Overview

Dataset statistics

Number of variables33
Number of observations9212
Missing cells9084
Missing cells (%)3.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory2.4 MiB
Average record size in memory271.0 B

Variable types

Text10
Categorical12
DateTime1
Numeric7
Boolean3

Dataset

Description서울특별시 동대문구 관내에 식재된 수목의 위경도 및 주소, 흉고직경, 근원직경, 식재간격, 수령 등의 정보를 제공합니다.
Author서울특별시 동대문구
URLhttps://www.data.go.kr/data/15109347/fileData.do

Alerts

수목구분 has constant value ""Constant
수목유형 has constant value ""Constant
관리기관전화번호 has constant value ""Constant
관리기관명 has constant value ""Constant
데이터기준일자 has constant value ""Constant
도로종류 has constant value ""Constant
수목명 is highly imbalanced (53.1%)Imbalance
보호틀파손여부 is highly imbalanced (89.8%)Imbalance
뿌리융기여부 is highly imbalanced (78.4%)Imbalance
통기 is highly imbalanced (93.0%)Imbalance
지장물2 is highly imbalanced (65.7%)Imbalance
도로명주소 has 8789 (95.4%) missing valuesMissing
보도폭 has 246 (2.7%) missing valuesMissing
관리번호 has unique valuesUnique
수목전경사진 has unique valuesUnique
보호덮개사진 has unique valuesUnique

Reproduction

Analysis started2023-12-12 21:20:48.202227
Analysis finished2023-12-12 21:20:49.685374
Duration1.48 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

관리번호
Text

UNIQUE 

Distinct9212
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size72.1 KiB
2023-12-13T06:20:49.844919image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length19
Median length17
Mean length14.09162
Min length13

Characters and Unicode

Total characters129812
Distinct characters71
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique9212 ?
Unique (%)100.0%

Sample

1st row06-천호대로-가-0484
2nd row06-외대역동로-가-0141
3rd row06-제기로17길-가-0003
4th row06-천호대로-가-0339
5th row06-답십리로-가-0017
ValueCountFrequency (%)
06-천호대로-가-0484 1
 
< 0.1%
06-청계천로-가-0188 1
 
< 0.1%
06-무학로-가-0013 1
 
< 0.1%
06-고산자로-가-0226 1
 
< 0.1%
06-장안벚꽃로-가-0488 1
 
< 0.1%
06-황물로-가-0247 1
 
< 0.1%
06-한천로-가-0549 1
 
< 0.1%
06-이문로-가-0103 1
 
< 0.1%
06-황물로-가-0294 1
 
< 0.1%
06-한천로-가-0513 1
 
< 0.1%
Other values (9202) 9202
99.9%
2023-12-13T06:20:50.156975image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
- 27636
21.3%
0 24673
19.0%
6 11136
 
8.6%
9662
 
7.4%
9212
 
7.1%
1 5042
 
3.9%
2 3894
 
3.0%
3 2978
 
2.3%
4 2538
 
2.0%
5 2515
 
1.9%
Other values (61) 30526
23.5%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 58116
44.8%
Other Letter 44060
33.9%
Dash Punctuation 27636
21.3%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
9662
21.9%
9212
20.9%
2249
 
5.1%
1545
 
3.5%
1516
 
3.4%
1278
 
2.9%
919
 
2.1%
765
 
1.7%
740
 
1.7%
680
 
1.5%
Other values (50) 15494
35.2%
Decimal Number
ValueCountFrequency (%)
0 24673
42.5%
6 11136
19.2%
1 5042
 
8.7%
2 3894
 
6.7%
3 2978
 
5.1%
4 2538
 
4.4%
5 2515
 
4.3%
7 1895
 
3.3%
8 1857
 
3.2%
9 1588
 
2.7%
Dash Punctuation
ValueCountFrequency (%)
- 27636
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 85752
66.1%
Hangul 44060
33.9%

Most frequent character per script

Hangul
ValueCountFrequency (%)
9662
21.9%
9212
20.9%
2249
 
5.1%
1545
 
3.5%
1516
 
3.4%
1278
 
2.9%
919
 
2.1%
765
 
1.7%
740
 
1.7%
680
 
1.5%
Other values (50) 15494
35.2%
Common
ValueCountFrequency (%)
- 27636
32.2%
0 24673
28.8%
6 11136
13.0%
1 5042
 
5.9%
2 3894
 
4.5%
3 2978
 
3.5%
4 2538
 
3.0%
5 2515
 
2.9%
7 1895
 
2.2%
8 1857
 
2.2%

Most occurring blocks

ValueCountFrequency (%)
ASCII 85752
66.1%
Hangul 44060
33.9%

Most frequent character per block

ASCII
ValueCountFrequency (%)
- 27636
32.2%
0 24673
28.8%
6 11136
13.0%
1 5042
 
5.9%
2 3894
 
4.5%
3 2978
 
3.5%
4 2538
 
3.0%
5 2515
 
2.9%
7 1895
 
2.2%
8 1857
 
2.2%
Hangul
ValueCountFrequency (%)
9662
21.9%
9212
20.9%
2249
 
5.1%
1545
 
3.5%
1516
 
3.4%
1278
 
2.9%
919
 
2.1%
765
 
1.7%
740
 
1.7%
680
 
1.5%
Other values (50) 15494
35.2%

수목명
Categorical

IMBALANCE 

Distinct29
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size72.1 KiB
은행나무
3665 
양버즘나무
2582 
이팝나무
1560 
느티나무
666 
벚나무
 
312
Other values (24)
427 

Length

Max length6
Median length4
Mean length4.2508684
Min length3

Unique

Unique8 ?
Unique (%)0.1%

Sample

1st row양버즘나무
2nd row양버즘나무
3rd row은행나무
4th row양버즘나무
5th row양버즘나무

Common Values

ValueCountFrequency (%)
은행나무 3665
39.8%
양버즘나무 2582
28.0%
이팝나무 1560
16.9%
느티나무 666
 
7.2%
벚나무 312
 
3.4%
회화나무 127
 
1.4%
메타세쿼이아 57
 
0.6%
단풍나무 51
 
0.6%
감나무 33
 
0.4%
산딸나무 30
 
0.3%
Other values (19) 129
 
1.4%

Length

2023-12-13T06:20:50.311390image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
은행나무 3665
39.8%
양버즘나무 2582
28.0%
이팝나무 1560
16.9%
느티나무 666
 
7.2%
벚나무 312
 
3.4%
회화나무 127
 
1.4%
메타세쿼이아 57
 
0.6%
단풍나무 51
 
0.6%
감나무 33
 
0.4%
산딸나무 30
 
0.3%
Other values (19) 129
 
1.4%

수목구분
Categorical

CONSTANT 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size72.1 KiB
가로수
9212 

Length

Max length3
Median length3
Mean length3
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
가로수 9212
100.0%

Length

2023-12-13T06:20:50.432397image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T06:20:50.506955image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
가로수 9212
100.0%

수목유형
Categorical

CONSTANT 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size72.1 KiB
교목
9212 

Length

Max length2
Median length2
Mean length2
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
교목 9212
100.0%

Length

2023-12-13T06:20:50.590157image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T06:20:50.665617image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
교목 9212
100.0%
Distinct76
Distinct (%)0.8%
Missing0
Missing (%)0.0%
Memory size72.1 KiB
Minimum1947-04-04 00:00:00
Maximum2022-04-05 00:00:00
2023-12-13T06:20:50.753010image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T06:20:50.880270image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

관리기관전화번호
Categorical

CONSTANT 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size72.1 KiB
02-2127-4319
9212 

Length

Max length12
Median length12
Mean length12
Min length12

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row02-2127-4319
2nd row02-2127-4319
3rd row02-2127-4319
4th row02-2127-4319
5th row02-2127-4319

Common Values

ValueCountFrequency (%)
02-2127-4319 9212
100.0%

Length

2023-12-13T06:20:50.988159image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T06:20:51.068441image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
02-2127-4319 9212
100.0%

관리기관명
Categorical

CONSTANT 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size72.1 KiB
서울특별시 동대문구청
9212 

Length

Max length11
Median length11
Mean length11
Min length11

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row서울특별시 동대문구청
2nd row서울특별시 동대문구청
3rd row서울특별시 동대문구청
4th row서울특별시 동대문구청
5th row서울특별시 동대문구청

Common Values

ValueCountFrequency (%)
서울특별시 동대문구청 9212
100.0%

Length

2023-12-13T06:20:51.148246image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T06:20:51.233383image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
서울특별시 9212
50.0%
동대문구청 9212
50.0%

데이터기준일자
Categorical

CONSTANT 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size72.1 KiB
2022-12-12
9212 

Length

Max length10
Median length10
Mean length10
Min length10

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2022-12-12
2nd row2022-12-12
3rd row2022-12-12
4th row2022-12-12
5th row2022-12-12

Common Values

ValueCountFrequency (%)
2022-12-12 9212
100.0%

Length

2023-12-13T06:20:51.326968image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T06:20:51.401727image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2022-12-12 9212
100.0%
Distinct66
Distinct (%)0.7%
Missing0
Missing (%)0.0%
Memory size72.1 KiB
2023-12-13T06:20:51.605190image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length9
Median length7
Mean length4.0916196
Min length3

Characters and Unicode

Total characters37692
Distinct characters70
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

Unique2 ?
Unique (%)< 0.1%

Sample

1st row천호대로
2nd row외대역동로
3rd row제기로17길
4th row천호대로
5th row답십리로
ValueCountFrequency (%)
한천로 697
 
7.6%
천호대로 549
 
6.0%
장안벚꽃로 530
 
5.8%
답십리로 461
 
5.0%
왕산로 416
 
4.5%
전농로 394
 
4.3%
사가정로 387
 
4.2%
회기로 363
 
3.9%
황물로 354
 
3.8%
이문로 330
 
3.6%
Other values (56) 4731
51.4%
2023-12-13T06:20:51.967455image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
9212
24.4%
2249
 
6.0%
1545
 
4.1%
1516
 
4.0%
1278
 
3.4%
919
 
2.4%
765
 
2.0%
740
 
2.0%
680
 
1.8%
680
 
1.8%
Other values (60) 18108
48.0%

Most occurring categories

ValueCountFrequency (%)
Other Letter 34848
92.5%
Decimal Number 2844
 
7.5%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
9212
26.4%
2249
 
6.5%
1545
 
4.4%
1516
 
4.4%
1278
 
3.7%
919
 
2.6%
765
 
2.2%
740
 
2.1%
680
 
2.0%
680
 
2.0%
Other values (50) 15264
43.8%
Decimal Number
ValueCountFrequency (%)
1 594
20.9%
5 534
18.8%
2 388
13.6%
4 290
10.2%
0 247
8.7%
8 245
8.6%
3 226
 
7.9%
7 198
 
7.0%
6 87
 
3.1%
9 35
 
1.2%

Most occurring scripts

ValueCountFrequency (%)
Hangul 34848
92.5%
Common 2844
 
7.5%

Most frequent character per script

Hangul
ValueCountFrequency (%)
9212
26.4%
2249
 
6.5%
1545
 
4.4%
1516
 
4.4%
1278
 
3.7%
919
 
2.6%
765
 
2.2%
740
 
2.1%
680
 
2.0%
680
 
2.0%
Other values (50) 15264
43.8%
Common
ValueCountFrequency (%)
1 594
20.9%
5 534
18.8%
2 388
13.6%
4 290
10.2%
0 247
8.7%
8 245
8.6%
3 226
 
7.9%
7 198
 
7.0%
6 87
 
3.1%
9 35
 
1.2%

Most occurring blocks

ValueCountFrequency (%)
Hangul 34848
92.5%
ASCII 2844
 
7.5%

Most frequent character per block

Hangul
ValueCountFrequency (%)
9212
26.4%
2249
 
6.5%
1545
 
4.4%
1516
 
4.4%
1278
 
3.7%
919
 
2.6%
765
 
2.2%
740
 
2.1%
680
 
2.0%
680
 
2.0%
Other values (50) 15264
43.8%
ASCII
ValueCountFrequency (%)
1 594
20.9%
5 534
18.8%
2 388
13.6%
4 290
10.2%
0 247
8.7%
8 245
8.6%
3 226
 
7.9%
7 198
 
7.0%
6 87
 
3.1%
9 35
 
1.2%

도로종류
Categorical

CONSTANT 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size72.1 KiB
특별시도
9212 

Length

Max length4
Median length4
Mean length4
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
특별시도 9212
100.0%

Length

2023-12-13T06:20:52.088591image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T06:20:52.158617image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
특별시도 9212
100.0%
Distinct65
Distinct (%)0.7%
Missing0
Missing (%)0.0%
Memory size72.1 KiB
2023-12-13T06:20:52.347129image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length23
Median length22
Mean length20.39188
Min length18

Characters and Unicode

Total characters187850
Distinct characters40
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

Unique2 ?
Unique (%)< 0.1%

Sample

1st row서울특별시 동대문구 신설동 117-21
2nd row서울특별시 동대문구 휘경동 55-3
3rd row서울특별시 동대문구 청량리동 520-55
4th row서울특별시 동대문구 신설동 117-21
5th row서울특별시 동대문구 전농동 621-1
ValueCountFrequency (%)
서울특별시 9212
25.0%
동대문구 9212
25.0%
장안동 1671
 
4.5%
신설동 1517
 
4.1%
답십리동 1514
 
4.1%
전농동 965
 
2.6%
제기동 951
 
2.6%
용두동 935
 
2.5%
413-7 697
 
1.9%
464-1 565
 
1.5%
Other values (66) 9609
26.1%
2023-12-13T06:20:52.699829image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
27636
14.7%
18424
 
9.8%
1 9987
 
5.3%
9673
 
5.1%
9212
 
4.9%
9212
 
4.9%
9212
 
4.9%
9212
 
4.9%
9212
 
4.9%
9212
 
4.9%
Other values (30) 66858
35.6%

Most occurring categories

ValueCountFrequency (%)
Other Letter 112355
59.8%
Decimal Number 39461
 
21.0%
Space Separator 27636
 
14.7%
Dash Punctuation 8398
 
4.5%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
18424
16.4%
9673
8.6%
9212
8.2%
9212
8.2%
9212
8.2%
9212
8.2%
9212
8.2%
9212
8.2%
9212
8.2%
1811
 
1.6%
Other values (18) 17963
16.0%
Decimal Number
ValueCountFrequency (%)
1 9987
25.3%
4 5461
13.8%
6 4813
12.2%
2 4780
12.1%
5 3563
 
9.0%
3 3411
 
8.6%
7 2792
 
7.1%
9 2429
 
6.2%
0 1286
 
3.3%
8 939
 
2.4%
Space Separator
ValueCountFrequency (%)
27636
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 8398
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 112355
59.8%
Common 75495
40.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
18424
16.4%
9673
8.6%
9212
8.2%
9212
8.2%
9212
8.2%
9212
8.2%
9212
8.2%
9212
8.2%
9212
8.2%
1811
 
1.6%
Other values (18) 17963
16.0%
Common
ValueCountFrequency (%)
27636
36.6%
1 9987
 
13.2%
- 8398
 
11.1%
4 5461
 
7.2%
6 4813
 
6.4%
2 4780
 
6.3%
5 3563
 
4.7%
3 3411
 
4.5%
7 2792
 
3.7%
9 2429
 
3.2%
Other values (2) 2225
 
2.9%

Most occurring blocks

ValueCountFrequency (%)
Hangul 112355
59.8%
ASCII 75495
40.2%

Most frequent character per block

ASCII
ValueCountFrequency (%)
27636
36.6%
1 9987
 
13.2%
- 8398
 
11.1%
4 5461
 
7.2%
6 4813
 
6.4%
2 4780
 
6.3%
5 3563
 
4.7%
3 3411
 
4.5%
7 2792
 
3.7%
9 2429
 
3.2%
Other values (2) 2225
 
2.9%
Hangul
ValueCountFrequency (%)
18424
16.4%
9673
8.6%
9212
8.2%
9212
8.2%
9212
8.2%
9212
8.2%
9212
8.2%
9212
8.2%
9212
8.2%
1811
 
1.6%
Other values (18) 17963
16.0%
Distinct65
Distinct (%)0.7%
Missing0
Missing (%)0.0%
Memory size72.1 KiB
2023-12-13T06:20:52.927790image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length23
Median length22
Mean length20.46624
Min length16

Characters and Unicode

Total characters188535
Distinct characters44
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

Unique2 ?
Unique (%)< 0.1%

Sample

1st row서울특별시 동대문구 장안동 204-13
2nd row서울특별시 동대문구 이문동 101-37
3rd row서울특별시 동대문구 청량리동 205-293
4th row서울특별시 동대문구 장안동 204-13
5th row서울특별시 동대문구 장안동 333-2
ValueCountFrequency (%)
서울특별시 8825
23.9%
동대문구 8825
23.9%
휘경동 1753
 
4.8%
이문동 1577
 
4.3%
장안동 1454
 
3.9%
전농동 1266
 
3.4%
답십리동 838
 
2.3%
제기동 744
 
2.0%
209-13 697
 
1.9%
620-67 614
 
1.7%
Other values (71) 10296
27.9%
2023-12-13T06:20:53.282323image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
27677
 
14.7%
18037
 
9.6%
10402
 
5.5%
9212
 
4.9%
9212
 
4.9%
- 9006
 
4.8%
8825
 
4.7%
8825
 
4.7%
8825
 
4.7%
8825
 
4.7%
Other values (34) 69689
37.0%

Most occurring categories

ValueCountFrequency (%)
Other Letter 111360
59.1%
Decimal Number 40492
 
21.5%
Space Separator 27677
 
14.7%
Dash Punctuation 9006
 
4.8%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
18037
16.2%
10402
9.3%
9212
8.3%
9212
8.3%
8825
7.9%
8825
7.9%
8825
7.9%
8825
7.9%
8825
7.9%
2140
 
1.9%
Other values (22) 18232
16.4%
Decimal Number
ValueCountFrequency (%)
1 7859
19.4%
2 7054
17.4%
3 6537
16.1%
6 4158
10.3%
4 3465
8.6%
0 3066
 
7.6%
7 2792
 
6.9%
9 2611
 
6.4%
5 1764
 
4.4%
8 1186
 
2.9%
Space Separator
ValueCountFrequency (%)
27677
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 9006
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 111360
59.1%
Common 77175
40.9%

Most frequent character per script

Hangul
ValueCountFrequency (%)
18037
16.2%
10402
9.3%
9212
8.3%
9212
8.3%
8825
7.9%
8825
7.9%
8825
7.9%
8825
7.9%
8825
7.9%
2140
 
1.9%
Other values (22) 18232
16.4%
Common
ValueCountFrequency (%)
27677
35.9%
- 9006
 
11.7%
1 7859
 
10.2%
2 7054
 
9.1%
3 6537
 
8.5%
6 4158
 
5.4%
4 3465
 
4.5%
0 3066
 
4.0%
7 2792
 
3.6%
9 2611
 
3.4%
Other values (2) 2950
 
3.8%

Most occurring blocks

ValueCountFrequency (%)
Hangul 111360
59.1%
ASCII 77175
40.9%

Most frequent character per block

ASCII
ValueCountFrequency (%)
27677
35.9%
- 9006
 
11.7%
1 7859
 
10.2%
2 7054
 
9.1%
3 6537
 
8.5%
6 4158
 
5.4%
4 3465
 
4.5%
0 3066
 
4.0%
7 2792
 
3.6%
9 2611
 
3.4%
Other values (2) 2950
 
3.8%
Hangul
ValueCountFrequency (%)
18037
16.2%
10402
9.3%
9212
8.3%
9212
8.3%
8825
7.9%
8825
7.9%
8825
7.9%
8825
7.9%
8825
7.9%
2140
 
1.9%
Other values (22) 18232
16.4%
Distinct3423
Distinct (%)37.2%
Missing0
Missing (%)0.0%
Memory size72.1 KiB
2023-12-13T06:20:53.497415image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length27
Median length21
Mean length8.1728181
Min length2

Characters and Unicode

Total characters75288
Distinct characters791
Distinct categories9 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1784 ?
Unique (%)19.4%

Sample

1st row천호대로 47 앞
2nd row동양엔파트 앞
3rd row서일eng 앞
4th row신답역 앞 정류장 앞
5th row대한열쇠 앞
ValueCountFrequency (%)
6118
34.7%
454
 
2.6%
맞은편 342
 
1.9%
반대편 196
 
1.1%
정류장 152
 
0.9%
청계천 128
 
0.7%
산책로 118
 
0.7%
공사장 88
 
0.5%
단지 85
 
0.5%
레미안크레시티아파트 84
 
0.5%
Other values (3434) 9879
56.0%
2023-12-13T06:20:53.839202image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
8432
 
11.2%
6224
 
8.3%
2102
 
2.8%
1751
 
2.3%
1612
 
2.1%
1255
 
1.7%
1194
 
1.6%
1123
 
1.5%
962
 
1.3%
955
 
1.3%
Other values (781) 49678
66.0%

Most occurring categories

ValueCountFrequency (%)
Other Letter 63050
83.7%
Space Separator 8432
 
11.2%
Decimal Number 1864
 
2.5%
Uppercase Letter 1640
 
2.2%
Lowercase Letter 210
 
0.3%
Dash Punctuation 74
 
0.1%
Other Punctuation 16
 
< 0.1%
Close Punctuation 1
 
< 0.1%
Open Punctuation 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
6224
 
9.9%
2102
 
3.3%
1751
 
2.8%
1612
 
2.6%
1255
 
2.0%
1194
 
1.9%
1123
 
1.8%
962
 
1.5%
955
 
1.5%
914
 
1.4%
Other values (716) 44958
71.3%
Uppercase Letter
ValueCountFrequency (%)
K 278
17.0%
S 235
14.3%
C 175
10.7%
A 115
 
7.0%
G 107
 
6.5%
E 91
 
5.5%
B 83
 
5.1%
T 73
 
4.5%
O 66
 
4.0%
I 64
 
3.9%
Other values (15) 353
21.5%
Lowercase Letter
ValueCountFrequency (%)
o 25
11.9%
a 19
 
9.0%
d 16
 
7.6%
e 14
 
6.7%
w 14
 
6.7%
l 13
 
6.2%
m 13
 
6.2%
r 12
 
5.7%
t 12
 
5.7%
s 12
 
5.7%
Other values (13) 60
28.6%
Decimal Number
ValueCountFrequency (%)
1 519
27.8%
2 313
16.8%
5 206
 
11.1%
0 186
 
10.0%
4 179
 
9.6%
3 158
 
8.5%
7 119
 
6.4%
8 73
 
3.9%
6 62
 
3.3%
9 49
 
2.6%
Other Punctuation
ValueCountFrequency (%)
& 14
87.5%
# 1
 
6.2%
. 1
 
6.2%
Space Separator
ValueCountFrequency (%)
8432
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 74
100.0%
Close Punctuation
ValueCountFrequency (%)
) 1
100.0%
Open Punctuation
ValueCountFrequency (%)
( 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 63050
83.7%
Common 10388
 
13.8%
Latin 1850
 
2.5%

Most frequent character per script

Hangul
ValueCountFrequency (%)
6224
 
9.9%
2102
 
3.3%
1751
 
2.8%
1612
 
2.6%
1255
 
2.0%
1194
 
1.9%
1123
 
1.8%
962
 
1.5%
955
 
1.5%
914
 
1.4%
Other values (716) 44958
71.3%
Latin
ValueCountFrequency (%)
K 278
15.0%
S 235
12.7%
C 175
 
9.5%
A 115
 
6.2%
G 107
 
5.8%
E 91
 
4.9%
B 83
 
4.5%
T 73
 
3.9%
O 66
 
3.6%
I 64
 
3.5%
Other values (38) 563
30.4%
Common
ValueCountFrequency (%)
8432
81.2%
1 519
 
5.0%
2 313
 
3.0%
5 206
 
2.0%
0 186
 
1.8%
4 179
 
1.7%
3 158
 
1.5%
7 119
 
1.1%
- 74
 
0.7%
8 73
 
0.7%
Other values (7) 129
 
1.2%

Most occurring blocks

ValueCountFrequency (%)
Hangul 63050
83.7%
ASCII 12238
 
16.3%

Most frequent character per block

ASCII
ValueCountFrequency (%)
8432
68.9%
1 519
 
4.2%
2 313
 
2.6%
K 278
 
2.3%
S 235
 
1.9%
5 206
 
1.7%
0 186
 
1.5%
4 179
 
1.5%
C 175
 
1.4%
3 158
 
1.3%
Other values (55) 1557
 
12.7%
Hangul
ValueCountFrequency (%)
6224
 
9.9%
2102
 
3.3%
1751
 
2.8%
1612
 
2.6%
1255
 
2.0%
1194
 
1.9%
1123
 
1.8%
962
 
1.5%
955
 
1.5%
914
 
1.4%
Other values (716) 44958
71.3%

수목위도
Real number (ℝ)

Distinct8887
Distinct (%)96.5%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean37.579934
Minimum37.560934
Maximum37.607201
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size81.1 KiB
2023-12-13T06:20:54.015258image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum37.560934
5-th percentile37.565478
Q137.572789
median37.577918
Q337.586553
95-th percentile37.599901
Maximum37.607201
Range0.04626698
Interquartile range (IQR)0.0137634

Descriptive statistics

Standard deviation0.010041054
Coefficient of variation (CV)0.0002671919
Kurtosis-0.16327181
Mean37.579934
Median Absolute Deviation (MAD)0.006186695
Skewness0.6035137
Sum346186.35
Variance0.00010082276
MonotonicityNot monotonic
2023-12-13T06:20:54.148381image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
37.59120178 8
 
0.1%
37.59157944 5
 
0.1%
37.57294083 5
 
0.1%
37.60294342 4
 
< 0.1%
37.58654022 4
 
< 0.1%
37.57658768 4
 
< 0.1%
37.59164047 4
 
< 0.1%
37.5761528 3
 
< 0.1%
37.57731247 3
 
< 0.1%
37.59159851 3
 
< 0.1%
Other values (8877) 9169
99.5%
ValueCountFrequency (%)
37.56093442 1
< 0.1%
37.5609388 1
< 0.1%
37.56096726 1
< 0.1%
37.5609853 1
< 0.1%
37.56099441 1
< 0.1%
37.5610046 1
< 0.1%
37.56101088 1
< 0.1%
37.56101704 1
< 0.1%
37.56102721 1
< 0.1%
37.56104416 1
< 0.1%
ValueCountFrequency (%)
37.6072014 1
< 0.1%
37.60714059 1
< 0.1%
37.60709574 1
< 0.1%
37.60705509 1
< 0.1%
37.60701392 1
< 0.1%
37.60695358 1
< 0.1%
37.60688568 1
< 0.1%
37.60654449 1
< 0.1%
37.60649064 1
< 0.1%
37.60643534 1
< 0.1%

수목경도
Real number (ℝ)

Distinct8788
Distinct (%)95.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean127.05262
Minimum127.02351
Maximum127.07702
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size81.1 KiB
2023-12-13T06:20:54.291833image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum127.02351
5-th percentile127.02885
Q1127.04049
median127.05386
Q3127.06568
95-th percentile127.07348
Maximum127.07702
Range0.0535135
Interquartile range (IQR)0.025187

Descriptive statistics

Standard deviation0.014368967
Coefficient of variation (CV)0.00011309462
Kurtosis-1.0932446
Mean127.05262
Median Absolute Deviation (MAD)0.0125564
Skewness-0.19889889
Sum1170408.7
Variance0.00020646722
MonotonicityNot monotonic
2023-12-13T06:20:54.451998image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
127.0342331 9
 
0.1%
127.034256 8
 
0.1%
127.0350876 7
 
0.1%
127.0342636 7
 
0.1%
127.0266418 6
 
0.1%
127.0557404 6
 
0.1%
127.0342484 5
 
0.1%
127.0342102 5
 
0.1%
127.0342407 4
 
< 0.1%
127.038414 4
 
< 0.1%
Other values (8778) 9151
99.3%
ValueCountFrequency (%)
127.0235095 1
< 0.1%
127.0235507 1
< 0.1%
127.0235508 1
< 0.1%
127.0235519 1
< 0.1%
127.0235532 1
< 0.1%
127.0235573 1
< 0.1%
127.0235645 1
< 0.1%
127.0235716 1
< 0.1%
127.0236018 1
< 0.1%
127.0236441 1
< 0.1%
ValueCountFrequency (%)
127.077023 2
< 0.1%
127.077019 1
< 0.1%
127.0770169 1
< 0.1%
127.0770137 1
< 0.1%
127.0770136 1
< 0.1%
127.0770103 1
< 0.1%
127.0770096 1
< 0.1%
127.0770077 1
< 0.1%
127.0770065 1
< 0.1%
127.0770061 1
< 0.1%

도로명주소
Text

MISSING 

Distinct114
Distinct (%)27.0%
Missing8789
Missing (%)95.4%
Memory size72.1 KiB
2023-12-13T06:20:54.675408image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length23
Median length22
Mean length19.269504
Min length16

Characters and Unicode

Total characters8151
Distinct characters68
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

Unique72 ?
Unique (%)17.0%

Sample

1st row서울특별시 동대문구 서울시립대로 26-1
2nd row서울특별시 동대문구 한천로 272
3rd row서울특별시 동대문구 회기로 66
4th row서울특별시 동대문구 왕산로 52
5th row서울특별시 동대문구 왕산로 52
ValueCountFrequency (%)
서울특별시 423
24.9%
동대문구 423
24.9%
사가정로 59
 
3.5%
전농로10길 55
 
3.2%
20 53
 
3.1%
답십리로 44
 
2.6%
148 42
 
2.5%
130 40
 
2.4%
왕산로 38
 
2.2%
회기로 19
 
1.1%
Other values (129) 504
29.6%
2023-12-13T06:20:55.100117image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1277
15.7%
492
 
6.0%
449
 
5.5%
436
 
5.3%
433
 
5.3%
433
 
5.3%
425
 
5.2%
423
 
5.2%
423
 
5.2%
423
 
5.2%
Other values (58) 2937
36.0%

Most occurring categories

ValueCountFrequency (%)
Other Letter 5510
67.6%
Decimal Number 1321
 
16.2%
Space Separator 1277
 
15.7%
Dash Punctuation 43
 
0.5%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
492
8.9%
449
 
8.1%
436
 
7.9%
433
 
7.9%
433
 
7.9%
425
 
7.7%
423
 
7.7%
423
 
7.7%
423
 
7.7%
423
 
7.7%
Other values (46) 1150
20.9%
Decimal Number
ValueCountFrequency (%)
1 309
23.4%
0 237
17.9%
2 168
12.7%
4 126
9.5%
3 119
 
9.0%
6 81
 
6.1%
8 76
 
5.8%
9 71
 
5.4%
5 70
 
5.3%
7 64
 
4.8%
Space Separator
ValueCountFrequency (%)
1277
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 43
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 5510
67.6%
Common 2641
32.4%

Most frequent character per script

Hangul
ValueCountFrequency (%)
492
8.9%
449
 
8.1%
436
 
7.9%
433
 
7.9%
433
 
7.9%
425
 
7.7%
423
 
7.7%
423
 
7.7%
423
 
7.7%
423
 
7.7%
Other values (46) 1150
20.9%
Common
ValueCountFrequency (%)
1277
48.4%
1 309
 
11.7%
0 237
 
9.0%
2 168
 
6.4%
4 126
 
4.8%
3 119
 
4.5%
6 81
 
3.1%
8 76
 
2.9%
9 71
 
2.7%
5 70
 
2.7%
Other values (2) 107
 
4.1%

Most occurring blocks

ValueCountFrequency (%)
Hangul 5510
67.6%
ASCII 2641
32.4%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1277
48.4%
1 309
 
11.7%
0 237
 
9.0%
2 168
 
6.4%
4 126
 
4.8%
3 119
 
4.5%
6 81
 
3.1%
8 76
 
2.9%
9 71
 
2.7%
5 70
 
2.7%
Other values (2) 107
 
4.1%
Hangul
ValueCountFrequency (%)
492
8.9%
449
 
8.1%
436
 
7.9%
433
 
7.9%
433
 
7.9%
425
 
7.7%
423
 
7.7%
423
 
7.7%
423
 
7.7%
423
 
7.7%
Other values (46) 1150
20.9%
Distinct1277
Distinct (%)13.9%
Missing0
Missing (%)0.0%
Memory size72.1 KiB
2023-12-13T06:20:55.509584image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length25
Median length23
Mean length20.104103
Min length16

Characters and Unicode

Total characters185199
Distinct characters43
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

Unique512 ?
Unique (%)5.6%

Sample

1st row서울특별시 동대문구 용두동 237-10
2nd row서울특별시 동대문구 휘경동 112-43
3rd row서울특별시 동대문구 청량리동 203-316
4th row서울특별시 동대문구 답십리동 524-1
5th row서울특별시 동대문구 전농동 485-11
ValueCountFrequency (%)
서울특별시 9212
24.9%
동대문구 9212
24.9%
답십리동 1441
 
3.9%
장안동 1427
 
3.9%
전농동 1253
 
3.4%
용두동 1230
 
3.3%
제기동 930
 
2.5%
이문동 910
 
2.5%
휘경동 761
 
2.1%
청량리동 704
 
1.9%
Other values (1256) 9918
26.8%
2023-12-13T06:20:56.003450image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
27786
15.0%
18424
 
9.9%
10124
 
5.5%
9212
 
5.0%
9212
 
5.0%
9212
 
5.0%
9212
 
5.0%
9212
 
5.0%
9212
 
5.0%
9212
 
5.0%
Other values (33) 64381
34.8%

Most occurring categories

ValueCountFrequency (%)
Other Letter 112849
60.9%
Decimal Number 36903
 
19.9%
Space Separator 27786
 
15.0%
Dash Punctuation 7661
 
4.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
18424
16.3%
10124
9.0%
9212
8.2%
9212
8.2%
9212
8.2%
9212
8.2%
9212
8.2%
9212
8.2%
9212
8.2%
2148
 
1.9%
Other values (21) 17669
15.7%
Decimal Number
ValueCountFrequency (%)
1 6074
16.5%
2 5132
13.9%
4 4100
11.1%
5 3997
10.8%
3 3967
10.7%
6 3263
8.8%
7 3061
8.3%
0 2746
7.4%
9 2739
7.4%
8 1824
 
4.9%
Space Separator
ValueCountFrequency (%)
27786
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 7661
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 112849
60.9%
Common 72350
39.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
18424
16.3%
10124
9.0%
9212
8.2%
9212
8.2%
9212
8.2%
9212
8.2%
9212
8.2%
9212
8.2%
9212
8.2%
2148
 
1.9%
Other values (21) 17669
15.7%
Common
ValueCountFrequency (%)
27786
38.4%
- 7661
 
10.6%
1 6074
 
8.4%
2 5132
 
7.1%
4 4100
 
5.7%
5 3997
 
5.5%
3 3967
 
5.5%
6 3263
 
4.5%
7 3061
 
4.2%
0 2746
 
3.8%
Other values (2) 4563
 
6.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 112849
60.9%
ASCII 72350
39.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
27786
38.4%
- 7661
 
10.6%
1 6074
 
8.4%
2 5132
 
7.1%
4 4100
 
5.7%
5 3997
 
5.5%
3 3967
 
5.5%
6 3263
 
4.5%
7 3061
 
4.2%
0 2746
 
3.8%
Other values (2) 4563
 
6.3%
Hangul
ValueCountFrequency (%)
18424
16.3%
10124
9.0%
9212
8.2%
9212
8.2%
9212
8.2%
9212
8.2%
9212
8.2%
9212
8.2%
9212
8.2%
2148
 
1.9%
Other values (21) 17669
15.7%

행정동
Categorical

Distinct15
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size72.1 KiB
용신동
1538 
제기동
917 
답십리1동
892 
장안1동
872 
전농1동
825 
Other values (10)
4168 

Length

Max length5
Median length4
Mean length3.8671298
Min length3

Unique

Unique1 ?
Unique (%)< 0.1%

Sample

1st row용신동
2nd row휘경1동
3rd row청량리동
4th row답십리1동
5th row전농1동

Common Values

ValueCountFrequency (%)
용신동 1538
16.7%
제기동 917
10.0%
답십리1동 892
9.7%
장안1동 872
9.5%
전농1동 825
9.0%
청량리동 713
7.7%
장안2동 617
6.7%
답십리2동 569
 
6.2%
이문2동 536
 
5.8%
휘경2동 442
 
4.8%
Other values (5) 1291
14.0%

Length

2023-12-13T06:20:56.138942image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
용신동 1538
16.7%
제기동 917
10.0%
답십리1동 892
9.7%
장안1동 872
9.5%
전농1동 825
9.0%
청량리동 713
7.7%
장안2동 617
6.7%
답십리2동 569
 
6.2%
이문2동 536
 
5.8%
휘경2동 442
 
4.8%
Other values (5) 1291
14.0%

흉고직경
Real number (ℝ)

Distinct80
Distinct (%)0.9%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.27948545
Minimum0.03
Maximum1.59
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size81.1 KiB
2023-12-13T06:20:56.260438image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0.03
5-th percentile0.1
Q10.16
median0.29
Q30.38
95-th percentile0.49
Maximum1.59
Range1.56
Interquartile range (IQR)0.22

Descriptive statistics

Standard deviation0.13183915
Coefficient of variation (CV)0.47172097
Kurtosis0.61011319
Mean0.27948545
Median Absolute Deviation (MAD)0.1
Skewness0.39867639
Sum2574.62
Variance0.017381561
MonotonicityNot monotonic
2023-12-13T06:20:56.395831image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.11 514
 
5.6%
0.1 336
 
3.6%
0.32 329
 
3.6%
0.12 296
 
3.2%
0.35 279
 
3.0%
0.39 273
 
3.0%
0.38 268
 
2.9%
0.33 266
 
2.9%
0.13 264
 
2.9%
0.37 256
 
2.8%
Other values (70) 6131
66.6%
ValueCountFrequency (%)
0.03 7
 
0.1%
0.04 20
 
0.2%
0.05 21
 
0.2%
0.06 34
 
0.4%
0.07 69
 
0.7%
0.08 91
 
1.0%
0.09 198
 
2.1%
0.1 336
3.6%
0.11 514
5.6%
0.12 296
3.2%
ValueCountFrequency (%)
1.59 1
< 0.1%
0.89 1
< 0.1%
0.86 1
< 0.1%
0.83 1
< 0.1%
0.81 1
< 0.1%
0.8 1
< 0.1%
0.78 1
< 0.1%
0.77 2
< 0.1%
0.76 2
< 0.1%
0.74 1
< 0.1%

근원직경
Real number (ℝ)

Distinct91
Distinct (%)1.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.34648176
Minimum0.04
Maximum1.56
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size81.1 KiB
2023-12-13T06:20:56.531888image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0.04
5-th percentile0.13
Q10.2
median0.35
Q30.46
95-th percentile0.59
Maximum1.56
Range1.52
Interquartile range (IQR)0.26

Descriptive statistics

Standard deviation0.15553707
Coefficient of variation (CV)0.44890405
Kurtosis0.057073953
Mean0.34648176
Median Absolute Deviation (MAD)0.13
Skewness0.31149361
Sum3191.79
Variance0.024191779
MonotonicityNot monotonic
2023-12-13T06:20:56.668256image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.14 360
 
3.9%
0.45 306
 
3.3%
0.13 286
 
3.1%
0.48 271
 
2.9%
0.18 266
 
2.9%
0.42 250
 
2.7%
0.16 242
 
2.6%
0.43 241
 
2.6%
0.4 240
 
2.6%
0.15 234
 
2.5%
Other values (81) 6516
70.7%
ValueCountFrequency (%)
0.04 5
 
0.1%
0.05 18
 
0.2%
0.06 9
 
0.1%
0.07 11
 
0.1%
0.08 33
 
0.4%
0.09 33
 
0.4%
0.1 48
 
0.5%
0.11 119
1.3%
0.12 154
1.7%
0.13 286
3.1%
ValueCountFrequency (%)
1.56 1
< 0.1%
1.33 1
< 0.1%
1.15 1
< 0.1%
1.05 2
< 0.1%
1.02 2
< 0.1%
0.99 1
< 0.1%
0.92 2
< 0.1%
0.9 1
< 0.1%
0.89 2
< 0.1%
0.88 2
< 0.1%

식재간격
Real number (ℝ)

Distinct194
Distinct (%)2.1%
Missing49
Missing (%)0.5%
Infinite0
Infinite (%)0.0%
Mean7.2601768
Minimum0.5
Maximum50
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size81.1 KiB
2023-12-13T06:20:56.795814image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0.5
5-th percentile3.8
Q15.4
median6.5
Q38
95-th percentile14.2
Maximum50
Range49.5
Interquartile range (IQR)2.6

Descriptive statistics

Standard deviation3.6734494
Coefficient of variation (CV)0.50597244
Kurtosis15.608331
Mean7.2601768
Median Absolute Deviation (MAD)1.5
Skewness3.0423112
Sum66525
Variance13.49423
MonotonicityNot monotonic
2023-12-13T06:20:57.160499image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
6.0 1464
15.9%
7.0 1124
 
12.2%
5.0 907
 
9.8%
8.0 740
 
8.0%
4.0 408
 
4.4%
9.0 405
 
4.4%
6.5 325
 
3.5%
5.5 311
 
3.4%
7.5 178
 
1.9%
10.0 170
 
1.8%
Other values (184) 3131
34.0%
ValueCountFrequency (%)
0.5 1
 
< 0.1%
0.7 1
 
< 0.1%
0.8 1
 
< 0.1%
1.0 34
0.4%
1.4 3
 
< 0.1%
1.5 18
 
0.2%
1.6 2
 
< 0.1%
1.7 1
 
< 0.1%
1.8 5
 
0.1%
2.0 81
0.9%
ValueCountFrequency (%)
50.0 1
< 0.1%
46.0 1
< 0.1%
45.0 1
< 0.1%
42.0 1
< 0.1%
40.0 1
< 0.1%
36.5 1
< 0.1%
36.0 1
< 0.1%
35.0 1
< 0.1%
34.0 2
< 0.1%
33.0 1
< 0.1%

수령
Real number (ℝ)

Distinct92
Distinct (%)1.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean33.025076
Minimum6
Maximum133
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size81.1 KiB
2023-12-13T06:20:57.273513image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum6
5-th percentile14
Q123
median31
Q340
95-th percentile58
Maximum133
Range127
Interquartile range (IQR)17

Descriptive statistics

Standard deviation13.315955
Coefficient of variation (CV)0.40320739
Kurtosis1.7160935
Mean33.025076
Median Absolute Deviation (MAD)8
Skewness0.97673198
Sum304227
Variance177.31465
MonotonicityNot monotonic
2023-12-13T06:20:57.400007image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
23 520
 
5.6%
30 495
 
5.4%
25 443
 
4.8%
28 369
 
4.0%
32 358
 
3.9%
35 329
 
3.6%
21 294
 
3.2%
33 283
 
3.1%
34 282
 
3.1%
40 276
 
3.0%
Other values (82) 5563
60.4%
ValueCountFrequency (%)
6 3
 
< 0.1%
7 24
 
0.3%
8 7
 
0.1%
9 20
 
0.2%
10 19
 
0.2%
11 33
 
0.4%
12 39
 
0.4%
13 100
1.1%
14 219
2.4%
15 190
2.1%
ValueCountFrequency (%)
133 1
 
< 0.1%
112 2
< 0.1%
105 1
 
< 0.1%
100 3
< 0.1%
99 1
 
< 0.1%
98 2
< 0.1%
96 1
 
< 0.1%
94 1
 
< 0.1%
92 2
< 0.1%
90 2
< 0.1%

도로폭
Real number (ℝ)

Distinct22
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean22.963092
Minimum4
Maximum40
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size81.1 KiB
2023-12-13T06:20:57.510958image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum4
5-th percentile10
Q120
median20
Q325
95-th percentile40
Maximum40
Range36
Interquartile range (IQR)5

Descriptive statistics

Standard deviation7.7519313
Coefficient of variation (CV)0.33758221
Kurtosis0.075997847
Mean22.963092
Median Absolute Deviation (MAD)5
Skewness0.29340041
Sum211536
Variance60.092439
MonotonicityNot monotonic
2023-12-13T06:20:57.686478image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=22)
ValueCountFrequency (%)
20 2794
30.3%
25 1876
20.4%
30 745
 
8.1%
35 634
 
6.9%
40 549
 
6.0%
17 417
 
4.5%
10 387
 
4.2%
29 330
 
3.6%
14 321
 
3.5%
15 204
 
2.2%
Other values (12) 955
 
10.4%
ValueCountFrequency (%)
4 66
 
0.7%
5 27
 
0.3%
6 107
 
1.2%
7 26
 
0.3%
8 32
 
0.3%
9 14
 
0.2%
10 387
4.2%
11 51
 
0.6%
12 23
 
0.2%
14 321
3.5%
ValueCountFrequency (%)
40 549
 
6.0%
35 634
 
6.9%
30 745
 
8.1%
29 330
 
3.6%
25 1876
20.4%
23 187
 
2.0%
20 2794
30.3%
19 98
 
1.1%
18 192
 
2.1%
17 417
 
4.5%

보도폭
Text

MISSING 

Distinct166
Distinct (%)1.9%
Missing246
Missing (%)2.7%
Memory size72.1 KiB
2023-12-13T06:20:57.870140image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length8
Median length3
Mean length2.6764443
Min length1

Characters and Unicode

Total characters23997
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

Unique86 ?
Unique (%)1.0%

Sample

1st row3
2nd row1.1
3rd row1.5
4th row3
5th row1.3
ValueCountFrequency (%)
1.5 784
 
8.7%
2 662
 
7.4%
1.3 634
 
7.1%
1.2 552
 
6.2%
1.7 479
 
5.3%
1.6 430
 
4.8%
1 424
 
4.7%
1.8 410
 
4.6%
1.4 374
 
4.2%
3 294
 
3.3%
Other values (156) 3923
43.8%
2023-12-13T06:20:58.175332image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
. 7398
30.8%
1 5150
21.5%
2 3390
14.1%
3 1939
 
8.1%
5 1607
 
6.7%
4 1023
 
4.3%
8 937
 
3.9%
7 858
 
3.6%
6 747
 
3.1%
9 430
 
1.8%
Other values (2) 518
 
2.2%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 16497
68.7%
Other Punctuation 7398
30.8%
Math Symbol 102
 
0.4%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 5150
31.2%
2 3390
20.5%
3 1939
 
11.8%
5 1607
 
9.7%
4 1023
 
6.2%
8 937
 
5.7%
7 858
 
5.2%
6 747
 
4.5%
9 430
 
2.6%
0 416
 
2.5%
Other Punctuation
ValueCountFrequency (%)
. 7398
100.0%
Math Symbol
ValueCountFrequency (%)
| 102
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 23997
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
. 7398
30.8%
1 5150
21.5%
2 3390
14.1%
3 1939
 
8.1%
5 1607
 
6.7%
4 1023
 
4.3%
8 937
 
3.9%
7 858
 
3.6%
6 747
 
3.1%
9 430
 
1.8%
Other values (2) 518
 
2.2%

Most occurring blocks

ValueCountFrequency (%)
ASCII 23997
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
. 7398
30.8%
1 5150
21.5%
2 3390
14.1%
3 1939
 
8.1%
5 1607
 
6.7%
4 1023
 
4.3%
8 937
 
3.9%
7 858
 
3.6%
6 747
 
3.1%
9 430
 
1.8%
Other values (2) 518
 
2.2%

보호덮개
Categorical

Distinct5
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size72.1 KiB
주철
3055 
<NA>
2815 
압연강판
2710 
기타
631 
콘크리트
 
1

Length

Max length4
Median length4
Mean length3.1997395
Min length2

Unique

Unique1 ?
Unique (%)< 0.1%

Sample

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

Common Values

ValueCountFrequency (%)
주철 3055
33.2%
<NA> 2815
30.6%
압연강판 2710
29.4%
기타 631
 
6.8%
콘크리트 1
 
< 0.1%

Length

2023-12-13T06:20:58.289881image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T06:20:58.381709image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
주철 3055
33.2%
na 2815
30.6%
압연강판 2710
29.4%
기타 631
 
6.8%
콘크리트 1
 
< 0.1%

보호틀
Categorical

Distinct6
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size72.1 KiB
사각형
6410 
대상형
1586 
<NA>
941 
말발굽형
 
266
원형
 
6

Length

Max length4
Median length3
Mean length3.1300478
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
사각형 6410
69.6%
대상형 1586
 
17.2%
<NA> 941
 
10.2%
말발굽형 266
 
2.9%
원형 6
 
0.1%
기타 3
 
< 0.1%

Length

2023-12-13T06:20:58.487347image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T06:20:58.607761image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
사각형 6410
69.6%
대상형 1586
 
17.2%
na 941
 
10.2%
말발굽형 266
 
2.9%
원형 6
 
0.1%
기타 3
 
< 0.1%

보호틀파손여부
Boolean

IMBALANCE 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size9.1 KiB
False
9089 
True
 
123
ValueCountFrequency (%)
False 9089
98.7%
True 123
 
1.3%
2023-12-13T06:20:58.698354image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

뿌리융기여부
Boolean

IMBALANCE 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size9.1 KiB
False
8896 
True
 
316
ValueCountFrequency (%)
False 8896
96.6%
True 316
 
3.4%
2023-12-13T06:20:58.771628image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

통기
Boolean

IMBALANCE 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size9.1 KiB
False
9134 
True
 
78
ValueCountFrequency (%)
False 9134
99.2%
True 78
 
0.8%
2023-12-13T06:20:58.841326image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

지장물1
Categorical

Distinct10
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size72.1 KiB
전깃줄
3995 
<NA>
2482 
전신주
1108 
가로등
994 
표지판
 
349
Other values (5)
 
284

Length

Max length4
Median length3
Mean length3.2597699
Min length2

Unique

Unique1 ?
Unique (%)< 0.1%

Sample

1st row전깃줄
2nd row전깃줄
3rd row전깃줄
4th row전깃줄
5th row표지판

Common Values

ValueCountFrequency (%)
전깃줄 3995
43.4%
<NA> 2482
26.9%
전신주 1108
 
12.0%
가로등 994
 
10.8%
표지판 349
 
3.8%
신호등 194
 
2.1%
건물 51
 
0.6%
기타 22
 
0.2%
간판 16
 
0.2%
전신수 1
 
< 0.1%

Length

2023-12-13T06:20:58.944178image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T06:20:59.069276image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
전깃줄 3995
43.4%
na 2482
26.9%
전신주 1108
 
12.0%
가로등 994
 
10.8%
표지판 349
 
3.8%
신호등 194
 
2.1%
건물 51
 
0.6%
기타 22
 
0.2%
간판 16
 
0.2%
전신수 1
 
< 0.1%

지장물2
Categorical

IMBALANCE 

Distinct9
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size72.1 KiB
<NA>
6860 
전깃줄
1930 
가로등
 
208
건물
 
69
전신주
 
63
Other values (4)
 
82

Length

Max length4
Median length4
Mean length3.7323057
Min length2

Unique

Unique1 ?
Unique (%)< 0.1%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 6860
74.5%
전깃줄 1930
 
21.0%
가로등 208
 
2.3%
건물 69
 
0.7%
전신주 63
 
0.7%
기타 44
 
0.5%
표지판 35
 
0.4%
신호등 2
 
< 0.1%
간판 1
 
< 0.1%

Length

2023-12-13T06:20:59.207233image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T06:20:59.323582image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 6860
74.5%
전깃줄 1930
 
21.0%
가로등 208
 
2.3%
건물 69
 
0.7%
전신주 63
 
0.7%
기타 44
 
0.5%
표지판 35
 
0.4%
신호등 2
 
< 0.1%
간판 1
 
< 0.1%

수목전경사진
Text

UNIQUE 

Distinct9212
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size72.1 KiB
2023-12-13T06:20:59.551068image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length30
Median length28
Mean length25.09162
Min length24

Characters and Unicode

Total characters231144
Distinct characters75
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

Unique9212 ?
Unique (%)100.0%

Sample

1st row01-06-천호대로-가-0484-001.jpg
2nd row01-06-외대역동로-가-0141-001.jpg
3rd row01-06-제기로17길-가-0003-001.jpg
4th row01-06-천호대로-가-0339-001.jpg
5th row01-06-답십리로-가-0017-001.jpg
ValueCountFrequency (%)
01-06-천호대로-가-0484-001.jpg 1
 
< 0.1%
01-06-청계천로-가-0188-001.jpg 1
 
< 0.1%
01-06-무학로-가-0013-001.jpg 1
 
< 0.1%
01-06-고산자로-가-0226-001.jpg 1
 
< 0.1%
01-06-장안벚꽃로-가-0488-001.jpg 1
 
< 0.1%
01-06-황물로-가-0247-001.jpg 1
 
< 0.1%
01-06-한천로-가-0549-001.jpg 1
 
< 0.1%
01-06-이문로-가-0103-001.jpg 1
 
< 0.1%
01-06-황물로-가-0294-001.jpg 1
 
< 0.1%
01-06-한천로-가-0513-001.jpg 1
 
< 0.1%
Other values (9202) 9202
99.9%
2023-12-13T06:20:59.932801image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 52309
22.6%
- 46060
19.9%
1 23466
10.2%
6 11136
 
4.8%
9662
 
4.2%
. 9212
 
4.0%
g 9212
 
4.0%
p 9212
 
4.0%
9212
 
4.0%
j 9212
 
4.0%
Other values (65) 42451
18.4%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 104176
45.1%
Dash Punctuation 46060
19.9%
Other Letter 44060
19.1%
Lowercase Letter 27636
 
12.0%
Other Punctuation 9212
 
4.0%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
9662
21.9%
9212
20.9%
2249
 
5.1%
1545
 
3.5%
1516
 
3.4%
1278
 
2.9%
919
 
2.1%
765
 
1.7%
740
 
1.7%
680
 
1.5%
Other values (50) 15494
35.2%
Decimal Number
ValueCountFrequency (%)
0 52309
50.2%
1 23466
22.5%
6 11136
 
10.7%
2 3894
 
3.7%
3 2978
 
2.9%
4 2538
 
2.4%
5 2515
 
2.4%
7 1895
 
1.8%
8 1857
 
1.8%
9 1588
 
1.5%
Lowercase Letter
ValueCountFrequency (%)
g 9212
33.3%
p 9212
33.3%
j 9212
33.3%
Dash Punctuation
ValueCountFrequency (%)
- 46060
100.0%
Other Punctuation
ValueCountFrequency (%)
. 9212
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 159448
69.0%
Hangul 44060
 
19.1%
Latin 27636
 
12.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
9662
21.9%
9212
20.9%
2249
 
5.1%
1545
 
3.5%
1516
 
3.4%
1278
 
2.9%
919
 
2.1%
765
 
1.7%
740
 
1.7%
680
 
1.5%
Other values (50) 15494
35.2%
Common
ValueCountFrequency (%)
0 52309
32.8%
- 46060
28.9%
1 23466
14.7%
6 11136
 
7.0%
. 9212
 
5.8%
2 3894
 
2.4%
3 2978
 
1.9%
4 2538
 
1.6%
5 2515
 
1.6%
7 1895
 
1.2%
Other values (2) 3445
 
2.2%
Latin
ValueCountFrequency (%)
g 9212
33.3%
p 9212
33.3%
j 9212
33.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 187084
80.9%
Hangul 44060
 
19.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 52309
28.0%
- 46060
24.6%
1 23466
12.5%
6 11136
 
6.0%
. 9212
 
4.9%
g 9212
 
4.9%
p 9212
 
4.9%
j 9212
 
4.9%
2 3894
 
2.1%
3 2978
 
1.6%
Other values (5) 10393
 
5.6%
Hangul
ValueCountFrequency (%)
9662
21.9%
9212
20.9%
2249
 
5.1%
1545
 
3.5%
1516
 
3.4%
1278
 
2.9%
919
 
2.1%
765
 
1.7%
740
 
1.7%
680
 
1.5%
Other values (50) 15494
35.2%

보호덮개사진
Text

UNIQUE 

Distinct9212
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size72.1 KiB
2023-12-13T06:21:00.243189image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length30
Median length28
Mean length25.09162
Min length24

Characters and Unicode

Total characters231144
Distinct characters75
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

Unique9212 ?
Unique (%)100.0%

Sample

1st row01-06-천호대로-가-0484-002.jpg
2nd row01-06-외대역동로-가-0141-002.jpg
3rd row01-06-제기로17길-가-0003-002.jpg
4th row01-06-천호대로-가-0339-002.jpg
5th row01-06-답십리로-가-0017-002.jpg
ValueCountFrequency (%)
01-06-천호대로-가-0484-002.jpg 1
 
< 0.1%
01-06-청계천로-가-0188-002.jpg 1
 
< 0.1%
01-06-무학로-가-0013-002.jpg 1
 
< 0.1%
01-06-고산자로-가-0226-002.jpg 1
 
< 0.1%
01-06-장안벚꽃로-가-0488-002.jpg 1
 
< 0.1%
01-06-황물로-가-0247-002.jpg 1
 
< 0.1%
01-06-한천로-가-0549-002.jpg 1
 
< 0.1%
01-06-이문로-가-0103-002.jpg 1
 
< 0.1%
01-06-황물로-가-0294-002.jpg 1
 
< 0.1%
01-06-한천로-가-0513-002.jpg 1
 
< 0.1%
Other values (9202) 9202
99.9%
2023-12-13T06:21:00.643265image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 52309
22.6%
- 46060
19.9%
1 14254
 
6.2%
2 13106
 
5.7%
6 11136
 
4.8%
9662
 
4.2%
g 9212
 
4.0%
p 9212
 
4.0%
j 9212
 
4.0%
. 9212
 
4.0%
Other values (65) 47769
20.7%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 104176
45.1%
Dash Punctuation 46060
19.9%
Other Letter 44060
19.1%
Lowercase Letter 27636
 
12.0%
Other Punctuation 9212
 
4.0%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
9662
21.9%
9212
20.9%
2249
 
5.1%
1545
 
3.5%
1516
 
3.4%
1278
 
2.9%
919
 
2.1%
765
 
1.7%
740
 
1.7%
680
 
1.5%
Other values (50) 15494
35.2%
Decimal Number
ValueCountFrequency (%)
0 52309
50.2%
1 14254
 
13.7%
2 13106
 
12.6%
6 11136
 
10.7%
3 2978
 
2.9%
4 2538
 
2.4%
5 2515
 
2.4%
7 1895
 
1.8%
8 1857
 
1.8%
9 1588
 
1.5%
Lowercase Letter
ValueCountFrequency (%)
g 9212
33.3%
p 9212
33.3%
j 9212
33.3%
Dash Punctuation
ValueCountFrequency (%)
- 46060
100.0%
Other Punctuation
ValueCountFrequency (%)
. 9212
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 159448
69.0%
Hangul 44060
 
19.1%
Latin 27636
 
12.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
9662
21.9%
9212
20.9%
2249
 
5.1%
1545
 
3.5%
1516
 
3.4%
1278
 
2.9%
919
 
2.1%
765
 
1.7%
740
 
1.7%
680
 
1.5%
Other values (50) 15494
35.2%
Common
ValueCountFrequency (%)
0 52309
32.8%
- 46060
28.9%
1 14254
 
8.9%
2 13106
 
8.2%
6 11136
 
7.0%
. 9212
 
5.8%
3 2978
 
1.9%
4 2538
 
1.6%
5 2515
 
1.6%
7 1895
 
1.2%
Other values (2) 3445
 
2.2%
Latin
ValueCountFrequency (%)
g 9212
33.3%
p 9212
33.3%
j 9212
33.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 187084
80.9%
Hangul 44060
 
19.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 52309
28.0%
- 46060
24.6%
1 14254
 
7.6%
2 13106
 
7.0%
6 11136
 
6.0%
g 9212
 
4.9%
p 9212
 
4.9%
j 9212
 
4.9%
. 9212
 
4.9%
3 2978
 
1.6%
Other values (5) 10393
 
5.6%
Hangul
ValueCountFrequency (%)
9662
21.9%
9212
20.9%
2249
 
5.1%
1545
 
3.5%
1516
 
3.4%
1278
 
2.9%
919
 
2.1%
765
 
1.7%
740
 
1.7%
680
 
1.5%
Other values (50) 15494
35.2%

Sample

관리번호수목명수목구분수목유형식재일관리기관전화번호관리기관명데이터기준일자도로명도로종류도로시작점도로종료점수목위치수목위도수목경도도로명주소지번주소행정동흉고직경근원직경식재간격수령도로폭보도폭보호덮개보호틀보호틀파손여부뿌리융기여부통기지장물1지장물2수목전경사진보호덮개사진
006-천호대로-가-0484양버즘나무가로수교목1995-04-0402-2127-4319서울특별시 동대문구청2022-12-12천호대로특별시도서울특별시 동대문구 신설동 117-21서울특별시 동대문구 장안동 204-13천호대로 47 앞37.574013127.028637<NA>서울특별시 동대문구 용두동 237-10용신동0.380.4519.032403<NA><NA>NNN전깃줄<NA>01-06-천호대로-가-0484-001.jpg01-06-천호대로-가-0484-002.jpg
106-외대역동로-가-0141양버즘나무가로수교목1994-04-0402-2127-4319서울특별시 동대문구청2022-12-12외대역동로특별시도서울특별시 동대문구 휘경동 55-3서울특별시 동대문구 이문동 101-37동양엔파트 앞37.59188127.066931<NA>서울특별시 동대문구 휘경동 112-43휘경1동0.40.51<NA>34101.1주철말발굽형NYN전깃줄<NA>01-06-외대역동로-가-0141-001.jpg01-06-외대역동로-가-0141-002.jpg
206-제기로17길-가-0003은행나무가로수교목1976-04-0602-2127-4319서울특별시 동대문구청2022-12-12제기로17길특별시도서울특별시 동대문구 청량리동 520-55서울특별시 동대문구 청량리동 205-293서일eng 앞37.587162127.041206<NA>서울특별시 동대문구 청량리동 203-316청량리동0.410.495.052141.5기타<NA>NNN전깃줄건물01-06-제기로17길-가-0003-001.jpg01-06-제기로17길-가-0003-002.jpg
306-천호대로-가-0339양버즘나무가로수교목1979-04-0602-2127-4319서울특별시 동대문구청2022-12-12천호대로특별시도서울특별시 동대문구 신설동 117-21서울특별시 동대문구 장안동 204-13신답역 앞 정류장 앞37.570862127.047104<NA>서울특별시 동대문구 답십리동 524-1답십리1동0.580.67.049403압연강판사각형NNN전깃줄<NA>01-06-천호대로-가-0339-001.jpg01-06-천호대로-가-0339-002.jpg
406-답십리로-가-0017양버즘나무가로수교목1991-04-0402-2127-4319서울특별시 동대문구청2022-12-12답십리로특별시도서울특별시 동대문구 전농동 621-1서울특별시 동대문구 장안동 333-2대한열쇠 앞37.576884127.046116<NA>서울특별시 동대문구 전농동 485-11전농1동0.430.577.936301.3주철사각형NNN표지판전깃줄01-06-답십리로-가-0017-001.jpg01-06-답십리로-가-0017-002.jpg
506-사가정로-가-0199은행나무가로수교목2003-04-0702-2127-4319서울특별시 동대문구청2022-12-12사가정로특별시도서울특별시 동대문구 답십리동 524-1경기도 구리시 아천동 28-2푸른마을아파트37.580064127.07516<NA>서울특별시 동대문구 장안동 469-1장안2동0.190.255.024201주철사각형NNN전깃줄<NA>01-06-사가정로-가-0199-001.jpg01-06-사가정로-가-0199-002.jpg
606-한천로-가-0376은행나무가로수교목1992-04-0602-2127-4319서울특별시 동대문구청2022-12-12한천로특별시도서울특별시 동대문구 장안동 413-7서울특별시 동대문구 이문동 209-13시현pet살롱 앞37.598417127.067649<NA>서울특별시 동대문구 이문동 105-1이문1동0.280.378.035200.9압연강판사각형NNN전깃줄<NA>01-06-한천로-가-0376-001.jpg01-06-한천로-가-0376-002.jpg
706-서울시립대로-가-0126은행나무가로수교목1971-04-0602-2127-4319서울특별시 동대문구청2022-12-12서울시립대로특별시도서울특별시 동대문구 답십리동 464-1서울특별시 동대문구 전농동 152-11정원돌솥밥37.582705127.05287<NA>서울특별시 동대문구 전농동 124-19전농1동0.450.557.057251.7주철사각형NNN전깃줄<NA>01-06-서울시립대로-가-0126-001.jpg01-06-서울시립대로-가-0126-002.jpg
806-서울시립대로-가-0195은행나무가로수교목1974-04-0402-2127-4319서울특별시 동대문구청2022-12-12서울시립대로특별시도서울특별시 동대문구 답십리동 464-1서울특별시 동대문구 전농동 152-11주안건설앞37.58075127.051531<NA>서울특별시 동대문구 전농동 582-24전농1동0.420.515.753251.7주철사각형NNN전깃줄<NA>01-06-서울시립대로-가-0195-001.jpg01-06-서울시립대로-가-0195-002.jpg
906-제기로17길-가-0032은행나무가로수교목1974-04-0402-2127-4319서울특별시 동대문구청2022-12-12제기로17길특별시도서울특별시 동대문구 청량리동 520-55서울특별시 동대문구 청량리동 205-293제기로17길53 앞37.589175127.040736<NA>서울특별시 동대문구 청량리동 205-375청량리동0.420.485.653141.7기타<NA>NNN전신주전깃줄01-06-제기로17길-가-0032-001.jpg01-06-제기로17길-가-0032-002.jpg
관리번호수목명수목구분수목유형식재일관리기관전화번호관리기관명데이터기준일자도로명도로종류도로시작점도로종료점수목위치수목위도수목경도도로명주소지번주소행정동흉고직경근원직경식재간격수령도로폭보도폭보호덮개보호틀보호틀파손여부뿌리융기여부통기지장물1지장물2수목전경사진보호덮개사진
920206-답십리로29길-가-0024이팝나무가로수교목2000-04-0402-2127-4319서울특별시 동대문구청2022-12-12답십리로29길특별시도서울특별시 동대문구 전농동 651-22서울특별시 동대문구 전농동 558-154롯데캐슬노블레스아파트 앞37.577129127.050522<NA>서울특별시 동대문구 전농동 695-4전농1동0.130.148.02852<NA>대상형NNN<NA><NA>01-06-답십리로29길-가-0024-001.jpg01-06-답십리로29길-가-0024-002.jpg
920306-답십리로29길-가-0025이팝나무가로수교목2008-04-0402-2127-4319서울특별시 동대문구청2022-12-12답십리로29길특별시도서울특별시 동대문구 전농동 651-22서울특별시 동대문구 전농동 558-154롯데캐슬노블레스아파트 앞37.577194127.050561<NA>서울특별시 동대문구 전농동 695-4전농1동0.090.118.01952<NA>대상형NNN<NA><NA>01-06-답십리로29길-가-0025-001.jpg01-06-답십리로29길-가-0025-002.jpg
920406-답십리로29길-가-0026이팝나무가로수교목2006-04-0502-2127-4319서울특별시 동대문구청2022-12-12답십리로29길특별시도서울특별시 동대문구 전농동 651-22서울특별시 동대문구 전농동 558-154롯데캐슬노블레스아파트 앞37.577259127.050613<NA>서울특별시 동대문구 전농동 695-4전농1동0.10.128.02152<NA>대상형NNN<NA><NA>01-06-답십리로29길-가-0026-001.jpg01-06-답십리로29길-가-0026-002.jpg
920506-답십리로29길-가-0027이팝나무가로수교목2006-04-0502-2127-4319서울특별시 동대문구청2022-12-12답십리로29길특별시도서울특별시 동대문구 전농동 651-22서울특별시 동대문구 전농동 558-154롯데캐슬노블레스아파트 앞37.57732127.050659<NA>서울특별시 동대문구 전농동 695-4전농1동0.10.128.02152<NA>대상형NNN<NA><NA>01-06-답십리로29길-가-0027-001.jpg01-06-답십리로29길-가-0027-002.jpg
920606-답십리로-가-0450양버즘나무가로수교목2006-04-0502-2127-4319서울특별시 동대문구청2022-12-12답십리로특별시도서울특별시 동대문구 전농동 621-1서울특별시 동대문구 장안동 333-2KB국민은행 앞37.575813127.047798<NA>서울특별시 동대문구 전농동 648-164전농1동0.250.3111.021301.2주철사각형NNN가로등전깃줄01-06-답십리로-가-0450-001.jpg01-06-답십리로-가-0450-002.jpg
920706-고산자로-가-0152벚나무가로수교목2008-04-0402-2127-4319서울특별시 동대문구청2022-12-12고산자로특별시도서울특별시 동대문구 용두동 696-10서울특별시 동대문구 제기동 1149-16KB국민은행 앞37.587456127.037956<NA>서울특별시 동대문구 제기동 122-40제기동0.090.10.511251.2<NA>대상형NNN가로등<NA>01-06-고산자로-가-0152-001.jpg01-06-고산자로-가-0152-002.jpg
920806-천호대로47길-가-0006느티나무가로수교목1972-04-0602-2127-4319서울특별시 동대문구청2022-12-12천호대로47길특별시도서울특별시 동대문구 답십리동 463-13서울특별시 동대문구 답십리동 645-8신답초등학교 옆37.573167127.043026서울특별시 동대문구 천호대로 177서울특별시 동대문구 답십리동 463-13답십리1동0.450.596.855193.5압연강판<NA>NYN전깃줄<NA>01-06-천호대로47길-가-0006-001.jpg01-06-천호대로47길-가-0006-002.jpg
920906-장안벚꽃로-가-0245이팝나무가로수교목2006-04-0502-2127-4319서울특별시 동대문구청2022-12-12장안벚꽃로특별시도서울특별시 동대문구 장안동 467서울특별시 동대문구 휘경동 산6-69전동중학교 옆37.585167127.071857<NA>서울특별시 동대문구 휘경동 49-11휘경2동0.10.136.021202.4압연강판<NA>NYN<NA><NA>01-06-장안벚꽃로-가-0245-001.jpg01-06-장안벚꽃로-가-0245-002.jpg
921006-사가정로-가-0036은행나무가로수교목1977-04-0602-2127-4319서울특별시 동대문구청2022-12-12사가정로특별시도서울특별시 동대문구 답십리동 524-1경기도 구리시 아천동 28-2헤드캔디 앞37.572853127.051567<NA>서울특별시 동대문구 답십리동 524-1답십리1동0.40.515.550202.7압연강판사각형NNN가로등전깃줄01-06-사가정로-가-0036-001.jpg01-06-사가정로-가-0036-002.jpg
921106-사가정로-가-0330은행나무가로수교목1982-04-0602-2127-4319서울특별시 동대문구청2022-12-12사가정로특별시도서울특별시 동대문구 답십리동 524-1경기도 구리시 아천동 28-2타이어365타이어할인점 전농점 앞37.575848127.055321<NA>서울특별시 동대문구 전농동 325-21전농1동0.360.413.045202.3주철사각형NNN전신주전깃줄01-06-사가정로-가-0330-001.jpg01-06-사가정로-가-0330-002.jpg