Overview

Dataset statistics

Number of variables6
Number of observations597
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory29.3 KiB
Average record size in memory50.2 B

Variable types

Numeric2
Categorical3
Text1

Dataset

Description서울특별시 종로구가 소유한 공유 재산 현황에 관한 데이터로 소유한 구유지의 소재지, 토지지목코드, 해당 면적 등에 대한 자료를 제공합니다.
Author서울특별시 종로구
URLhttps://www.data.go.kr/data/15021673/fileData.do

Alerts

재산용도코드 has constant value ""Constant
재산관리관 is highly imbalanced (91.8%)Imbalance
지목 is highly imbalanced (78.4%)Imbalance
순번 has unique valuesUnique
소재지 has unique valuesUnique

Reproduction

Analysis started2023-12-12 15:09:41.527402
Analysis finished2023-12-12 15:09:42.527695
Duration1 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

순번
Real number (ℝ)

UNIQUE 

Distinct597
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean299
Minimum1
Maximum597
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size5.4 KiB
2023-12-13T00:09:43.018721image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile30.8
Q1150
median299
Q3448
95-th percentile567.2
Maximum597
Range596
Interquartile range (IQR)298

Descriptive statistics

Standard deviation172.48333
Coefficient of variation (CV)0.57686733
Kurtosis-1.2
Mean299
Median Absolute Deviation (MAD)149
Skewness0
Sum178503
Variance29750.5
MonotonicityStrictly increasing
2023-12-13T00:09:43.207375image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 1
 
0.2%
394 1
 
0.2%
396 1
 
0.2%
397 1
 
0.2%
398 1
 
0.2%
399 1
 
0.2%
400 1
 
0.2%
401 1
 
0.2%
402 1
 
0.2%
403 1
 
0.2%
Other values (587) 587
98.3%
ValueCountFrequency (%)
1 1
0.2%
2 1
0.2%
3 1
0.2%
4 1
0.2%
5 1
0.2%
6 1
0.2%
7 1
0.2%
8 1
0.2%
9 1
0.2%
10 1
0.2%
ValueCountFrequency (%)
597 1
0.2%
596 1
0.2%
595 1
0.2%
594 1
0.2%
593 1
0.2%
592 1
0.2%
591 1
0.2%
590 1
0.2%
589 1
0.2%
588 1
0.2%

재산용도코드
Categorical

CONSTANT 

Distinct1
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size4.8 KiB
03-일반재산
597 

Length

Max length7
Median length7
Mean length7
Min length7

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row03-일반재산
2nd row03-일반재산
3rd row03-일반재산
4th row03-일반재산
5th row03-일반재산

Common Values

ValueCountFrequency (%)
03-일반재산 597
100.0%

Length

2023-12-13T00:09:43.395416image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T00:09:43.514292image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
03-일반재산 597
100.0%

재산관리관
Categorical

IMBALANCE 

Distinct3
Distinct (%)0.5%
Missing0
Missing (%)0.0%
Memory size4.8 KiB
재무과
587 
건설교통국 건설관리과
 
9
도시관리국 주거재생과
 
1

Length

Max length11
Median length3
Mean length3.1340034
Min length3

Unique

Unique1 ?
Unique (%)0.2%

Sample

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

Common Values

ValueCountFrequency (%)
재무과 587
98.3%
건설교통국 건설관리과 9
 
1.5%
도시관리국 주거재생과 1
 
0.2%

Length

2023-12-13T00:09:43.643179image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T00:09:43.760676image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
재무과 587
96.7%
건설교통국 9
 
1.5%
건설관리과 9
 
1.5%
도시관리국 1
 
0.2%
주거재생과 1
 
0.2%

소재지
Text

UNIQUE 

Distinct597
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size4.8 KiB
2023-12-13T00:09:44.141878image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length23
Median length22
Mean length20.360134
Min length17

Characters and Unicode

Total characters12155
Distinct characters95
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

Unique597 ?
Unique (%)100.0%

Sample

1st row서울특별시 종로구 청운동 2-72
2nd row서울특별시 종로구 청운동 8-24
3rd row서울특별시 종로구 청운동 8-27
4th row서울특별시 종로구 청운동 38-7
5th row서울특별시 종로구 청운동 121-2
ValueCountFrequency (%)
서울특별시 597
25.0%
종로구 597
25.0%
창신동 147
 
6.2%
숭인동 57
 
2.4%
사직동 45
 
1.9%
평창동 28
 
1.2%
행촌동 27
 
1.1%
구기동 26
 
1.1%
부암동 23
 
1.0%
원서동 18
 
0.8%
Other values (649) 823
34.5%
2023-12-13T00:09:44.744447image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
2388
19.6%
구 623
 
5.1%
서 615
 
5.1%
로 612
 
5.0%
종 611
 
5.0%
울 597
 
4.9%
특 597
 
4.9%
별 597
 
4.9%
시 597
 
4.9%
동 579
 
4.8%
Other values (85) 4339
35.7%

Most occurring categories

ValueCountFrequency (%)
Other Letter 6561
54.0%
Decimal Number 2636
21.7%
Space Separator 2388
 
19.6%
Dash Punctuation 570
 
4.7%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
구 623
9.5%
서 615
9.4%
로 612
9.3%
종 611
9.3%
울 597
9.1%
특 597
9.1%
별 597
9.1%
시 597
9.1%
동 579
8.8%
신 179
 
2.7%
Other values (73) 954
14.5%
Decimal Number
ValueCountFrequency (%)
1 562
21.3%
2 362
13.7%
3 315
11.9%
6 271
10.3%
5 235
8.9%
4 208
 
7.9%
0 200
 
7.6%
7 188
 
7.1%
8 148
 
5.6%
9 147
 
5.6%
Space Separator
ValueCountFrequency (%)
2388
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 570
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 6561
54.0%
Common 5594
46.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
구 623
9.5%
서 615
9.4%
로 612
9.3%
종 611
9.3%
울 597
9.1%
특 597
9.1%
별 597
9.1%
시 597
9.1%
동 579
8.8%
신 179
 
2.7%
Other values (73) 954
14.5%
Common
ValueCountFrequency (%)
2388
42.7%
- 570
 
10.2%
1 562
 
10.0%
2 362
 
6.5%
3 315
 
5.6%
6 271
 
4.8%
5 235
 
4.2%
4 208
 
3.7%
0 200
 
3.6%
7 188
 
3.4%
Other values (2) 295
 
5.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 6561
54.0%
ASCII 5594
46.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
2388
42.7%
- 570
 
10.2%
1 562
 
10.0%
2 362
 
6.5%
3 315
 
5.6%
6 271
 
4.8%
5 235
 
4.2%
4 208
 
3.7%
0 200
 
3.6%
7 188
 
3.4%
Other values (2) 295
 
5.3%
Hangul
ValueCountFrequency (%)
구 623
9.5%
서 615
9.4%
로 612
9.3%
종 611
9.3%
울 597
9.1%
특 597
9.1%
별 597
9.1%
시 597
9.1%
동 579
8.8%
신 179
 
2.7%
Other values (73) 954
14.5%

지목
Categorical

IMBALANCE 

Distinct8
Distinct (%)1.3%
Missing0
Missing (%)0.0%
Memory size4.8 KiB
08-대
543 
14-도로
 
23
01-전
 
10
05-임야
 
7
10-학교용지
 
6
Other values (3)
 
8

Length

Max length7
Median length4
Mean length4.1038526
Min length4

Unique

Unique1 ?
Unique (%)0.2%

Sample

1st row08-대
2nd row08-대
3rd row05-임야
4th row08-대
5th row08-대

Common Values

ValueCountFrequency (%)
08-대 543
91.0%
14-도로 23
 
3.9%
01-전 10
 
1.7%
05-임야 7
 
1.2%
10-학교용지 6
 
1.0%
28-잡종지 4
 
0.7%
18-구거 3
 
0.5%
25-종교용지 1
 
0.2%

Length

2023-12-13T00:09:44.960058image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T00:09:45.129990image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
08-대 543
91.0%
14-도로 23
 
3.9%
01-전 10
 
1.7%
05-임야 7
 
1.2%
10-학교용지 6
 
1.0%
28-잡종지 4
 
0.7%
18-구거 3
 
0.5%
25-종교용지 1
 
0.2%

면적
Real number (ℝ)

Distinct340
Distinct (%)57.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean37.365193
Minimum0.02
Maximum937
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size5.4 KiB
2023-12-13T00:09:45.314834image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0.02
5-th percentile0.7
Q14.6
median14
Q337
95-th percentile144.2
Maximum937
Range936.98
Interquartile range (IQR)32.4

Descriptive statistics

Standard deviation77.639002
Coefficient of variation (CV)2.077843
Kurtosis51.571328
Mean37.365193
Median Absolute Deviation (MAD)11.4
Skewness6.1514255
Sum22307.02
Variance6027.8147
MonotonicityNot monotonic
2023-12-13T00:09:45.537810image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.7 14
 
2.3%
1.0 9
 
1.5%
2.3 7
 
1.2%
0.2 7
 
1.2%
0.8 7
 
1.2%
1.3 7
 
1.2%
3.3 6
 
1.0%
1.7 6
 
1.0%
7.0 5
 
0.8%
6.6 5
 
0.8%
Other values (330) 524
87.8%
ValueCountFrequency (%)
0.02 1
 
0.2%
0.1 2
 
0.3%
0.2 7
1.2%
0.3 2
 
0.3%
0.4 3
 
0.5%
0.5 4
 
0.7%
0.6 3
 
0.5%
0.7 14
2.3%
0.8 7
1.2%
0.9 1
 
0.2%
ValueCountFrequency (%)
937.0 1
0.2%
665.0 1
0.2%
648.9 1
0.2%
628.0 1
0.2%
477.7 1
0.2%
458.0 1
0.2%
337.8 1
0.2%
279.0 1
0.2%
271.7 1
0.2%
255.0 1
0.2%

Interactions

2023-12-13T00:09:42.034200image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T00:09:41.763497image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T00:09:42.157367image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T00:09:41.896393image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-13T00:09:45.658464image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
순번재산관리관지목면적
순번1.0000.0480.3650.197
재산관리관0.0481.0000.0000.000
지목0.3650.0001.0000.242
면적0.1970.0000.2421.000
2023-12-13T00:09:45.761888image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
지목재산관리관
지목1.0000.000
재산관리관0.0001.000
2023-12-13T00:09:45.861565image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
순번면적재산관리관지목
순번1.0000.1900.0280.183
면적0.1901.0000.0000.120
재산관리관0.0280.0001.0000.000
지목0.1830.1200.0001.000

Missing values

2023-12-13T00:09:42.307655image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-13T00:09:42.466118image/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

순번재산용도코드재산관리관소재지지목면적
0103-일반재산재무과서울특별시 종로구 청운동 2-7208-대19.2
1203-일반재산재무과서울특별시 종로구 청운동 8-2408-대143.6
2303-일반재산재무과서울특별시 종로구 청운동 8-2705-임야36.2
3403-일반재산재무과서울특별시 종로구 청운동 38-708-대116.0
4503-일반재산재무과서울특별시 종로구 청운동 121-208-대2.3
5603-일반재산재무과서울특별시 종로구 신교동 1-1208-대112.4
6703-일반재산재무과서울특별시 종로구 신교동 1-1408-대61.8
7803-일반재산재무과서울특별시 종로구 신교동 1-2108-대102.5
8903-일반재산재무과서울특별시 종로구 신교동 1-3008-대161.0
91003-일반재산재무과서울특별시 종로구 신교동 1-3108-대77.0
순번재산용도코드재산관리관소재지지목면적
58758803-일반재산재무과서울특별시 종로구 홍지동 70-408-대106.0
58858903-일반재산재무과서울특별시 종로구 홍지동 70-608-대5.0
58959003-일반재산재무과서울특별시 종로구 홍지동 71-1205-임야23.0
59059103-일반재산재무과서울특별시 종로구 홍지동 79-108-대255.0
59159203-일반재산재무과서울특별시 종로구 신영동 136-908-대937.0
59259303-일반재산건설교통국 건설관리과서울특별시 종로구 신영동 158-2514-도로59.0
59359403-일반재산건설교통국 건설관리과서울특별시 종로구 신영동 158-2714-도로279.0
59459503-일반재산재무과서울특별시 종로구 신영동 172-308-대10.0
59559603-일반재산재무과서울특별시 종로구 신영동 176-1008-대40.0
59659703-일반재산재무과서울특별시 종로구 무악동 46-191708-대9.5