Overview

Dataset statistics

Number of variables9
Number of observations235
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory17.1 KiB
Average record size in memory74.6 B

Variable types

Categorical4
Text2
Numeric2
DateTime1

Dataset

Description경기도 안산시 내 노선별 가로수 현황입니다.노선명, 노선 구간, 구간 길이, 수종 및 가로수본수 등 데이터를 포함하고 있습니다.
Author경기도 안산시
URLhttps://www.data.go.kr/data/15124349/fileData.do

Alerts

시군명 has constant value ""Constant
데이터기준일 has constant value ""Constant
행정동 is highly overall correlated with 비고High correlation
수종 is highly overall correlated with 비고High correlation
비고 is highly overall correlated with 행정동 and 1 other fieldsHigh correlation
비고 is highly imbalanced (80.3%)Imbalance

Reproduction

Analysis started2023-12-11 23:39:06.629184
Analysis finished2023-12-11 23:39:07.649547
Duration1.02 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

시군명
Categorical

CONSTANT 

Distinct1
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size2.0 KiB
안산시
235 

Length

Max length3
Median length3
Mean length3
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
안산시 235
100.0%

Length

2023-12-12T08:39:07.710542image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T08:39:07.795136image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
안산시 235
100.0%

노선명
Text

Distinct120
Distinct (%)51.1%
Missing0
Missing (%)0.0%
Memory size2.0 KiB
2023-12-12T08:39:08.027478image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length7
Median length6
Mean length3.8382979
Min length3

Characters and Unicode

Total characters902
Distinct characters116
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

Unique67 ?
Unique (%)28.5%

Sample

1st row가루개로
2nd row각골동로
3rd row각골로
4th row각골로
5th row각골로
ValueCountFrequency (%)
수인로 12
 
5.1%
충장로 10
 
4.3%
항가울로 9
 
3.8%
석호로 6
 
2.6%
광덕4로 5
 
2.1%
성호로 5
 
2.1%
반석로 5
 
2.1%
안산천동로 5
 
2.1%
해안로 5
 
2.1%
장하로 4
 
1.7%
Other values (110) 169
71.9%
2023-12-12T08:39:08.507789image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
로 216
23.9%
길 30
 
3.3%
1 27
 
3.0%
안 25
 
2.8%
장 22
 
2.4%
산 22
 
2.4%
광 21
 
2.3%
호 20
 
2.2%
양 17
 
1.9%
골 17
 
1.9%
Other values (106) 485
53.8%

Most occurring categories

ValueCountFrequency (%)
Other Letter 847
93.9%
Decimal Number 55
 
6.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
로 216
25.5%
길 30
 
3.5%
안 25
 
3.0%
장 22
 
2.6%
산 22
 
2.6%
광 21
 
2.5%
호 20
 
2.4%
양 17
 
2.0%
골 17
 
2.0%
덕 17
 
2.0%
Other values (99) 440
51.9%
Decimal Number
ValueCountFrequency (%)
1 27
49.1%
4 10
 
18.2%
3 8
 
14.5%
2 6
 
10.9%
5 2
 
3.6%
8 1
 
1.8%
7 1
 
1.8%

Most occurring scripts

ValueCountFrequency (%)
Hangul 847
93.9%
Common 55
 
6.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
로 216
25.5%
길 30
 
3.5%
안 25
 
3.0%
장 22
 
2.6%
산 22
 
2.6%
광 21
 
2.5%
호 20
 
2.4%
양 17
 
2.0%
골 17
 
2.0%
덕 17
 
2.0%
Other values (99) 440
51.9%
Common
ValueCountFrequency (%)
1 27
49.1%
4 10
 
18.2%
3 8
 
14.5%
2 6
 
10.9%
5 2
 
3.6%
8 1
 
1.8%
7 1
 
1.8%

Most occurring blocks

ValueCountFrequency (%)
Hangul 847
93.9%
ASCII 55
 
6.1%

Most frequent character per block

Hangul
ValueCountFrequency (%)
로 216
25.5%
길 30
 
3.5%
안 25
 
3.0%
장 22
 
2.6%
산 22
 
2.6%
광 21
 
2.5%
호 20
 
2.4%
양 17
 
2.0%
골 17
 
2.0%
덕 17
 
2.0%
Other values (99) 440
51.9%
ASCII
ValueCountFrequency (%)
1 27
49.1%
4 10
 
18.2%
3 8
 
14.5%
2 6
 
10.9%
5 2
 
3.6%
8 1
 
1.8%
7 1
 
1.8%

행정동
Categorical

HIGH CORRELATION 

Distinct14
Distinct (%)6.0%
Missing0
Missing (%)0.0%
Memory size2.0 KiB
이동
35 
월피동
29 
사동
26 
해양동
23 
성포동
21 
Other values (9)
101 

Length

Max length4
Median length3
Mean length2.8680851
Min length2

Unique

Unique1 ?
Unique (%)0.4%

Sample

1st row월피동
2nd row본오2동
3rd row본오1동
4th row본오2동
5th row본오3동

Common Values

ValueCountFrequency (%)
이동 35
14.9%
월피동 29
12.3%
사동 26
11.1%
해양동 23
9.8%
성포동 21
8.9%
본오1동 19
8.1%
부곡동 19
8.1%
본오2동 14
 
6.0%
사이동 13
 
5.5%
일동 12
 
5.1%
Other values (4) 24
10.2%

Length

2023-12-12T08:39:08.690053image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
이동 35
14.9%
월피동 29
12.3%
사동 26
11.1%
해양동 23
9.8%
성포동 21
8.9%
본오1동 19
8.1%
부곡동 19
8.1%
본오2동 14
 
6.0%
사이동 13
 
5.5%
일동 12
 
5.1%
Other values (4) 24
10.2%

구간
Text

Distinct120
Distinct (%)51.1%
Missing0
Missing (%)0.0%
Memory size2.0 KiB
2023-12-12T08:39:08.963753image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length23
Median length21
Mean length19.510638
Min length7

Characters and Unicode

Total characters4585
Distinct characters64
Distinct categories5 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique67 ?
Unique (%)28.5%

Sample

1st row양상동 산60-3 ~ 월피동 213
2nd row본오동 729-7 ~ 본오동 745
3rd row본오동 1118-8 ~ 각골사거리
4th row본오동 1118-8 ~ 각골사거리
5th row본오동 1118-8 ~ 각골사거리
ValueCountFrequency (%)
233
20.3%
사동 108
 
9.4%
본오동 71
 
6.2%
이동 58
 
5.0%
월피동 48
 
4.2%
성포동 35
 
3.0%
부곡동 34
 
3.0%
일동 25
 
2.2%
수암동 19
 
1.7%
사사동 14
 
1.2%
Other values (236) 505
43.9%
2023-12-12T08:39:09.677161image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
916
20.0%
동 449
 
9.8%
1 357
 
7.8%
- 293
 
6.4%
~ 233
 
5.1%
6 206
 
4.5%
5 203
 
4.4%
4 183
 
4.0%
3 181
 
3.9%
7 170
 
3.7%
Other values (54) 1394
30.4%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 1840
40.1%
Other Letter 1303
28.4%
Space Separator 916
20.0%
Dash Punctuation 293
 
6.4%
Math Symbol 233
 
5.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
동 449
34.5%
사 148
 
11.4%
오 81
 
6.2%
본 71
 
5.4%
이 59
 
4.5%
피 48
 
3.7%
월 48
 
3.7%
곡 42
 
3.2%
포 36
 
2.8%
부 36
 
2.8%
Other values (41) 285
21.9%
Decimal Number
ValueCountFrequency (%)
1 357
19.4%
6 206
11.2%
5 203
11.0%
4 183
9.9%
3 181
9.8%
7 170
9.2%
9 164
8.9%
2 144
7.8%
8 122
 
6.6%
0 110
 
6.0%
Space Separator
ValueCountFrequency (%)
916
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 293
100.0%
Math Symbol
ValueCountFrequency (%)
~ 233
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 3282
71.6%
Hangul 1303
 
28.4%

Most frequent character per script

Hangul
ValueCountFrequency (%)
동 449
34.5%
사 148
 
11.4%
오 81
 
6.2%
본 71
 
5.4%
이 59
 
4.5%
피 48
 
3.7%
월 48
 
3.7%
곡 42
 
3.2%
포 36
 
2.8%
부 36
 
2.8%
Other values (41) 285
21.9%
Common
ValueCountFrequency (%)
916
27.9%
1 357
 
10.9%
- 293
 
8.9%
~ 233
 
7.1%
6 206
 
6.3%
5 203
 
6.2%
4 183
 
5.6%
3 181
 
5.5%
7 170
 
5.2%
9 164
 
5.0%
Other values (3) 376
11.5%

Most occurring blocks

ValueCountFrequency (%)
ASCII 3282
71.6%
Hangul 1303
 
28.4%

Most frequent character per block

ASCII
ValueCountFrequency (%)
916
27.9%
1 357
 
10.9%
- 293
 
8.9%
~ 233
 
7.1%
6 206
 
6.3%
5 203
 
6.2%
4 183
 
5.6%
3 181
 
5.5%
7 170
 
5.2%
9 164
 
5.0%
Other values (3) 376
11.5%
Hangul
ValueCountFrequency (%)
동 449
34.5%
사 148
 
11.4%
오 81
 
6.2%
본 71
 
5.4%
이 59
 
4.5%
피 48
 
3.7%
월 48
 
3.7%
곡 42
 
3.2%
포 36
 
2.8%
부 36
 
2.8%
Other values (41) 285
21.9%

구간길이
Real number (ℝ)

Distinct101
Distinct (%)43.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2262.9149
Minimum150
Maximum10062
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size2.2 KiB
2023-12-12T08:39:09.834844image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum150
5-th percentile240
Q1576
median1260
Q33095
95-th percentile7651
Maximum10062
Range9912
Interquartile range (IQR)2519

Descriptive statistics

Standard deviation2405.3192
Coefficient of variation (CV)1.0629296
Kurtosis1.5026384
Mean2262.9149
Median Absolute Deviation (MAD)860
Skewness1.5127651
Sum531785
Variance5785560.6
MonotonicityNot monotonic
2023-12-12T08:39:09.978036image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
7651 12
 
5.1%
6780 10
 
4.3%
5060 9
 
3.8%
4210 6
 
2.6%
300 5
 
2.1%
3820 5
 
2.1%
3095 5
 
2.1%
10062 5
 
2.1%
2130 5
 
2.1%
2860 5
 
2.1%
Other values (91) 168
71.5%
ValueCountFrequency (%)
150 2
0.9%
168 1
 
0.4%
180 2
0.9%
190 3
1.3%
200 2
0.9%
205 1
 
0.4%
240 2
0.9%
250 1
 
0.4%
253 1
 
0.4%
270 1
 
0.4%
ValueCountFrequency (%)
10062 5
2.1%
7651 12
5.1%
6780 10
4.3%
5060 9
3.8%
4820 3
 
1.3%
4210 6
2.6%
3820 5
2.1%
3360 4
 
1.7%
3350 4
 
1.7%
3095 5
2.1%

수종
Categorical

HIGH CORRELATION 

Distinct16
Distinct (%)6.8%
Missing0
Missing (%)0.0%
Memory size2.0 KiB
은행나무
53 
이팝나무
33 
중국단풍
33 
느티나무
29 
벚나무
26 
Other values (11)
61 

Length

Max length6
Median length4
Mean length3.7914894
Min length3

Unique

Unique3 ?
Unique (%)1.3%

Sample

1st row소나무
2nd row단풍나무
3rd row목백합
4th row목백합
5th row목백합

Common Values

ValueCountFrequency (%)
은행나무 53
22.6%
이팝나무 33
14.0%
중국단풍 33
14.0%
느티나무 29
12.3%
벚나무 26
11.1%
목백합 21
 
8.9%
단풍나무 11
 
4.7%
버즘나무 7
 
3.0%
소나무 5
 
2.1%
계수나무 5
 
2.1%
Other values (6) 12
 
5.1%

Length

2023-12-12T08:39:10.148292image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
은행나무 53
22.6%
이팝나무 33
14.0%
중국단풍 33
14.0%
느티나무 29
12.3%
벚나무 26
11.1%
목백합 21
 
8.9%
단풍나무 11
 
4.7%
버즘나무 7
 
3.0%
소나무 5
 
2.1%
계수나무 5
 
2.1%
Other values (6) 12
 
5.1%

가로수본수
Real number (ℝ)

Distinct139
Distinct (%)59.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean91.880851
Minimum2
Maximum670
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size2.2 KiB
2023-12-12T08:39:10.290241image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum2
5-th percentile11.7
Q137.5
median69
Q3121
95-th percentile244.1
Maximum670
Range668
Interquartile range (IQR)83.5

Descriptive statistics

Standard deviation84.808297
Coefficient of variation (CV)0.92302472
Kurtosis11.485086
Mean91.880851
Median Absolute Deviation (MAD)41
Skewness2.6610072
Sum21592
Variance7192.4473
MonotonicityNot monotonic
2023-12-12T08:39:10.454485image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
27 6
 
2.6%
54 5
 
2.1%
44 5
 
2.1%
88 4
 
1.7%
25 4
 
1.7%
12 4
 
1.7%
45 4
 
1.7%
60 3
 
1.3%
66 3
 
1.3%
41 3
 
1.3%
Other values (129) 194
82.6%
ValueCountFrequency (%)
2 1
 
0.4%
4 1
 
0.4%
6 2
0.9%
7 1
 
0.4%
9 3
1.3%
10 2
0.9%
11 2
0.9%
12 4
1.7%
13 1
 
0.4%
14 2
0.9%
ValueCountFrequency (%)
670 1
0.4%
453 1
0.4%
449 1
0.4%
379 1
0.4%
373 1
0.4%
313 1
0.4%
300 1
0.4%
280 1
0.4%
272 1
0.4%
258 1
0.4%

비고
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct3
Distinct (%)1.3%
Missing0
Missing (%)0.0%
Memory size2.0 KiB
<NA>
223 
중앙분리대
 
11
조형섬잣나무
 
1

Length

Max length6
Median length4
Mean length4.0553191
Min length4

Unique

Unique1 ?
Unique (%)0.4%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 223
94.9%
중앙분리대 11
 
4.7%
조형섬잣나무 1
 
0.4%

Length

2023-12-12T08:39:10.605230image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T08:39:10.720590image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 223
94.9%
중앙분리대 11
 
4.7%
조형섬잣나무 1
 
0.4%

데이터기준일
Date

CONSTANT 

Distinct1
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size2.0 KiB
Minimum2023-10-10 00:00:00
Maximum2023-10-10 00:00:00
2023-12-12T08:39:10.845846image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:39:10.984502image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=1)

Interactions

2023-12-12T08:39:07.204597image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:39:06.970725image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:39:07.320332image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:39:07.083933image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-12T08:39:11.101380image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
행정동구간길이수종가로수본수비고
행정동1.0000.3850.6410.0601.000
구간길이0.3851.0000.5430.6830.262
수종0.6410.5431.0000.3641.000
가로수본수0.0600.6830.3641.0000.000
비고1.0000.2621.0000.0001.000
2023-12-12T08:39:11.267252image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
행정동수종비고
행정동1.0000.2780.707
수종0.2781.0000.894
비고0.7070.8941.000
2023-12-12T08:39:11.390898image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
구간길이가로수본수행정동수종비고
구간길이1.0000.4360.1790.2140.000
가로수본수0.4361.0000.0210.1320.000
행정동0.1790.0211.0000.2780.707
수종0.2140.1320.2781.0000.894
비고0.0000.0000.7070.8941.000

Missing values

2023-12-12T08:39:07.471651image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-12T08:39:07.596565image/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

시군명노선명행정동구간구간길이수종가로수본수비고데이터기준일
0안산시가루개로월피동양상동 산60-3 ~ 월피동 2132050소나무186<NA>2023-10-10
1안산시각골동로본오2동본오동 729-7 ~ 본오동 745600단풍나무72<NA>2023-10-10
2안산시각골로본오1동본오동 1118-8 ~ 각골사거리1360목백합14<NA>2023-10-10
3안산시각골로본오2동본오동 1118-8 ~ 각골사거리1360목백합59<NA>2023-10-10
4안산시각골로본오3동본오동 1118-8 ~ 각골사거리1360목백합47<NA>2023-10-10
5안산시각골서로본오1동본오동 815-7 ~ 본오동 850-12717목백합9<NA>2023-10-10
6안산시각골서로본오1동본오동 815-7 ~ 본오동 850-12717이팝나무25<NA>2023-10-10
7안산시각골서로본오2동본오동 815-7 ~ 본오동 850-12717목백합17<NA>2023-10-10
8안산시각골서로본오2동본오동 815-7 ~ 본오동 850-12717이팝나무18<NA>2023-10-10
9안산시감골1로사이동용신2교 ~ 사동 1346762느티나무20<NA>2023-10-10
시군명노선명행정동구간구간길이수종가로수본수비고데이터기준일
225안산시해양4로해양동사동 1639-2 ~ 사동 1639-46399이팝나무79<NA>2023-10-10
226안산시해양5로해양동해양중학교 ~ 해양초등학교 안길383이팝나무79<NA>2023-10-10
227안산시해양로해양동사동 1642346회화나무50<NA>2023-10-10
228안산시호동로일동일동 600-7 ~ 일동 551-81200은행나무104<NA>2023-10-10
229안산시호동로일동일동 600-7 ~ 일동 551-81200중국단풍81<NA>2023-10-10
230안산시화랑로성포동성포동 679-14 ~ 성포동 585-1716느티나무44<NA>2023-10-10
231안산시화랑로성포동성포동 679-14 ~ 성포동 585-1716계수나무57<NA>2023-10-10
232안산시후곡로사동사동 1305-9 ~ 사동 1275916느티나무54<NA>2023-10-10
233안산시후곡로사동사동 1305-9 ~ 사동 1275916이팝나무88<NA>2023-10-10
234안산시안산테콤단지반월동사사동 119-40 ~ 사사동 119-58205벚나무41<NA>2023-10-10