Overview

Dataset statistics

Number of variables8
Number of observations30
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory2.1 KiB
Average record size in memory70.4 B

Variable types

DateTime1
Numeric2
Categorical3
Text2

Dataset

Description샘플 데이터
Author경기신용보증재단
URLhttps://bigdata-region.kr/#/dataset/77075d54-1ede-447c-8fd8-88aa45dd4e4a

Alerts

기준년월 has constant value ""Constant
면적당임차료 is highly overall correlated with 자가여부High correlation
자가여부 is highly overall correlated with 면적당임차료High correlation
관리번호 has unique valuesUnique
주요제품명 has unique valuesUnique
면적당임차료 has 17 (56.7%) zerosZeros

Reproduction

Analysis started2023-12-10 14:15:28.396996
Analysis finished2023-12-10 14:15:31.503574
Duration3.11 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

기준년월
Date

CONSTANT 

Distinct1
Distinct (%)3.3%
Missing0
Missing (%)0.0%
Memory size372.0 B
Minimum2021-10-01 00:00:00
Maximum2021-10-01 00:00:00
2023-12-10T23:15:31.600813image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T23:15:31.858952image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=1)

관리번호
Real number (ℝ)

UNIQUE 

Distinct30
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1.0934098 × 108
Minimum1.0006314 × 108
Maximum1.1000743 × 108
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size402.0 B
2023-12-10T23:15:32.123056image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1.0006314 × 108
5-th percentile1.0453509 × 108
Q11.1000143 × 108
median1.100036 × 108
Q31.1000487 × 108
95-th percentile1.1000737 × 108
Maximum1.1000743 × 108
Range9944294
Interquartile range (IQR)3435.5

Descriptive statistics

Standard deviation2521941
Coefficient of variation (CV)0.02306492
Kurtosis12.206608
Mean1.0934098 × 108
Median Absolute Deviation (MAD)2026.5
Skewness-3.6599937
Sum3.2802295 × 109
Variance6.3601863 × 1012
MonotonicityNot monotonic
2023-12-10T23:15:32.432170image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=30)
ValueCountFrequency (%)
100063139 1
 
3.3%
110001625 1
 
3.3%
110007433 1
 
3.3%
110004857 1
 
3.3%
110007388 1
 
3.3%
110004795 1
 
3.3%
110007346 1
 
3.3%
110004549 1
 
3.3%
110007187 1
 
3.3%
110004413 1
 
3.3%
Other values (20) 20
66.7%
ValueCountFrequency (%)
100063139 1
3.3%
100063564 1
3.3%
110000288 1
3.3%
110000436 1
3.3%
110000933 1
3.3%
110001257 1
3.3%
110001382 1
3.3%
110001387 1
3.3%
110001564 1
3.3%
110001582 1
3.3%
ValueCountFrequency (%)
110007433 1
3.3%
110007388 1
3.3%
110007346 1
3.3%
110007187 1
3.3%
110007001 1
3.3%
110005820 1
3.3%
110005371 1
3.3%
110004870 1
3.3%
110004857 1
3.3%
110004795 1
3.3%

시군명
Categorical

Distinct13
Distinct (%)43.3%
Missing0
Missing (%)0.0%
Memory size372.0 B
평택시
7 
화성시(화성)
4 
포천시(의정부)
3 
고양시
3 
수원시
3 
Other values (8)
10 

Length

Max length8
Median length3
Mean length4.7
Min length3

Unique

Unique6 ?
Unique (%)20.0%

Sample

1st row포천시(의정부)
2nd row평택시
3rd row평택시
4th row고양시
5th row수원시

Common Values

ValueCountFrequency (%)
평택시 7
23.3%
화성시(화성) 4
13.3%
포천시(의정부) 3
10.0%
고양시 3
10.0%
수원시 3
10.0%
안성시 2
 
6.7%
남양주시 2
 
6.7%
안양시 1
 
3.3%
연천시(의정부) 1
 
3.3%
양주시(의정부) 1
 
3.3%
Other values (3) 3
10.0%

Length

2023-12-10T23:15:32.701737image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
평택시 7
23.3%
화성시(화성 4
13.3%
포천시(의정부 3
10.0%
고양시 3
10.0%
수원시 3
10.0%
안성시 2
 
6.7%
남양주시 2
 
6.7%
안양시 1
 
3.3%
연천시(의정부 1
 
3.3%
양주시(의정부 1
 
3.3%
Other values (3) 3
10.0%

업종대분류명
Categorical

Distinct8
Distinct (%)26.7%
Missing0
Missing (%)0.0%
Memory size372.0 B
C 제조업(10~34)
12 
C 제조업 (10 ~ 33)
9 
G 도매 및 소매업 (45~47)
3 
I 숙박 및 음식점업 (55 ~ 56)
2 
J출판;영상;방송통신및정보서비스업(58~63)
 
1
Other values (3)
3 

Length

Max length25
Median length21
Mean length14.8
Min length12

Unique

Unique4 ?
Unique (%)13.3%

Sample

1st rowC 제조업(10~34)
2nd rowC 제조업 (10 ~ 33)
3rd rowC 제조업(10~34)
4th rowG 도매 및 소매업 (45~47)
5th rowJ출판;영상;방송통신및정보서비스업(58~63)

Common Values

ValueCountFrequency (%)
C 제조업(10~34) 12
40.0%
C 제조업 (10 ~ 33) 9
30.0%
G 도매 및 소매업 (45~47) 3
 
10.0%
I 숙박 및 음식점업 (55 ~ 56) 2
 
6.7%
J출판;영상;방송통신및정보서비스업(58~63) 1
 
3.3%
G 도매 및 소매업(45~47) 1
 
3.3%
F 건설업 (41 ~ 42) 1
 
3.3%
F 건설업(41~42) 1
 
3.3%

Length

2023-12-10T23:15:33.027521image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T23:15:33.262385image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
c 21
19.1%
12
10.9%
제조업(10~34 12
10.9%
제조업 9
8.2%
10 9
8.2%
33 9
8.2%
및 6
 
5.5%
g 4
 
3.6%
도매 4
 
3.6%
소매업 3
 
2.7%
Other values (13) 21
19.1%

업종중분류명
Text

Distinct28
Distinct (%)93.3%
Missing0
Missing (%)0.0%
Memory size372.0 B
2023-12-10T23:15:33.667142image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length29
Median length18.5
Mean length14.966667
Min length4

Characters and Unicode

Total characters449
Distinct characters100
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

Unique26 ?
Unique (%)86.7%

Sample

1st row전기공급 및 전기제어 장치 제조업
2nd row낙농제품 및 식용빙과류 제조업
3rd row기타 전자부품 제조업
4th row건축자재; 철물 및 난방장치 도매업
5th row기타 정보 서비스업
ValueCountFrequency (%)
제조업 18
 
14.0%
및 17
 
13.2%
기타 5
 
3.9%
도매업 4
 
3.1%
종이 3
 
2.3%
가공 3
 
2.3%
금속파스너 2
 
1.6%
식품 2
 
1.6%
스프링 2
 
1.6%
저장 2
 
1.6%
Other values (64) 71
55.0%
2023-12-10T23:15:34.336931image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
99
22.0%
업 32
 
7.1%
제 25
 
5.6%
조 19
 
4.2%
및 17
 
3.8%
기 13
 
2.9%
품 12
 
2.7%
용 10
 
2.2%
가 9
 
2.0%
; 9
 
2.0%
Other values (90) 204
45.4%

Most occurring categories

ValueCountFrequency (%)
Other Letter 340
75.7%
Space Separator 99
 
22.0%
Other Punctuation 9
 
2.0%
Decimal Number 1
 
0.2%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
업 32
 
9.4%
제 25
 
7.4%
조 19
 
5.6%
및 17
 
5.0%
기 13
 
3.8%
품 12
 
3.5%
용 10
 
2.9%
가 9
 
2.6%
공 8
 
2.4%
금 6
 
1.8%
Other values (87) 189
55.6%
Space Separator
ValueCountFrequency (%)
99
100.0%
Other Punctuation
ValueCountFrequency (%)
; 9
100.0%
Decimal Number
ValueCountFrequency (%)
1 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 340
75.7%
Common 109
 
24.3%

Most frequent character per script

Hangul
ValueCountFrequency (%)
업 32
 
9.4%
제 25
 
7.4%
조 19
 
5.6%
및 17
 
5.0%
기 13
 
3.8%
품 12
 
3.5%
용 10
 
2.9%
가 9
 
2.6%
공 8
 
2.4%
금 6
 
1.8%
Other values (87) 189
55.6%
Common
ValueCountFrequency (%)
99
90.8%
; 9
 
8.3%
1 1
 
0.9%

Most occurring blocks

ValueCountFrequency (%)
Hangul 340
75.7%
ASCII 109
 
24.3%

Most frequent character per block

ASCII
ValueCountFrequency (%)
99
90.8%
; 9
 
8.3%
1 1
 
0.9%
Hangul
ValueCountFrequency (%)
업 32
 
9.4%
제 25
 
7.4%
조 19
 
5.6%
및 17
 
5.0%
기 13
 
3.8%
품 12
 
3.5%
용 10
 
2.9%
가 9
 
2.6%
공 8
 
2.4%
금 6
 
1.8%
Other values (87) 189
55.6%

주요제품명
Text

UNIQUE 

Distinct30
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size372.0 B
2023-12-10T23:15:34.686237image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length19
Median length12
Mean length7.1
Min length2

Characters and Unicode

Total characters213
Distinct characters112
Distinct categories6 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique30 ?
Unique (%)100.0%

Sample

1st row수배전반
2nd row치즈
3rd rowBLU; IP CCTV
4th row방화문문
5th row시스템 소프트웨어 자문;개발
ValueCountFrequency (%)
시스템 2
 
4.5%
수배전반 1
 
2.3%
전자통신용 1
 
2.3%
골판지상자 1
 
2.3%
배기구 1
 
2.3%
테일트림파이프 1
 
2.3%
반도체 1
 
2.3%
배관공사외 1
 
2.3%
젖소착유기등 1
 
2.3%
인쇄용스티커 1
 
2.3%
Other values (33) 33
75.0%
2023-12-10T23:15:35.174310image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
14
 
6.6%
스 6
 
2.8%
; 6
 
2.8%
기 6
 
2.8%
이 5
 
2.3%
도 4
 
1.9%
장 4
 
1.9%
용 4
 
1.9%
가 4
 
1.9%
공 4
 
1.9%
Other values (102) 156
73.2%

Most occurring categories

ValueCountFrequency (%)
Other Letter 177
83.1%
Space Separator 14
 
6.6%
Uppercase Letter 12
 
5.6%
Other Punctuation 6
 
2.8%
Open Punctuation 2
 
0.9%
Close Punctuation 2
 
0.9%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
스 6
 
3.4%
기 6
 
3.4%
이 5
 
2.8%
도 4
 
2.3%
장 4
 
2.3%
용 4
 
2.3%
가 4
 
2.3%
공 4
 
2.3%
전 4
 
2.3%
트 3
 
1.7%
Other values (90) 133
75.1%
Uppercase Letter
ValueCountFrequency (%)
C 3
25.0%
P 2
16.7%
V 2
16.7%
T 1
 
8.3%
I 1
 
8.3%
U 1
 
8.3%
L 1
 
8.3%
B 1
 
8.3%
Space Separator
ValueCountFrequency (%)
14
100.0%
Other Punctuation
ValueCountFrequency (%)
; 6
100.0%
Open Punctuation
ValueCountFrequency (%)
( 2
100.0%
Close Punctuation
ValueCountFrequency (%)
) 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 177
83.1%
Common 24
 
11.3%
Latin 12
 
5.6%

Most frequent character per script

Hangul
ValueCountFrequency (%)
스 6
 
3.4%
기 6
 
3.4%
이 5
 
2.8%
도 4
 
2.3%
장 4
 
2.3%
용 4
 
2.3%
가 4
 
2.3%
공 4
 
2.3%
전 4
 
2.3%
트 3
 
1.7%
Other values (90) 133
75.1%
Latin
ValueCountFrequency (%)
C 3
25.0%
P 2
16.7%
V 2
16.7%
T 1
 
8.3%
I 1
 
8.3%
U 1
 
8.3%
L 1
 
8.3%
B 1
 
8.3%
Common
ValueCountFrequency (%)
14
58.3%
; 6
25.0%
( 2
 
8.3%
) 2
 
8.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 177
83.1%
ASCII 36
 
16.9%

Most frequent character per block

ASCII
ValueCountFrequency (%)
14
38.9%
; 6
16.7%
C 3
 
8.3%
( 2
 
5.6%
) 2
 
5.6%
P 2
 
5.6%
V 2
 
5.6%
T 1
 
2.8%
I 1
 
2.8%
U 1
 
2.8%
Other values (2) 2
 
5.6%
Hangul
ValueCountFrequency (%)
스 6
 
3.4%
기 6
 
3.4%
이 5
 
2.8%
도 4
 
2.3%
장 4
 
2.3%
용 4
 
2.3%
가 4
 
2.3%
공 4
 
2.3%
전 4
 
2.3%
트 3
 
1.7%
Other values (90) 133
75.1%

자가여부
Categorical

HIGH CORRELATION 

Distinct2
Distinct (%)6.7%
Missing0
Missing (%)0.0%
Memory size372.0 B
부
18 
여
12 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row여
2nd row여
3rd row여
4th row여
5th row부

Common Values

ValueCountFrequency (%)
부 18
60.0%
여 12
40.0%

Length

2023-12-10T23:15:35.391939image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T23:15:35.561031image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
부 18
60.0%
여 12
40.0%

면적당임차료
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct14
Distinct (%)46.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean113.9894
Minimum0
Maximum544.90818
Zeros17
Zeros (%)56.7%
Negative0
Negative (%)0.0%
Memory size402.0 B
2023-12-10T23:15:35.722036image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q3212.77751
95-th percentile455.671
Maximum544.90818
Range544.90818
Interquartile range (IQR)212.77751

Descriptive statistics

Standard deviation164.25075
Coefficient of variation (CV)1.44093
Kurtosis0.66389843
Mean113.9894
Median Absolute Deviation (MAD)0
Skewness1.3126811
Sum3419.6821
Variance26978.309
MonotonicityNot monotonic
2023-12-10T23:15:35.953685image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=14)
ValueCountFrequency (%)
0.0 17
56.7%
290.1751714 1
 
3.3%
171.6465353 1
 
3.3%
544.9081803 1
 
3.3%
258.4995785 1
 
3.3%
197.825081 1
 
3.3%
326.9556793 1
 
3.3%
86.2158083 1
 
3.3%
217.7616473 1
 
3.3%
257.3158426 1
 
3.3%
Other values (4) 4
 
13.3%
ValueCountFrequency (%)
0.0 17
56.7%
69.82543641 1
 
3.3%
86.2158083 1
 
3.3%
87.32834471 1
 
3.3%
171.6465353 1
 
3.3%
197.825081 1
 
3.3%
217.7616473 1
 
3.3%
257.3158426 1
 
3.3%
258.4995785 1
 
3.3%
290.1751714 1
 
3.3%
ValueCountFrequency (%)
544.9081803 1
3.3%
456.1983471 1
3.3%
455.026455 1
3.3%
326.9556793 1
3.3%
290.1751714 1
3.3%
258.4995785 1
3.3%
257.3158426 1
3.3%
217.7616473 1
3.3%
197.825081 1
3.3%
171.6465353 1
3.3%

Interactions

2023-12-10T23:15:30.404684image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T23:15:29.592599image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T23:15:30.600408image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T23:15:30.040438image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-10T23:15:36.098803image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
관리번호시군명업종대분류명업종중분류명주요제품명자가여부면적당임차료
관리번호1.0000.0000.0001.0001.0000.0000.000
시군명0.0001.0000.6840.0001.0000.2700.000
업종대분류명0.0000.6841.0001.0001.0000.0000.855
업종중분류명1.0000.0001.0001.0001.0001.0000.976
주요제품명1.0001.0001.0001.0001.0001.0001.000
자가여부0.0000.2700.0001.0001.0001.0000.777
면적당임차료0.0000.0000.8550.9761.0000.7771.000
2023-12-10T23:15:36.313828image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
업종대분류명자가여부시군명
업종대분류명1.0000.0000.325
자가여부0.0001.0000.158
시군명0.3250.1581.000
2023-12-10T23:15:36.478483image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
관리번호면적당임차료시군명업종대분류명자가여부
관리번호1.000-0.0000.0000.0000.045
면적당임차료-0.0001.0000.0000.4410.527
시군명0.0000.0001.0000.3250.158
업종대분류명0.0000.4410.3251.0000.000
자가여부0.0450.5270.1580.0001.000

Missing values

2023-12-10T23:15:30.901828image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-10T23:15:31.314761image/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

기준년월관리번호시군명업종대분류명업종중분류명주요제품명자가여부면적당임차료
02021-10100063139포천시(의정부)C 제조업(10~34)전기공급 및 전기제어 장치 제조업수배전반여0.0
12021-10100063564평택시C 제조업 (10 ~ 33)낙농제품 및 식용빙과류 제조업치즈여0.0
22021-10110000288평택시C 제조업(10~34)기타 전자부품 제조업BLU; IP CCTV여0.0
32021-10110001564고양시G 도매 및 소매업 (45~47)건축자재; 철물 및 난방장치 도매업방화문문여0.0
42021-10110000933수원시J출판;영상;방송통신및정보서비스업(58~63)기타 정보 서비스업시스템 소프트웨어 자문;개발부0.0
52021-10110004325안양시G 도매 및 소매업(45~47)신선 식품 및 단순 가공 식품 도매업육류 도소매부290.175171
62021-10110002257포천시(의정부)C 제조업 (10 ~ 33)골판지; 종이 상자 및 종이 용기 제조업종이컵여0.0
72021-10110004870평택시C 제조업(10~34)산업용 난방 보일러; 금속탱크; 및 유사 용기 제조업금속탱크부171.646535
82021-10110001257고양시C 제조업 (10 ~ 33)의료용 기기 제조업레이저 치료기부544.90818
92021-10110000436화성시(화성)C 제조업(10~34)구조용 금속제품 제조업이동통신철구조무; 반도체장비 프레임부258.499578
기준년월관리번호시군명업종대분류명업종중분류명주요제품명자가여부면적당임차료
202021-10110003946평택시C 제조업 (10 ~ 33)수산물 가공 및 저장 처리업중화식품류여0.0
212021-10110007001광명시(서부)C 제조업 (10 ~ 33)절연선 및 케이블 제조업전자통신용 부품(가스킷;실링 외)여0.0
222021-10110004413포천시(의정부)C 제조업 (10 ~ 33)가죽; 가방 및 유사제품 제조업임가공가죽부257.315843
232021-10110007187남양주시C 제조업(10~34)금속파스너; 스프링 및 금속선 가공제품 제조업볼트부87.328345
242021-10110004549용인시I 숙박 및 음식점업 (55 ~ 56)음식점업간이음식점부0.0
252021-10110007346화성시(화성)C 제조업(10~34)육류 가공 및 저장 처리업축산물염장가공여0.0
262021-10110004795남양주시G 도매 및 소매업 (45~47)가정용품 도매업화장지;위생용품부456.198347
272021-10110007388고양시G 도매 및 소매업 (45~47)산업용 농축산물 및 산동물 도매업동물사료도매업부69.825436
282021-10110004857평택시C 제조업 (10 ~ 33)1차 철강 제조업스테인리스부455.026455
292021-10110007433파주시(고양)C 제조업(10~34)금속파스너; 스프링 및 금속선 가공제품 제조업진열대부0.0