고지13026경기도 하남시 하남대로284번길 29경기도 하남시 상산곡동 59번지37.499713127.23361하남시청031-5182-1155<NA>
199하남시BRT버스환승공영차고지차고지13023경기도 하남시 창우로 146경기도 하남시 창우동 539번지37.539026127.230138하남시청031-5182-1155<NA>
200화성시버스공영차고지<NA>18511경기도 화성시 10용사로 636경기도 화성시 반송동 240번지37.185495127.079439화성시 버스혁신과031-5189-2847<NA>

Duplicate rows

Most frequently occurring

시군명시설명시설유형소재지우편번호소재지도로명주소소재지지번주소WGS84위도WGS84경도관리기관명연락처특이사항# duplicates
0남양주시버스차고지버스차고지12017경기도 남양주시 진접읍 팔야로82번길 3경기도 남양주시 진접읍 팔야리 495-3번지37.749123127.218503(주)태산운수031-529-1207<NA>2
1남양주시버스차고지버스차고지12019경기도 남양주시 진접읍 광릉내로 102경기도 남양주시 진접읍 팔야리 759-1번지37.74574127.205251KD운송그룹02-3436-6366<NA>2
2남양주시버스차고지버스차고지12021경기도 남양주시 진접읍 경복대로 497경기도 남양주시 진접읍 진벌리 638-5번지37.73893127.21475KD운송그룹02-3436-6366<NA>2
3남양주시버스차고지버스차고지12136경기도 남양주시 진건읍 사릉로372번길 1경기도 남양주시 진건읍 사능리 355번지37.655554127.182862KD운송그룹02-3436-6366<NA>2
4남양주시버스차고지버스차고지12147경기도 남양주시 호평로67번길 2경기도 남양주시 호평동 189-3번지37.656834127.247585KD운송그룹02-3436-6366<NA>2
5남양주시버스차고지버스차고지12197경기도 남양주시 화도읍 수레로1092번길 5-4경기도 남양주시 화도읍 차산리 167-1번지37.634168127.304938KD운송그룹02-3436-6366<NA>2
6남양주시버스차고지버스차고지12270경기도 남양주시 와부읍 덕소로 320경기도 남양주시 와부읍 도곡리 517-3번지37.572712127.226334KD운송그룹02-3436-6366<NA>2