Overview

Dataset statistics

Number of variables15
Number of observations10000
Missing cells9088
Missing cells (%)6.1%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory1.3 MiB
Average record size in memory133.0 B

Variable types

Numeric4
Text4
Categorical6
Boolean1

Dataset

Description양평군 관내 가로수 데이터를 행정구역, 가로수 노선, 가로수길 시작점, 종점, 고유번호, 경도, 위도 등의 항목으로 제공하는 서비스
Author경기도 양평군
URLhttps://www.data.go.kr/data/15097915/fileData.do

Alerts

피해여부 has constant value ""Constant
가로수 수량 has constant value ""Constant
수종 is highly overall correlated with 수령 and 3 other fieldsHigh correlation
행정 구역(읍-면-동) is highly overall correlated with 번호 and 6 other fieldsHigh correlation
수고(m) is highly overall correlated with 번호 and 5 other fieldsHigh correlation
관리 기관 is highly overall correlated with 번호 and 6 other fieldsHigh correlation
번호 is highly overall correlated with 행정 구역(읍-면-동) and 2 other fieldsHigh correlation
수령 is highly overall correlated with 행정 구역(읍-면-동) and 3 other fieldsHigh correlation
위도 is highly overall correlated with 행정 구역(읍-면-동) and 1 other fieldsHigh correlation
경도 is highly overall correlated with 행정 구역(읍-면-동) and 2 other fieldsHigh correlation
관리상태 is highly imbalanced (99.9%)Imbalance
관리 기관 is highly imbalanced (96.3%)Imbalance
수령 has 9010 (90.1%) missing valuesMissing
번호 has unique valuesUnique

Reproduction

Analysis started2024-03-14 12:43:38.979717
Analysis finished2024-03-14 12:43:45.635038
Duration6.66 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

번호
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct10000
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean30285.955
Minimum2
Maximum60342
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-03-14T21:43:45.842356image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum2
5-th percentile3034.9
Q115338
median30081
Q345511.25
95-th percentile57369.75
Maximum60342
Range60340
Interquartile range (IQR)30173.25

Descriptive statistics

Standard deviation17436.694
Coefficient of variation (CV)0.57573531
Kurtosis-1.2013292
Mean30285.955
Median Absolute Deviation (MAD)15106.5
Skewness-0.0078093705
Sum3.0285955 × 108
Variance3.0403829 × 108
MonotonicityNot monotonic
2024-03-14T21:43:46.276149image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
25703 1
 
< 0.1%
30428 1
 
< 0.1%
15536 1
 
< 0.1%
36967 1
 
< 0.1%
42420 1
 
< 0.1%
30956 1
 
< 0.1%
2634 1
 
< 0.1%
45503 1
 
< 0.1%
57483 1
 
< 0.1%
34511 1
 
< 0.1%
Other values (9990) 9990
99.9%
ValueCountFrequency (%)
2 1
< 0.1%
13 1
< 0.1%
26 1
< 0.1%
30 1
< 0.1%
35 1
< 0.1%
42 1
< 0.1%
44 1
< 0.1%
46 1
< 0.1%
54 1
< 0.1%
58 1
< 0.1%
ValueCountFrequency (%)
60342 1
< 0.1%
60337 1
< 0.1%
60311 1
< 0.1%
60307 1
< 0.1%
60303 1
< 0.1%
60295 1
< 0.1%
60294 1
< 0.1%
60288 1
< 0.1%
60284 1
< 0.1%
60266 1
< 0.1%

가로수 노선
Text

Distinct260
Distinct (%)2.6%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2024-03-14T21:43:47.209795image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length19
Median length17
Mean length7.5165
Min length3

Characters and Unicode

Total characters75165
Distinct characters128
Distinct categories7 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique166 ?
Unique (%)1.7%

Sample

1st row10호 (정배-서후)
2nd row4호(부리-곡수)
3rd row3호 (아신-용천)
4th row10호 (정배-서후)
5th row용문면
ValueCountFrequency (%)
강하면 1054
 
6.9%
지평면 935
 
6.2%
용문면 715
 
4.7%
강상 508
 
3.3%
양동면 472
 
3.1%
병산리-교평리 440
 
2.9%
341호 405
 
2.7%
중원-곡수 405
 
2.7%
청운면 382
 
2.5%
석산-덕수 344
 
2.3%
Other values (287) 9524
62.7%
2024-03-14T21:43:48.575237image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
6893
 
9.2%
면 4781
 
6.4%
) 4577
 
6.1%
( 4577
 
6.1%
- 4069
 
5.4%
호 3893
 
5.2%
3 2398
 
3.2%
리 2337
 
3.1%
강 2001
 
2.7%
수 1784
 
2.4%
Other values (118) 37855
50.4%

Most occurring categories

ValueCountFrequency (%)
Other Letter 45288
60.3%
Decimal Number 9626
 
12.8%
Space Separator 6893
 
9.2%
Close Punctuation 4577
 
6.1%
Open Punctuation 4577
 
6.1%
Dash Punctuation 4069
 
5.4%
Math Symbol 135
 
0.2%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
면 4781
 
10.6%
호 3893
 
8.6%
리 2337
 
5.2%
강 2001
 
4.4%
수 1784
 
3.9%
평 1694
 
3.7%
양 1605
 
3.5%
지 1390
 
3.1%
운 1163
 
2.6%
하 1076
 
2.4%
Other values (103) 23564
52.0%
Decimal Number
ValueCountFrequency (%)
3 2398
24.9%
4 1440
15.0%
1 1438
14.9%
5 838
 
8.7%
2 709
 
7.4%
8 663
 
6.9%
0 620
 
6.4%
7 586
 
6.1%
6 572
 
5.9%
9 362
 
3.8%
Space Separator
ValueCountFrequency (%)
6893
100.0%
Close Punctuation
ValueCountFrequency (%)
) 4577
100.0%
Open Punctuation
ValueCountFrequency (%)
( 4577
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 4069
100.0%
Math Symbol
ValueCountFrequency (%)
~ 135
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 45288
60.3%
Common 29877
39.7%

Most frequent character per script

Hangul
ValueCountFrequency (%)
면 4781
 
10.6%
호 3893
 
8.6%
리 2337
 
5.2%
강 2001
 
4.4%
수 1784
 
3.9%
평 1694
 
3.7%
양 1605
 
3.5%
지 1390
 
3.1%
운 1163
 
2.6%
하 1076
 
2.4%
Other values (103) 23564
52.0%
Common
ValueCountFrequency (%)
6893
23.1%
) 4577
15.3%
( 4577
15.3%
- 4069
13.6%
3 2398
 
8.0%
4 1440
 
4.8%
1 1438
 
4.8%
5 838
 
2.8%
2 709
 
2.4%
8 663
 
2.2%
Other values (5) 2275
 
7.6%

Most occurring blocks

ValueCountFrequency (%)
Hangul 45288
60.3%
ASCII 29877
39.7%

Most frequent character per block

ASCII
ValueCountFrequency (%)
6893
23.1%
) 4577
15.3%
( 4577
15.3%
- 4069
13.6%
3 2398
 
8.0%
4 1440
 
4.8%
1 1438
 
4.8%
5 838
 
2.8%
2 709
 
2.4%
8 663
 
2.2%
Other values (5) 2275
 
7.6%
Hangul
ValueCountFrequency (%)
면 4781
 
10.6%
호 3893
 
8.6%
리 2337
 
5.2%
강 2001
 
4.4%
수 1784
 
3.9%
평 1694
 
3.7%
양 1605
 
3.5%
지 1390
 
3.1%
운 1163
 
2.6%
하 1076
 
2.4%
Other values (103) 23564
52.0%

행정 구역(읍-면-동)
Categorical

HIGH CORRELATION 

Distinct17
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
지평면
1763 
강하면
1229 
용문면
1103 
양동면
759 
개군면
734 
Other values (12)
4412 

Length

Max length13
Median length3
Mean length3.057
Min length3

Unique

Unique1 ?
Unique (%)< 0.1%

Sample

1st row서종면
2nd row개군면
3rd row옥천면
4th row서종면
5th row용문면

Common Values

ValueCountFrequency (%)
지평면 1763
17.6%
강하면 1229
12.3%
용문면 1103
11.0%
양동면 759
7.6%
개군면 734
7.3%
양평읍 681
 
6.8%
옥천면 656
 
6.6%
강상면 633
 
6.3%
청운면 615
 
6.2%
서종면 567
 
5.7%
Other values (7) 1260
12.6%

Length

2024-03-14T21:43:48.987204image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
지평면 1763
17.6%
강하면 1229
12.3%
용문면 1185
11.8%
청운면 789
7.9%
양동면 759
7.6%
개군면 734
7.3%
양평읍 698
 
7.0%
단월면 684
 
6.8%
옥천면 656
 
6.6%
강상면 633
 
6.3%
Other values (2) 870
8.7%

가로수길 시작점
Text

Distinct541
Distinct (%)5.4%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2024-03-14T21:43:50.232105image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length21
Median length15
Mean length11.7629
Min length3

Characters and Unicode

Total characters117629
Distinct characters124
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

Unique209 ?
Unique (%)2.1%

Sample

1st row서종면 정배리 산104-5
2nd row개군면 향리 14-1
3rd row용천리 1019
4th row서종면 정배리 산104-5
5th row용문면 삼성리 66-5
ValueCountFrequency (%)
지평면 1062
 
3.9%
강하면 1060
 
3.9%
용문면 948
 
3.5%
강상면 599
 
2.2%
양평읍 587
 
2.2%
운심리 561
 
2.1%
서종면 506
 
1.9%
곡수리 493
 
1.8%
송현리 470
 
1.7%
58-3 446
 
1.6%
Other values (617) 20306
75.1%
2024-03-14T21:43:52.003766image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
18366
 
15.6%
리 9359
 
8.0%
1 7981
 
6.8%
- 7764
 
6.6%
면 5877
 
5.0%
2 4973
 
4.2%
3 4367
 
3.7%
5 3690
 
3.1%
4 3674
 
3.1%
6 3374
 
2.9%
Other values (114) 48204
41.0%

Most occurring categories

ValueCountFrequency (%)
Other Letter 53432
45.4%
Decimal Number 38065
32.4%
Space Separator 18366
 
15.6%
Dash Punctuation 7764
 
6.6%
Other Punctuation 2
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
리 9359
 
17.5%
면 5877
 
11.0%
평 2531
 
4.7%
양 1891
 
3.5%
산 1882
 
3.5%
용 1690
 
3.2%
강 1660
 
3.1%
지 1384
 
2.6%
하 1266
 
2.4%
운 1253
 
2.3%
Other values (101) 24639
46.1%
Decimal Number
ValueCountFrequency (%)
1 7981
21.0%
2 4973
13.1%
3 4367
11.5%
5 3690
9.7%
4 3674
9.7%
6 3374
8.9%
0 2771
 
7.3%
8 2529
 
6.6%
7 2478
 
6.5%
9 2228
 
5.9%
Space Separator
ValueCountFrequency (%)
18366
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 7764
100.0%
Other Punctuation
ValueCountFrequency (%)
. 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 64197
54.6%
Hangul 53432
45.4%

Most frequent character per script

Hangul
ValueCountFrequency (%)
리 9359
 
17.5%
면 5877
 
11.0%
평 2531
 
4.7%
양 1891
 
3.5%
산 1882
 
3.5%
용 1690
 
3.2%
강 1660
 
3.1%
지 1384
 
2.6%
하 1266
 
2.4%
운 1253
 
2.3%
Other values (101) 24639
46.1%
Common
ValueCountFrequency (%)
18366
28.6%
1 7981
12.4%
- 7764
12.1%
2 4973
 
7.7%
3 4367
 
6.8%
5 3690
 
5.7%
4 3674
 
5.7%
6 3374
 
5.3%
0 2771
 
4.3%
8 2529
 
3.9%
Other values (3) 4708
 
7.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 64197
54.6%
Hangul 53432
45.4%

Most frequent character per block

ASCII
ValueCountFrequency (%)
18366
28.6%
1 7981
12.4%
- 7764
12.1%
2 4973
 
7.7%
3 4367
 
6.8%
5 3690
 
5.7%
4 3674
 
5.7%
6 3374
 
5.3%
0 2771
 
4.3%
8 2529
 
3.9%
Other values (3) 4708
 
7.3%
Hangul
ValueCountFrequency (%)
리 9359
 
17.5%
면 5877
 
11.0%
평 2531
 
4.7%
양 1891
 
3.5%
산 1882
 
3.5%
용 1690
 
3.2%
강 1660
 
3.1%
지 1384
 
2.6%
하 1266
 
2.4%
운 1253
 
2.3%
Other values (101) 24639
46.1%

가로수길 종점
Text

Distinct531
Distinct (%)5.3%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2024-03-14T21:43:53.212461image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length22
Median length17
Mean length11.5313
Min length3

Characters and Unicode

Total characters115313
Distinct characters120
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

Unique206 ?
Unique (%)2.1%

Sample

1st row서종면 서후리 159-9
2nd row지평면 수곡리1181
3rd row용천리 949
4th row서종면 서후리 159-9
5th row용문면 삼성리 826-2
ValueCountFrequency (%)
지평면 1268
 
4.6%
강하면 963
 
3.5%
용문면 948
 
3.5%
곡수리 699
 
2.6%
성덕리 621
 
2.3%
강상면 510
 
1.9%
양평읍 466
 
1.7%
개군면 459
 
1.7%
402 446
 
1.6%
용천리 435
 
1.6%
Other values (610) 20478
75.0%
2024-03-14T21:43:54.699861image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
18637
 
16.2%
리 9736
 
8.4%
- 6859
 
5.9%
면 6075
 
5.3%
1 5587
 
4.8%
4 4443
 
3.9%
3 4441
 
3.9%
2 4388
 
3.8%
5 3901
 
3.4%
0 2732
 
2.4%
Other values (110) 48514
42.1%

Most occurring categories

ValueCountFrequency (%)
Other Letter 54202
47.0%
Decimal Number 35611
30.9%
Space Separator 18637
 
16.2%
Dash Punctuation 6859
 
5.9%
Other Punctuation 4
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
리 9736
 
18.0%
면 6075
 
11.2%
평 2647
 
4.9%
산 2178
 
4.0%
양 1847
 
3.4%
용 1544
 
2.8%
수 1501
 
2.8%
강 1486
 
2.7%
지 1477
 
2.7%
덕 1228
 
2.3%
Other values (97) 24483
45.2%
Decimal Number
ValueCountFrequency (%)
1 5587
15.7%
4 4443
12.5%
3 4441
12.5%
2 4388
12.3%
5 3901
11.0%
0 2732
7.7%
6 2682
7.5%
9 2578
7.2%
7 2508
7.0%
8 2351
6.6%
Space Separator
ValueCountFrequency (%)
18637
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 6859
100.0%
Other Punctuation
ValueCountFrequency (%)
. 4
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 61111
53.0%
Hangul 54202
47.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
리 9736
 
18.0%
면 6075
 
11.2%
평 2647
 
4.9%
산 2178
 
4.0%
양 1847
 
3.4%
용 1544
 
2.8%
수 1501
 
2.8%
강 1486
 
2.7%
지 1477
 
2.7%
덕 1228
 
2.3%
Other values (97) 24483
45.2%
Common
ValueCountFrequency (%)
18637
30.5%
- 6859
 
11.2%
1 5587
 
9.1%
4 4443
 
7.3%
3 4441
 
7.3%
2 4388
 
7.2%
5 3901
 
6.4%
0 2732
 
4.5%
6 2682
 
4.4%
9 2578
 
4.2%
Other values (3) 4863
 
8.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 61111
53.0%
Hangul 54202
47.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
18637
30.5%
- 6859
 
11.2%
1 5587
 
9.1%
4 4443
 
7.3%
3 4441
 
7.3%
2 4388
 
7.2%
5 3901
 
6.4%
0 2732
 
4.5%
6 2682
 
4.4%
9 2578
 
4.2%
Other values (3) 4863
 
8.0%
Hangul
ValueCountFrequency (%)
리 9736
 
18.0%
면 6075
 
11.2%
평 2647
 
4.9%
산 2178
 
4.0%
양 1847
 
3.4%
용 1544
 
2.8%
수 1501
 
2.8%
강 1486
 
2.7%
지 1477
 
2.7%
덕 1228
 
2.3%
Other values (97) 24483
45.2%

가로수 고유번호
Text

Distinct9824
Distinct (%)98.2%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2024-03-14T21:43:55.657554image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length24
Median length22
Mean length19.4293
Min length11

Characters and Unicode

Total characters194293
Distinct characters125
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

Unique9651 ?
Unique (%)96.5%

Sample

1st row서종면_정배리 산104-5_나_022
2nd row개군면_향리14-1_가_012
3rd row옥천면_용천리 1019_가_330
4th row서종면_정배리 산104-5_나_237
5th row용문면_삼성리 66-5_나_098
ValueCountFrequency (%)
강하면 1606
 
7.4%
운심리 561
 
2.6%
지평면_곡수리 492
 
2.3%
지평면_송현리 470
 
2.2%
옥천면_용천리 417
 
1.9%
단월면_석산리 411
 
1.9%
서종면_서종면 296
 
1.4%
왕창리 251
 
1.2%
지평면_지평로 241
 
1.1%
용문면_마룡리 215
 
1.0%
Other values (9901) 16633
77.0%
2024-03-14T21:43:56.865847image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
_ 30327
 
15.6%
1 12707
 
6.5%
11614
 
6.0%
면 10663
 
5.5%
0 10046
 
5.2%
리 9342
 
4.8%
2 8558
 
4.4%
- 7656
 
3.9%
3 7152
 
3.7%
4 6143
 
3.2%
Other values (115) 80085
41.2%

Most occurring categories

ValueCountFrequency (%)
Other Letter 76725
39.5%
Decimal Number 67969
35.0%
Connector Punctuation 30327
 
15.6%
Space Separator 11614
 
6.0%
Dash Punctuation 7656
 
3.9%
Other Punctuation 2
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
면 10663
 
13.9%
리 9342
 
12.2%
가 5111
 
6.7%
나 4700
 
6.1%
평 3309
 
4.3%
강 2923
 
3.8%
하 2495
 
3.3%
양 2429
 
3.2%
지 2127
 
2.8%
용 1909
 
2.5%
Other values (101) 31717
41.3%
Decimal Number
ValueCountFrequency (%)
1 12707
18.7%
0 10046
14.8%
2 8558
12.6%
3 7152
10.5%
4 6143
9.0%
5 5733
8.4%
6 5127
7.5%
8 4303
 
6.3%
7 4267
 
6.3%
9 3933
 
5.8%
Connector Punctuation
ValueCountFrequency (%)
_ 30327
100.0%
Space Separator
ValueCountFrequency (%)
11614
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 7656
100.0%
Other Punctuation
ValueCountFrequency (%)
. 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 117568
60.5%
Hangul 76725
39.5%

Most frequent character per script

Hangul
ValueCountFrequency (%)
면 10663
 
13.9%
리 9342
 
12.2%
가 5111
 
6.7%
나 4700
 
6.1%
평 3309
 
4.3%
강 2923
 
3.8%
하 2495
 
3.3%
양 2429
 
3.2%
지 2127
 
2.8%
용 1909
 
2.5%
Other values (101) 31717
41.3%
Common
ValueCountFrequency (%)
_ 30327
25.8%
1 12707
10.8%
11614
 
9.9%
0 10046
 
8.5%
2 8558
 
7.3%
- 7656
 
6.5%
3 7152
 
6.1%
4 6143
 
5.2%
5 5733
 
4.9%
6 5127
 
4.4%
Other values (4) 12505
10.6%

Most occurring blocks

ValueCountFrequency (%)
ASCII 117568
60.5%
Hangul 76725
39.5%

Most frequent character per block

ASCII
ValueCountFrequency (%)
_ 30327
25.8%
1 12707
10.8%
11614
 
9.9%
0 10046
 
8.5%
2 8558
 
7.3%
- 7656
 
6.5%
3 7152
 
6.1%
4 6143
 
5.2%
5 5733
 
4.9%
6 5127
 
4.4%
Other values (4) 12505
10.6%
Hangul
ValueCountFrequency (%)
면 10663
 
13.9%
리 9342
 
12.2%
가 5111
 
6.7%
나 4700
 
6.1%
평 3309
 
4.3%
강 2923
 
3.8%
하 2495
 
3.3%
양 2429
 
3.2%
지 2127
 
2.8%
용 1909
 
2.5%
Other values (101) 31717
41.3%

수종
Categorical

HIGH CORRELATION 

Distinct27
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
벚나무
3294 
이팝나무
1484 
은행나무
1434 
산수유나무
889 
단풍나무
737 
Other values (22)
2162 

Length

Max length9
Median length6
Mean length3.735
Min length2

Unique

Unique3 ?
Unique (%)< 0.1%

Sample

1st row매화나무
2nd row이팝나무
3rd row벚나무
4th row매화나무
5th row은행나무

Common Values

ValueCountFrequency (%)
벚나무 3294
32.9%
이팝나무 1484
14.8%
은행나무 1434
14.3%
산수유나무 889
 
8.9%
단풍나무 737
 
7.4%
매화나무 468
 
4.7%
소나무 308
 
3.1%
무궁화 298
 
3.0%
살구나무 276
 
2.8%
벚나무 165
 
1.7%
Other values (17) 647
 
6.5%

Length

2024-03-14T21:43:57.106024image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
벚나무 3459
34.3%
은행나무 1525
15.1%
이팝나무 1484
14.7%
산수유나무 889
 
8.8%
단풍나무 737
 
7.3%
매화나무 468
 
4.6%
소나무 372
 
3.7%
무궁화 298
 
3.0%
살구나무 282
 
2.8%
벗나무 143
 
1.4%
Other values (12) 440
 
4.4%

수고(m)
Categorical

HIGH CORRELATION 

Distinct43
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
4.5
1068 
7
873 
8
697 
6
 
609
6.5
 
593
Other values (38)
6160 

Length

Max length4
Median length3
Mean length2.323
Min length1

Unique

Unique1 ?
Unique (%)< 0.1%

Sample

1st row3.7
2nd row3.3
3rd row7.6
4th row3.7
5th row6

Common Values

ValueCountFrequency (%)
4.5 1068
 
10.7%
7 873
 
8.7%
8 697
 
7.0%
6 609
 
6.1%
6.5 593
 
5.9%
7.7 577
 
5.8%
5 551
 
5.5%
3.5 475
 
4.8%
7.2 472
 
4.7%
7.6 445
 
4.5%
Other values (33) 3640
36.4%

Length

2024-03-14T21:43:57.420996image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
4.5 1068
 
10.7%
7 873
 
8.7%
8 697
 
7.0%
6 609
 
6.1%
6.5 593
 
5.9%
7.7 577
 
5.8%
5 551
 
5.5%
3.5 475
 
4.8%
7.2 472
 
4.7%
7.6 445
 
4.5%
Other values (33) 3640
36.4%

수령
Real number (ℝ)

HIGH CORRELATION  MISSING 

Distinct6
Distinct (%)0.6%
Missing9010
Missing (%)90.1%
Infinite0
Infinite (%)0.0%
Mean7.820202
Minimum5
Maximum10
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-03-14T21:43:57.612559image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum5
5-th percentile6
Q17
median8
Q38
95-th percentile9
Maximum10
Range5
Interquartile range (IQR)1

Descriptive statistics

Standard deviation0.87661217
Coefficient of variation (CV)0.11209585
Kurtosis-0.500873
Mean7.820202
Median Absolute Deviation (MAD)1
Skewness-0.057617563
Sum7742
Variance0.7684489
MonotonicityNot monotonic
2024-03-14T21:43:57.806674image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=6)
ValueCountFrequency (%)
8 398
 
4.0%
7 309
 
3.1%
9 218
 
2.2%
6 53
 
0.5%
10 11
 
0.1%
5 1
 
< 0.1%
(Missing) 9010
90.1%
ValueCountFrequency (%)
5 1
 
< 0.1%
6 53
 
0.5%
7 309
3.1%
8 398
4.0%
9 218
2.2%
10 11
 
0.1%
ValueCountFrequency (%)
10 11
 
0.1%
9 218
2.2%
8 398
4.0%
7 309
3.1%
6 53
 
0.5%
5 1
 
< 0.1%

피해여부
Boolean

CONSTANT 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size87.9 KiB
False
10000 
ValueCountFrequency (%)
False 10000
100.0%
2024-03-14T21:43:57.967224image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

관리상태
Categorical

IMBALANCE 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
<NA>
9999 
0
 
1

Length

Max length4
Median length4
Mean length3.9997
Min length1

Unique

Unique1 ?
Unique (%)< 0.1%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 9999
> 99.9%
0 1
 
< 0.1%

Length

2024-03-14T21:43:58.141342image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-14T21:43:58.312293image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 9999
> 99.9%
0 1
 
< 0.1%

관리 기관
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
양평군 정원산림과
9961 
<NA>
 
39

Length

Max length9
Median length9
Mean length8.9805
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row양평군 정원산림과
2nd row양평군 정원산림과
3rd row양평군 정원산림과
4th row양평군 정원산림과
5th row양평군 정원산림과

Common Values

ValueCountFrequency (%)
양평군 정원산림과 9961
99.6%
<NA> 39
 
0.4%

Length

2024-03-14T21:43:58.576273image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-14T21:43:58.741070image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
양평군 9961
49.9%
정원산림과 9961
49.9%
na 39
 
0.2%

위도
Real number (ℝ)

HIGH CORRELATION 

Distinct9385
Distinct (%)94.2%
Missing39
Missing (%)0.4%
Infinite0
Infinite (%)0.0%
Mean37.497193
Minimum37.369849
Maximum37.650177
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-03-14T21:43:58.931134image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum37.369849
5-th percentile37.420249
Q137.453526
median37.486641
Q337.539418
95-th percentile37.607152
Maximum37.650177
Range0.280328
Interquartile range (IQR)0.085892

Descriptive statistics

Standard deviation0.058004511
Coefficient of variation (CV)0.0015469027
Kurtosis-0.37202609
Mean37.497193
Median Absolute Deviation (MAD)0.040227
Skewness0.55426227
Sum373509.54
Variance0.0033645233
MonotonicityNot monotonic
2024-03-14T21:43:59.182399image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
37.572651 20
 
0.2%
37.558886 7
 
0.1%
37.442584 4
 
< 0.1%
37.50468 4
 
< 0.1%
37.501977 4
 
< 0.1%
37.42749 4
 
< 0.1%
37.55207 4
 
< 0.1%
37.427406 4
 
< 0.1%
37.605143 4
 
< 0.1%
37.464676 3
 
< 0.1%
Other values (9375) 9903
99.0%
(Missing) 39
 
0.4%
ValueCountFrequency (%)
37.369849 1
< 0.1%
37.371487 1
< 0.1%
37.371721 1
< 0.1%
37.374061 1
< 0.1%
37.374412 1
< 0.1%
37.375348 1
< 0.1%
37.375582 1
< 0.1%
37.376401 1
< 0.1%
37.376635 1
< 0.1%
37.376752 1
< 0.1%
ValueCountFrequency (%)
37.650177 2
< 0.1%
37.649684 1
< 0.1%
37.648907 1
< 0.1%
37.648895 1
< 0.1%
37.648886 1
< 0.1%
37.648877 1
< 0.1%
37.648869 1
< 0.1%
37.648803 1
< 0.1%
37.648718 1
< 0.1%
37.648499 1
< 0.1%

경도
Real number (ℝ)

HIGH CORRELATION 

Distinct9402
Distinct (%)94.4%
Missing39
Missing (%)0.4%
Infinite0
Infinite (%)0.0%
Mean127.56529
Minimum127.31782
Maximum127.78872
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-03-14T21:43:59.445225image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum127.31782
5-th percentile127.39427
Q1127.47643
median127.58566
Q3127.63749
95-th percentile127.75007
Maximum127.78872
Range0.470893
Interquartile range (IQR)0.161055

Descriptive statistics

Standard deviation0.11481187
Coefficient of variation (CV)0.00090002439
Kurtosis-1.036745
Mean127.56529
Median Absolute Deviation (MAD)0.096149
Skewness-0.040295699
Sum1270677.8
Variance0.013181765
MonotonicityNot monotonic
2024-03-14T21:44:00.058857image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
127.513037 8
 
0.1%
127.631992 5
 
0.1%
127.326511 5
 
0.1%
127.540188 4
 
< 0.1%
127.390863 4
 
< 0.1%
127.396501 4
 
< 0.1%
127.610645 4
 
< 0.1%
127.604582 3
 
< 0.1%
127.682649 3
 
< 0.1%
127.477242 3
 
< 0.1%
Other values (9392) 9918
99.2%
(Missing) 39
 
0.4%
ValueCountFrequency (%)
127.317824 3
< 0.1%
127.31784 1
 
< 0.1%
127.317863 1
 
< 0.1%
127.319757 2
< 0.1%
127.319811 1
 
< 0.1%
127.319864 1
 
< 0.1%
127.320888 1
 
< 0.1%
127.321029 1
 
< 0.1%
127.32106 1
 
< 0.1%
127.321128 1
 
< 0.1%
ValueCountFrequency (%)
127.788717 1
< 0.1%
127.787976 1
< 0.1%
127.786918 1
< 0.1%
127.786516 1
< 0.1%
127.780838 1
< 0.1%
127.780759 1
< 0.1%
127.780713 1
< 0.1%
127.780531 1
< 0.1%
127.780521 1
< 0.1%
127.780371 1
< 0.1%

가로수 수량
Categorical

CONSTANT 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
1
10000 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row1
2nd row1
3rd row1
4th row1
5th row1

Common Values

ValueCountFrequency (%)
1 10000
100.0%

Length

2024-03-14T21:44:00.463624image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-14T21:44:00.757063image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
1 10000
100.0%

Interactions

2024-03-14T21:43:43.709460image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T21:43:40.804689image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T21:43:42.040462image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T21:43:42.986682image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T21:43:43.885662image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T21:43:41.069903image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T21:43:42.299325image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T21:43:43.157563image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T21:43:44.043550image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T21:43:41.304492image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T21:43:42.449851image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T21:43:43.298280image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T21:43:44.211045image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T21:43:41.771200image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T21:43:42.709435image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T21:43:43.540826image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-03-14T21:44:00.937276image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
번호행정 구역(읍-면-동)수종수고(m)수령위도경도
번호1.0000.8870.7940.9100.7310.7690.833
행정 구역(읍-면-동)0.8871.0000.9190.9220.7650.8380.922
수종0.7940.9191.0000.9370.8080.6960.776
수고(m)0.9100.9220.9371.0000.8710.8210.876
수령0.7310.7650.8080.8711.0000.5060.687
위도0.7690.8380.6960.8210.5061.0000.719
경도0.8330.9220.7760.8760.6870.7191.000
2024-03-14T21:44:01.225807image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
관리상태수종행정 구역(읍-면-동)수고(m)관리 기관
관리상태1.000NaNNaNNaNNaN
수종NaN1.0000.5620.5021.000
행정 구역(읍-면-동)NaN0.5621.0000.5431.000
수고(m)NaN0.5020.5431.0001.000
관리 기관NaN1.0001.0001.0001.000
2024-03-14T21:44:01.516845image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
번호수령위도경도행정 구역(읍-면-동)수종수고(m)관리상태관리 기관
번호1.000-0.2560.1840.3140.6150.4350.611NaN1.000
수령-0.2561.0000.018-0.1190.5070.5970.6880.0001.000
위도0.1840.0181.000-0.0550.5260.3350.451NaN1.000
경도0.314-0.119-0.0551.0000.7000.4140.539NaN1.000
행정 구역(읍-면-동)0.6150.5070.5260.7001.0000.5620.543NaN1.000
수종0.4350.5970.3350.4140.5621.0000.502NaN1.000
수고(m)0.6110.6880.4510.5390.5430.5021.000NaN1.000
관리상태NaN0.000NaNNaNNaNNaNNaN1.000NaN
관리 기관1.0001.0001.0001.0001.0001.0001.000NaN1.000

Missing values

2024-03-14T21:43:44.448989image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-03-14T21:43:45.001034image/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.
2024-03-14T21:43:45.433020image/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

번호가로수 노선행정 구역(읍-면-동)가로수길 시작점가로수길 종점가로수 고유번호수종수고(m)수령피해여부관리상태관리 기관위도경도가로수 수량
257022570310호 (정배-서후)서종면서종면 정배리 산104-5서종면 서후리 159-9서종면_정배리 산104-5_나_022매화나무3.7<NA>N<NA>양평군 정원산림과37.595431127.4258121
14594145954호(부리-곡수)개군면개군면 향리 14-1지평면 수곡리1181개군면_향리14-1_가_012이팝나무3.38N<NA>양평군 정원산림과37.427496127.5401211
46401464023호 (아신-용천)옥천면용천리 1019용천리 949옥천면_용천리 1019_가_330벚나무7.6<NA>N<NA>양평군 정원산림과37.557257127.5033431
259172591810호 (정배-서후)서종면서종면 정배리 산104-5서종면 서후리 159-9서종면_정배리 산104-5_나_237매화나무3.7<NA>N<NA>양평군 정원산림과37.582224127.4263771
4425744258용문면용문면용문면 삼성리 66-5용문면 삼성리 826-2용문면_삼성리 66-5_나_098은행나무6<NA>N<NA>양평군 정원산림과37.474926127.574521
3721437215옥천면 5번옥천면옥천면 옥천리 594-19옥천면 용천리 875-2옥천면_옥천리 594-19_가_074매화나무3.58N<NA>양평군 정원산림과37.529576127.4791911
2507925080391호 (문호-양서)양서면서종면 문호리 342양서면 건지미길 4서종면_서종면 문호리 342_가_205벚나무8.3<NA>N<NA>양평군 정원산림과37.579331127.3378681
3574235743개군면개군면양평읍 회현리 620-3양평읍 원덕리 원덕흑천길 107개군면_양평읍 회현리 620-3_가_144산수유나무5<NA>N<NA>양평군 정원산림과37.46723127.5410021
299742997586호(수입-노문)서종면수입리 442-27노문리 산73-4서종면_수입리 442-27_나_255벚나무8.2<NA>N<NA>양평군 정원산림과37.647788127.4207081
2243022431망미-곡수지평면망미리 870-9곡수리 605-6지평면 망미리 870-9_나_130무궁화나무5.5<NA>N<NA>양평군 정원산림과37.428769127.6373221
번호가로수 노선행정 구역(읍-면-동)가로수길 시작점가로수길 종점가로수 고유번호수종수고(m)수령피해여부관리상태관리 기관위도경도가로수 수량
40503405046호 (양수-갈운)청운면용두리 155-2용두리 108-5청운면_용두리 155-2_나_010은행나무7.4<NA>N<NA>양평군 정원산림과37.545529127.7324011
1855918560양동면양동면금왕리 10금왕리 84-1양동면_금왕리 10_나_003벚나무6.5<NA>N<NA>양평군 정원산림과37.49703127.7451611
256862568710호 (정배-서후)서종면서종면 정배리 산104-5서종면 서후리 159-9서종면_정배리 산104-5_나_006매화나무3.7<NA>N<NA>양평군 정원산림과37.595494127.4259551
5770057701청운 신론리 610-25번지청운면청운면 신론리 610-25청운면 삼성리 744-33청운면_신론리_610-25_나_135벗나무8<NA>N<NA>양평군 정원산림과37.570006127.7500651
5204652047지평면지평면지평면 송현리 879지평면 곡수리 380-1지평면_송현리 879_가_395이팝나무4.5<NA>N<NA>양평군 정원산림과37.440928127.6216421
3551635517개군면개군면양평읍 회현리 620-3상자포리 141개군면_양평읍 회현리 620-3_가_056매화나무3.58N<NA>양평군 정원산림과37.465041127.5239891
5050650507지평면지평면지평면 곡수리 565-13지평면 일신리 267-1지평면_곡수리 565-13_나_138이팝나무4.5<NA>N<NA>양평군 정원산림과37.428271127.6372761
4951449515지평면지평면지평면 곡수길91지평면 옥현리 산75-3지평면_곡수길91_가_273이팝나무4.5<NA>N<NA>양평군 정원산림과37.420297127.6153651
3160631607석장2리-앙덕개군면앙덕리 산2-11개군면 앙덕리 산3개군면_앙덕리 산2-11_나010매화나무3.29N<NA>양평군 정원산림과37.443917127.5161481
3237232373양동면양동면양동면 고송리 822-1양동면 단석리 산90양동면_고송리 822-1_나_035매화나무3.59N<NA>양평군 정원산림과37.483198127.7061251