Overview

Dataset statistics

Number of variables8
Number of observations10000
Missing cells14235
Missing cells (%)17.8%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory732.4 KiB
Average record size in memory75.0 B

Variable types

Numeric3
Categorical1
Text4

Dataset

Description부산광역시_교통시설물관리시스템_교통안전시설물정보(부착대정보)_20220630
Author부산광역시
URLhttp://data.busan.go.kr/dataSet/detail.nm?contentId=10&publicdatapk=15084054

Alerts

경도 is highly overall correlated with 위도 and 1 other fieldsHigh correlation
위도 is highly overall correlated with 경도 and 1 other fieldsHigh correlation
시군구명 is highly overall correlated with 경도 and 1 other fieldsHigh correlation
리명 has 8909 (89.1%) missing valuesMissing
도로명 has 5208 (52.1%) missing valuesMissing
교차로명 has 118 (1.2%) missing valuesMissing
번호 has unique valuesUnique

Reproduction

Analysis started2023-12-10 17:03:21.464192
Analysis finished2023-12-10 17:03:24.822380
Duration3.36 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

번호
Real number (ℝ)

UNIQUE 

Distinct10000
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean6013.2507
Minimum1
Maximum12033
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2023-12-11T02:03:24.942640image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile615.95
Q13011.5
median5992.5
Q39018.25
95-th percentile11422.05
Maximum12033
Range12032
Interquartile range (IQR)6006.75

Descriptive statistics

Standard deviation3468.5024
Coefficient of variation (CV)0.57680987
Kurtosis-1.2019369
Mean6013.2507
Median Absolute Deviation (MAD)3004
Skewness0.0057474712
Sum60132507
Variance12030509
MonotonicityNot monotonic
2023-12-11T02:03:25.171836image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
9250 1
 
< 0.1%
11767 1
 
< 0.1%
10681 1
 
< 0.1%
11578 1
 
< 0.1%
6356 1
 
< 0.1%
11747 1
 
< 0.1%
7587 1
 
< 0.1%
8385 1
 
< 0.1%
606 1
 
< 0.1%
11511 1
 
< 0.1%
Other values (9990) 9990
99.9%
ValueCountFrequency (%)
1 1
< 0.1%
2 1
< 0.1%
3 1
< 0.1%
5 1
< 0.1%
7 1
< 0.1%
8 1
< 0.1%
9 1
< 0.1%
10 1
< 0.1%
11 1
< 0.1%
12 1
< 0.1%
ValueCountFrequency (%)
12033 1
< 0.1%
12032 1
< 0.1%
12031 1
< 0.1%
12029 1
< 0.1%
12028 1
< 0.1%
12026 1
< 0.1%
12025 1
< 0.1%
12022 1
< 0.1%
12021 1
< 0.1%
12020 1
< 0.1%

시군구명
Categorical

HIGH CORRELATION 

Distinct16
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
강서구
1334 
해운대구
1098 
기장군
1089 
부산진구
848 
사하구
698 
Other values (11)
4933 

Length

Max length4
Median length3
Mean length3.0022
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row강서구
2nd row강서구
3rd row기장군
4th row서구
5th row해운대구

Common Values

ValueCountFrequency (%)
강서구 1334
13.3%
해운대구 1098
11.0%
기장군 1089
10.9%
부산진구 848
8.5%
사하구 698
 
7.0%
동래구 659
 
6.6%
사상구 627
 
6.3%
남구 602
 
6.0%
북구 556
 
5.6%
금정구 498
 
5.0%
Other values (6) 1991
19.9%

Length

2023-12-11T02:03:25.387297image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
강서구 1334
13.3%
해운대구 1098
11.0%
기장군 1089
10.9%
부산진구 848
8.5%
사하구 698
 
7.0%
동래구 659
 
6.6%
사상구 627
 
6.3%
남구 602
 
6.0%
북구 556
 
5.6%
금정구 498
 
5.0%
Other values (6) 1991
19.9%

동명
Text

Distinct159
Distinct (%)1.6%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2023-12-11T02:03:25.805639image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length6
Median length3
Mean length3.0662
Min length2

Characters and Unicode

Total characters30662
Distinct characters119
Distinct categories2 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique3 ?
Unique (%)< 0.1%

Sample

1st row구랑동
2nd row죽림동
3rd row일광면
4th row동대신동2가
5th row재송동
ValueCountFrequency (%)
정관읍 342
 
3.4%
우동 314
 
3.1%
연산동 296
 
3.0%
기장읍 282
 
2.8%
장안읍 254
 
2.5%
송정동 253
 
2.5%
거제동 201
 
2.0%
명지동 183
 
1.8%
중동 175
 
1.8%
대저2동 168
 
1.7%
Other values (149) 7532
75.3%
2023-12-11T02:03:26.404730image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
동 9195
30.0%
읍 914
 
3.0%
장 861
 
2.8%
정 831
 
2.7%
대 741
 
2.4%
가 557
 
1.8%
천 546
 
1.8%
연 520
 
1.7%
전 506
 
1.7%
명 503
 
1.6%
Other values (109) 15488
50.5%

Most occurring categories

ValueCountFrequency (%)
Other Letter 29943
97.7%
Decimal Number 719
 
2.3%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
동 9195
30.7%
읍 914
 
3.1%
장 861
 
2.9%
정 831
 
2.8%
대 741
 
2.5%
가 557
 
1.9%
천 546
 
1.8%
연 520
 
1.7%
전 506
 
1.7%
명 503
 
1.7%
Other values (103) 14769
49.3%
Decimal Number
ValueCountFrequency (%)
2 308
42.8%
1 174
24.2%
3 134
18.6%
4 52
 
7.2%
5 33
 
4.6%
6 18
 
2.5%

Most occurring scripts

ValueCountFrequency (%)
Hangul 29943
97.7%
Common 719
 
2.3%

Most frequent character per script

Hangul
ValueCountFrequency (%)
동 9195
30.7%
읍 914
 
3.1%
장 861
 
2.9%
정 831
 
2.8%
대 741
 
2.5%
가 557
 
1.9%
천 546
 
1.8%
연 520
 
1.7%
전 506
 
1.7%
명 503
 
1.7%
Other values (103) 14769
49.3%
Common
ValueCountFrequency (%)
2 308
42.8%
1 174
24.2%
3 134
18.6%
4 52
 
7.2%
5 33
 
4.6%
6 18
 
2.5%

Most occurring blocks

ValueCountFrequency (%)
Hangul 29943
97.7%
ASCII 719
 
2.3%

Most frequent character per block

Hangul
ValueCountFrequency (%)
동 9195
30.7%
읍 914
 
3.1%
장 861
 
2.9%
정 831
 
2.8%
대 741
 
2.5%
가 557
 
1.9%
천 546
 
1.8%
연 520
 
1.7%
전 506
 
1.7%
명 503
 
1.7%
Other values (103) 14769
49.3%
ASCII
ValueCountFrequency (%)
2 308
42.8%
1 174
24.2%
3 134
18.6%
4 52
 
7.2%
5 33
 
4.6%
6 18
 
2.5%

리명
Text

MISSING 

Distinct55
Distinct (%)5.0%
Missing8909
Missing (%)89.1%
Memory size156.2 KiB
2023-12-11T02:03:26.712553image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length3
Median length3
Mean length2.964253
Min length2

Characters and Unicode

Total characters3234
Distinct characters68
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

Unique1 ?
Unique (%)0.1%

Sample

1st row화전리
2nd row임랑리
3rd row예림리
4th row반룡리
5th row연화리
ValueCountFrequency (%)
용수리 91
 
8.3%
반룡리 76
 
7.0%
모전리 64
 
5.9%
청강리 52
 
4.8%
달산리 52
 
4.8%
예림리 52
 
4.8%
대라리 50
 
4.6%
매학리 47
 
4.3%
대변리 38
 
3.5%
시랑리 38
 
3.5%
Other values (45) 531
48.7%
2023-12-11T02:03:27.181525image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
리 1091
33.7%
룡 108
 
3.3%
천 105
 
3.2%
용 101
 
3.1%
수 91
 
2.8%
대 88
 
2.7%
전 81
 
2.5%
반 76
 
2.4%
모 64
 
2.0%
산 62
 
1.9%
Other values (58) 1367
42.3%

Most occurring categories

ValueCountFrequency (%)
Other Letter 3234
100.0%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
리 1091
33.7%
룡 108
 
3.3%
천 105
 
3.2%
용 101
 
3.1%
수 91
 
2.8%
대 88
 
2.7%
전 81
 
2.5%
반 76
 
2.4%
모 64
 
2.0%
산 62
 
1.9%
Other values (58) 1367
42.3%

Most occurring scripts

ValueCountFrequency (%)
Hangul 3234
100.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
리 1091
33.7%
룡 108
 
3.3%
천 105
 
3.2%
용 101
 
3.1%
수 91
 
2.8%
대 88
 
2.7%
전 81
 
2.5%
반 76
 
2.4%
모 64
 
2.0%
산 62
 
1.9%
Other values (58) 1367
42.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 3234
100.0%

Most frequent character per block

Hangul
ValueCountFrequency (%)
리 1091
33.7%
룡 108
 
3.3%
천 105
 
3.2%
용 101
 
3.1%
수 91
 
2.8%
대 88
 
2.7%
전 81
 
2.5%
반 76
 
2.4%
모 64
 
2.0%
산 62
 
1.9%
Other values (58) 1367
42.3%

도로명
Text

MISSING 

Distinct2358
Distinct (%)49.2%
Missing5208
Missing (%)52.1%
Memory size156.2 KiB
2023-12-11T02:03:27.687710image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length17
Median length14
Mean length9.3332638
Min length3

Characters and Unicode

Total characters44725
Distinct characters265
Distinct categories5 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1348 ?
Unique (%)28.1%

Sample

1st row가락대로 1405
2nd row수림로62번길 9
3rd row온천장로 123
4th row수영로 709-1
5th row낙동대로295번길 7
ValueCountFrequency (%)
16 105
 
1.1%
9 103
 
1.1%
중앙대로 98
 
1.0%
11 94
 
1.0%
7 89
 
0.9%
10 84
 
0.9%
해운대로 76
 
0.8%
35 70
 
0.7%
8 69
 
0.7%
14 68
 
0.7%
Other values (2244) 8724
91.1%
2023-12-11T02:03:28.371054image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
4788
 
10.7%
로 4611
 
10.3%
1 3677
 
8.2%
2 2280
 
5.1%
길 2051
 
4.6%
3 1999
 
4.5%
번 1911
 
4.3%
4 1645
 
3.7%
5 1449
 
3.2%
7 1381
 
3.1%
Other values (255) 18933
42.3%

Most occurring categories

ValueCountFrequency (%)
Other Letter 21755
48.6%
Decimal Number 17099
38.2%
Space Separator 4788
 
10.7%
Dash Punctuation 1059
 
2.4%
Uppercase Letter 24
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
로 4611
21.2%
길 2051
 
9.4%
번 1911
 
8.8%
대 1261
 
5.8%
동 456
 
2.1%
산 408
 
1.9%
수 269
 
1.2%
해 256
 
1.2%
장 255
 
1.2%
천 243
 
1.1%
Other values (239) 10034
46.1%
Decimal Number
ValueCountFrequency (%)
1 3677
21.5%
2 2280
13.3%
3 1999
11.7%
4 1645
9.6%
5 1449
 
8.5%
7 1381
 
8.1%
6 1313
 
7.7%
9 1166
 
6.8%
8 1122
 
6.6%
0 1067
 
6.2%
Uppercase Letter
ValueCountFrequency (%)
E 6
25.0%
C 6
25.0%
P 6
25.0%
A 6
25.0%
Space Separator
ValueCountFrequency (%)
4788
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 1059
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 22946
51.3%
Hangul 21755
48.6%
Latin 24
 
0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
로 4611
21.2%
길 2051
 
9.4%
번 1911
 
8.8%
대 1261
 
5.8%
동 456
 
2.1%
산 408
 
1.9%
수 269
 
1.2%
해 256
 
1.2%
장 255
 
1.2%
천 243
 
1.1%
Other values (239) 10034
46.1%
Common
ValueCountFrequency (%)
4788
20.9%
1 3677
16.0%
2 2280
9.9%
3 1999
8.7%
4 1645
 
7.2%
5 1449
 
6.3%
7 1381
 
6.0%
6 1313
 
5.7%
9 1166
 
5.1%
8 1122
 
4.9%
Other values (2) 2126
9.3%
Latin
ValueCountFrequency (%)
E 6
25.0%
C 6
25.0%
P 6
25.0%
A 6
25.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 22970
51.4%
Hangul 21755
48.6%

Most frequent character per block

ASCII
ValueCountFrequency (%)
4788
20.8%
1 3677
16.0%
2 2280
9.9%
3 1999
8.7%
4 1645
 
7.2%
5 1449
 
6.3%
7 1381
 
6.0%
6 1313
 
5.7%
9 1166
 
5.1%
8 1122
 
4.9%
Other values (6) 2150
9.4%
Hangul
ValueCountFrequency (%)
로 4611
21.2%
길 2051
 
9.4%
번 1911
 
8.8%
대 1261
 
5.8%
동 456
 
2.1%
산 408
 
1.9%
수 269
 
1.2%
해 256
 
1.2%
장 255
 
1.2%
천 243
 
1.1%
Other values (239) 10034
46.1%

교차로명
Text

MISSING 

Distinct3485
Distinct (%)35.3%
Missing118
Missing (%)1.2%
Memory size156.2 KiB
2023-12-11T02:03:28.808848image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length22
Median length19
Mean length7.7685691
Min length2

Characters and Unicode

Total characters76769
Distinct characters598
Distinct categories11 ?
Distinct scripts3 ?
Distinct blocks5 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1007 ?
Unique (%)10.2%

Sample

1st row미음지구1공구-3지점
2nd row가락중학교
3rd row부산은행연수원 진입로
4th row대신로타리
5th row재송유치원 진입로
ValueCountFrequency (%)
앞 358
 
2.9%
화전지구산업단지 141
 
1.1%
명지주거단지 89
 
0.7%
입구 81
 
0.6%
서부산유통단지 64
 
0.5%
주변 54
 
0.4%
옆 45
 
0.4%
장안일반산업단지 38
 
0.3%
후문 36
 
0.3%
명례일반산업단지 33
 
0.3%
Other values (3755) 11607
92.5%
2023-12-11T02:03:29.536024image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
2687
 
3.5%
지 2414
 
3.1%
구 1805
 
2.4%
동 1788
 
2.3%
) 1617
 
2.1%
( 1579
 
2.1%
교 1494
 
1.9%
산 1393
 
1.8%
리 1310
 
1.7%
아 1224
 
1.6%
Other values (588) 59458
77.5%

Most occurring categories

ValueCountFrequency (%)
Other Letter 64761
84.4%
Decimal Number 4191
 
5.5%
Space Separator 2687
 
3.5%
Close Punctuation 1617
 
2.1%
Open Punctuation 1579
 
2.1%
Uppercase Letter 1277
 
1.7%
Dash Punctuation 382
 
0.5%
Other Punctuation 180
 
0.2%
Lowercase Letter 43
 
0.1%
Math Symbol 30
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
지 2414
 
3.7%
구 1805
 
2.8%
동 1788
 
2.8%
교 1494
 
2.3%
산 1393
 
2.2%
리 1310
 
2.0%
아 1224
 
1.9%
대 1164
 
1.8%
트 1163
 
1.8%
장 1046
 
1.6%
Other values (528) 49960
77.1%
Uppercase Letter
ValueCountFrequency (%)
P 172
13.5%
B 146
11.4%
L 113
8.8%
C 105
8.2%
A 97
7.6%
G 94
 
7.4%
S 93
 
7.3%
E 80
 
6.3%
I 76
 
6.0%
K 62
 
4.9%
Other values (14) 239
18.7%
Lowercase Letter
ValueCountFrequency (%)
e 9
20.9%
a 7
16.3%
r 6
14.0%
k 6
14.0%
n 4
9.3%
s 3
 
7.0%
o 2
 
4.7%
g 2
 
4.7%
t 2
 
4.7%
i 1
 
2.3%
Decimal Number
ValueCountFrequency (%)
1 1219
29.1%
2 960
22.9%
3 522
12.5%
4 366
 
8.7%
0 318
 
7.6%
8 180
 
4.3%
6 175
 
4.2%
5 170
 
4.1%
7 154
 
3.7%
9 127
 
3.0%
Other Punctuation
ValueCountFrequency (%)
, 86
47.8%
' 47
26.1%
. 25
 
13.9%
: 10
 
5.6%
" 6
 
3.3%
@ 3
 
1.7%
/ 3
 
1.7%
Math Symbol
ValueCountFrequency (%)
~ 24
80.0%
→ 3
 
10.0%
> 3
 
10.0%
Space Separator
ValueCountFrequency (%)
2687
100.0%
Close Punctuation
ValueCountFrequency (%)
) 1617
100.0%
Open Punctuation
ValueCountFrequency (%)
( 1579
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 382
100.0%
Other Symbol
ValueCountFrequency (%)
㈜ 22
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 64783
84.4%
Common 10666
 
13.9%
Latin 1320
 
1.7%

Most frequent character per script

Hangul
ValueCountFrequency (%)
지 2414
 
3.7%
구 1805
 
2.8%
동 1788
 
2.8%
교 1494
 
2.3%
산 1393
 
2.2%
리 1310
 
2.0%
아 1224
 
1.9%
대 1164
 
1.8%
트 1163
 
1.8%
장 1046
 
1.6%
Other values (529) 49982
77.2%
Latin
ValueCountFrequency (%)
P 172
13.0%
B 146
11.1%
L 113
8.6%
C 105
 
8.0%
A 97
 
7.3%
G 94
 
7.1%
S 93
 
7.0%
E 80
 
6.1%
I 76
 
5.8%
K 62
 
4.7%
Other values (25) 282
21.4%
Common
ValueCountFrequency (%)
2687
25.2%
) 1617
15.2%
( 1579
14.8%
1 1219
11.4%
2 960
 
9.0%
3 522
 
4.9%
- 382
 
3.6%
4 366
 
3.4%
0 318
 
3.0%
8 180
 
1.7%
Other values (14) 836
 
7.8%

Most occurring blocks

ValueCountFrequency (%)
Hangul 64758
84.4%
ASCII 11983
 
15.6%
None 22
 
< 0.1%
Arrows 3
 
< 0.1%
Compat Jamo 3
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
2687
22.4%
) 1617
13.5%
( 1579
13.2%
1 1219
10.2%
2 960
 
8.0%
3 522
 
4.4%
- 382
 
3.2%
4 366
 
3.1%
0 318
 
2.7%
8 180
 
1.5%
Other values (48) 2153
18.0%
Hangul
ValueCountFrequency (%)
지 2414
 
3.7%
구 1805
 
2.8%
동 1788
 
2.8%
교 1494
 
2.3%
산 1393
 
2.2%
리 1310
 
2.0%
아 1224
 
1.9%
대 1164
 
1.8%
트 1163
 
1.8%
장 1046
 
1.6%
Other values (527) 49957
77.1%
None
ValueCountFrequency (%)
㈜ 22
100.0%
Arrows
ValueCountFrequency (%)
→ 3
100.0%
Compat Jamo
ValueCountFrequency (%)
ㅡ 3
100.0%

경도
Real number (ℝ)

HIGH CORRELATION 

Distinct9967
Distinct (%)99.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean129.05578
Minimum128.80932
Maximum129.29284
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2023-12-11T02:03:29.756225image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum128.80932
5-th percentile128.87083
Q1128.99584
median129.0652
Q3129.11335
95-th percentile129.21764
Maximum129.29284
Range0.483514
Interquartile range (IQR)0.11751438

Descriptive statistics

Standard deviation0.096390108
Coefficient of variation (CV)0.00074688716
Kurtosis-0.0738656
Mean129.05578
Median Absolute Deviation (MAD)0.0557527
Skewness-0.22546757
Sum1290557.8
Variance0.009291053
MonotonicityNot monotonic
2023-12-11T02:03:30.012967image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
128.8508481 2
 
< 0.1%
129.03281 2
 
< 0.1%
129.1836621 2
 
< 0.1%
128.8783342 2
 
< 0.1%
129.0170614 2
 
< 0.1%
129.088479 2
 
< 0.1%
129.0650893 2
 
< 0.1%
129.1171639 2
 
< 0.1%
129.1276 2
 
< 0.1%
129.1904332 2
 
< 0.1%
Other values (9957) 9980
99.8%
ValueCountFrequency (%)
128.8093211 1
< 0.1%
128.8093692 1
< 0.1%
128.8111164 1
< 0.1%
128.8113438 1
< 0.1%
128.8115858 1
< 0.1%
128.8117166 1
< 0.1%
128.8149083 1
< 0.1%
128.8151547 1
< 0.1%
128.8178918 1
< 0.1%
128.8179984 1
< 0.1%
ValueCountFrequency (%)
129.2928351 1
< 0.1%
129.2926588 1
< 0.1%
129.2854058 1
< 0.1%
129.2853789 1
< 0.1%
129.2849897 1
< 0.1%
129.2849347 1
< 0.1%
129.2848997 1
< 0.1%
129.2848706 1
< 0.1%
129.2848329 1
< 0.1%
129.2840086 1
< 0.1%

위도
Real number (ℝ)

HIGH CORRELATION 

Distinct9999
Distinct (%)> 99.9%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean35.170506
Minimum35.032442
Maximum35.385058
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2023-12-11T02:03:30.288131image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum35.032442
5-th percentile35.081174
Q135.1195
median35.165475
Q335.205661
95-th percentile35.320606
Maximum35.385058
Range0.35261548
Interquartile range (IQR)0.08616041

Descriptive statistics

Standard deviation0.065862251
Coefficient of variation (CV)0.0018726558
Kurtosis0.35704884
Mean35.170506
Median Absolute Deviation (MAD)0.042589045
Skewness0.70185629
Sum351705.06
Variance0.0043378361
MonotonicityNot monotonic
2023-12-11T02:03:30.600706image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
35.23991722 2
 
< 0.1%
35.12873204 1
 
< 0.1%
35.04832256 1
 
< 0.1%
35.18694217 1
 
< 0.1%
35.20026834 1
 
< 0.1%
35.13968744 1
 
< 0.1%
35.17663592 1
 
< 0.1%
35.24527048 1
 
< 0.1%
35.08182301 1
 
< 0.1%
35.2499894 1
 
< 0.1%
Other values (9989) 9989
99.9%
ValueCountFrequency (%)
35.03244248 1
< 0.1%
35.03275742 1
< 0.1%
35.03299073 1
< 0.1%
35.04757071 1
< 0.1%
35.04772653 1
< 0.1%
35.04773981 1
< 0.1%
35.04776375 1
< 0.1%
35.04780049 1
< 0.1%
35.04793953 1
< 0.1%
35.04829652 1
< 0.1%
ValueCountFrequency (%)
35.38505796 1
< 0.1%
35.38473336 1
< 0.1%
35.3763698 1
< 0.1%
35.37456187 1
< 0.1%
35.37449931 1
< 0.1%
35.37446211 1
< 0.1%
35.37445312 1
< 0.1%
35.37435713 1
< 0.1%
35.37434901 1
< 0.1%
35.37434451 1
< 0.1%

Interactions

2023-12-11T02:03:23.837298image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T02:03:22.894614image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T02:03:23.346544image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T02:03:23.994176image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T02:03:23.060408image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T02:03:23.480051image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T02:03:24.172307image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T02:03:23.201246image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T02:03:23.636342image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-11T02:03:31.191349image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
번호시군구명리명경도위도
번호1.0000.6760.7300.5790.481
시군구명0.6761.0000.6850.8950.853
리명0.7300.6851.0000.9940.994
경도0.5790.8950.9941.0000.769
위도0.4810.8530.9940.7691.000
2023-12-11T02:03:31.374471image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
번호경도위도시군구명
번호1.000-0.0100.0680.342
경도-0.0101.0000.5860.634
위도0.0680.5861.0000.553
시군구명0.3420.6340.5531.000

Missing values

2023-12-11T02:03:24.362068image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-11T02:03:24.576155image/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.
2023-12-11T02:03:24.742349image/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

번호시군구명동명리명도로명교차로명경도위도
92499250강서구구랑동<NA><NA>미음지구1공구-3지점128.85401335.128732
49744975강서구죽림동<NA>가락대로 1405가락중학교128.90439235.189371
35173518기장군일광면화전리<NA>부산은행연수원 진입로129.23300635.27596
28992900서구동대신동2가<NA><NA>대신로타리129.01902335.11052
72497250해운대구재송동<NA><NA>재송유치원 진입로129.12646235.182987
88238824금정구장전동<NA>수림로62번길 9제일김약국129.08642635.239784
88568857동래구온천동<NA>온천장로 123온천장소방서(허브스카이)129.08510535.222184
99989999수영구광안동<NA>수영로 709-1수영 BBQ 앞129.11787235.167525
57395740사하구감천동<NA><NA>감천한전사택128.99558835.091476
55695570사하구신평동<NA><NA>군부대(예비군훈련장)128.97701835.094929
번호시군구명동명리명도로명교차로명경도위도
64416442기장군일광면원리<NA>월드컵 빌리지(1)129.23962935.302681
1158511586기장군장안읍장안리<NA>명례일반산업단지 1번신호등129.25439435.367255
39413942기장군철마면와여리<NA>철마어린이집129.15025435.275765
88748875해운대구중동<NA><NA>좌동지하차도129.16747135.167206
10841085북구화명동<NA>화명신도시로 127화명10지점129.00973835.236009
91839184강서구미음동<NA>미음산단로 388미음지구2공구-7지점128.8602935.157262
1084310844부산진구연지동<NA><NA>정묘사앞삼거리129.06120835.174209
64286429기장군정관읍매학리<NA>진짜순대 앞129.17866335.322647
96479648남구용당동<NA><NA>동명정보대학129.09926435.12323
99759976서구남부민동<NA>충무대로 150모피고냉장129.02488635.084572