Overview

Dataset statistics

Number of variables6
Number of observations30
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory1.6 KiB
Average record size in memory54.4 B

Variable types

Numeric2
Categorical3
Text1

Dataset

Description샘플 데이터
Author경기도경제과학진흥원
URLhttps://bigdata-region.kr/#/dataset/bce40d5c-e90d-4b3c-8c51-7b1fd09adb60

Alerts

시도명 has constant value ""Constant
시군구명 has constant value ""Constant
분석인덱스 is highly overall correlated with 행정동명High correlation
행정동명 is highly overall correlated with 분석인덱스High correlation
분석인덱스 has unique valuesUnique
분석인덱스 has 1 (3.3%) zerosZeros

Reproduction

Analysis started2023-12-10 14:09:41.216962
Analysis finished2023-12-10 14:09:42.803425
Duration1.59 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

분석인덱스
Real number (ℝ)

HIGH CORRELATION  UNIQUE  ZEROS 

Distinct30
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean14.5
Minimum0
Maximum29
Zeros1
Zeros (%)3.3%
Negative0
Negative (%)0.0%
Memory size402.0 B
2023-12-10T23:09:42.921455image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile1.45
Q17.25
median14.5
Q321.75
95-th percentile27.55
Maximum29
Range29
Interquartile range (IQR)14.5

Descriptive statistics

Standard deviation8.8034084
Coefficient of variation (CV)0.60713162
Kurtosis-1.2
Mean14.5
Median Absolute Deviation (MAD)7.5
Skewness0
Sum435
Variance77.5
MonotonicityStrictly increasing
2023-12-10T23:09:43.124234image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=30)
ValueCountFrequency (%)
0 1
 
3.3%
16 1
 
3.3%
29 1
 
3.3%
28 1
 
3.3%
27 1
 
3.3%
26 1
 
3.3%
25 1
 
3.3%
24 1
 
3.3%
23 1
 
3.3%
22 1
 
3.3%
Other values (20) 20
66.7%
ValueCountFrequency (%)
0 1
3.3%
1 1
3.3%
2 1
3.3%
3 1
3.3%
4 1
3.3%
5 1
3.3%
6 1
3.3%
7 1
3.3%
8 1
3.3%
9 1
3.3%
ValueCountFrequency (%)
29 1
3.3%
28 1
3.3%
27 1
3.3%
26 1
3.3%
25 1
3.3%
24 1
3.3%
23 1
3.3%
22 1
3.3%
21 1
3.3%
20 1
3.3%

시도명
Categorical

CONSTANT 

Distinct1
Distinct (%)3.3%
Missing0
Missing (%)0.0%
Memory size372.0 B
경기도
30 

Length

Max length3
Median length3
Mean length3
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
경기도 30
100.0%

Length

2023-12-10T23:09:43.328841image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T23:09:43.505522image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
경기도 30
100.0%

시군구명
Categorical

CONSTANT 

Distinct1
Distinct (%)3.3%
Missing0
Missing (%)0.0%
Memory size372.0 B
가평군
30 

Length

Max length3
Median length3
Mean length3
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
가평군 30
100.0%

Length

2023-12-10T23:09:43.670897image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T23:09:43.818646image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
가평군 30
100.0%

행정동명
Categorical

HIGH CORRELATION 

Distinct5
Distinct (%)16.7%
Missing0
Missing (%)0.0%
Memory size372.0 B
가평읍
14 
상면
6 
설악면
6 
북면
3 
조종면
 
1

Length

Max length3
Median length3
Mean length2.7
Min length2

Unique

Unique1 ?
Unique (%)3.3%

Sample

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

Common Values

ValueCountFrequency (%)
가평읍 14
46.7%
상면 6
20.0%
설악면 6
20.0%
북면 3
 
10.0%
조종면 1
 
3.3%

Length

2023-12-10T23:09:43.986784image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T23:09:44.162877image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
가평읍 14
46.7%
상면 6
20.0%
설악면 6
20.0%
북면 3
 
10.0%
조종면 1
 
3.3%

업종대분류명
Text

Distinct15
Distinct (%)50.0%
Missing0
Missing (%)0.0%
Memory size372.0 B
2023-12-10T23:09:44.578833image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length20
Median length18
Mean length9.0333333
Min length4

Characters and Unicode

Total characters271
Distinct characters85
Distinct categories3 ?
Distinct scripts3 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique8 ?
Unique (%)26.7%

Sample

1st rowC제조업
2nd rowE하수·폐기물처리;원료재생및환경복원업
3rd rowF건설업
4th rowG도매및소매업
5th rowH운수및창고업
ValueCountFrequency (%)
c제조업 5
16.7%
g도매및소매업 4
13.3%
i숙박및음식점업 4
13.3%
r예술;스포츠및여가관련서비스업 3
10.0%
f건설업 2
 
6.7%
h운수및창고업 2
 
6.7%
s협회및단체;수리및기타개인서비스업 2
 
6.7%
e하수·폐기물처리;원료재생및환경복원업 1
 
3.3%
h운수업 1
 
3.3%
k금융및보험업 1
 
3.3%
Other values (5) 5
16.7%
2023-12-10T23:09:45.171119image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
업 35
 
12.9%
및 23
 
8.5%
스 11
 
4.1%
매 8
 
3.0%
비 8
 
3.0%
서 8
 
3.0%
; 8
 
3.0%
수 6
 
2.2%
C 5
 
1.8%
조 5
 
1.8%
Other values (75) 154
56.8%

Most occurring categories

ValueCountFrequency (%)
Other Letter 232
85.6%
Uppercase Letter 30
 
11.1%
Other Punctuation 9
 
3.3%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
업 35
 
15.1%
및 23
 
9.9%
스 11
 
4.7%
매 8
 
3.4%
비 8
 
3.4%
서 8
 
3.4%
수 6
 
2.6%
조 5
 
2.2%
제 5
 
2.2%
술 4
 
1.7%
Other values (59) 119
51.3%
Uppercase Letter
ValueCountFrequency (%)
C 5
16.7%
I 4
13.3%
G 4
13.3%
H 3
10.0%
R 3
10.0%
S 2
 
6.7%
F 2
 
6.7%
M 1
 
3.3%
N 1
 
3.3%
P 1
 
3.3%
Other values (4) 4
13.3%
Other Punctuation
ValueCountFrequency (%)
; 8
88.9%
· 1
 
11.1%

Most occurring scripts

ValueCountFrequency (%)
Hangul 232
85.6%
Latin 30
 
11.1%
Common 9
 
3.3%

Most frequent character per script

Hangul
ValueCountFrequency (%)
업 35
 
15.1%
및 23
 
9.9%
스 11
 
4.7%
매 8
 
3.4%
비 8
 
3.4%
서 8
 
3.4%
수 6
 
2.6%
조 5
 
2.2%
제 5
 
2.2%
술 4
 
1.7%
Other values (59) 119
51.3%
Latin
ValueCountFrequency (%)
C 5
16.7%
I 4
13.3%
G 4
13.3%
H 3
10.0%
R 3
10.0%
S 2
 
6.7%
F 2
 
6.7%
M 1
 
3.3%
N 1
 
3.3%
P 1
 
3.3%
Other values (4) 4
13.3%
Common
ValueCountFrequency (%)
; 8
88.9%
· 1
 
11.1%

Most occurring blocks

ValueCountFrequency (%)
Hangul 232
85.6%
ASCII 38
 
14.0%
None 1
 
0.4%

Most frequent character per block

Hangul
ValueCountFrequency (%)
업 35
 
15.1%
및 23
 
9.9%
스 11
 
4.7%
매 8
 
3.4%
비 8
 
3.4%
서 8
 
3.4%
수 6
 
2.6%
조 5
 
2.2%
제 5
 
2.2%
술 4
 
1.7%
Other values (59) 119
51.3%
ASCII
ValueCountFrequency (%)
; 8
21.1%
C 5
13.2%
I 4
10.5%
G 4
10.5%
H 3
 
7.9%
R 3
 
7.9%
S 2
 
5.3%
F 2
 
5.3%
M 1
 
2.6%
N 1
 
2.6%
Other values (5) 5
13.2%
None
ValueCountFrequency (%)
· 1
100.0%

보증금액
Real number (ℝ)

Distinct23
Distinct (%)76.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean23615660
Minimum9500000
Maximum78750000
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size402.0 B
2023-12-10T23:09:45.374230image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum9500000
5-th percentile9500000
Q115000000
median19281381
Q321900000
95-th percentile62843750
Maximum78750000
Range69250000
Interquartile range (IQR)6900000

Descriptive statistics

Standard deviation16768178
Coefficient of variation (CV)0.71004486
Kurtosis4.5988035
Mean23615660
Median Absolute Deviation (MAD)4281381
Skewness2.2098229
Sum7.0846981 × 108
Variance2.811718 × 1014
MonotonicityNot monotonic
2023-12-10T23:09:45.599092image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=23)
ValueCountFrequency (%)
20000000 3
 
10.0%
9500000 3
 
10.0%
15000000 3
 
10.0%
17500000 2
 
6.7%
68750000 1
 
3.3%
30000000 1
 
3.3%
31500000 1
 
3.3%
20463636 1
 
3.3%
15771428 1
 
3.3%
11850000 1
 
3.3%
Other values (13) 13
43.3%
ValueCountFrequency (%)
9500000 3
10.0%
10000000 1
 
3.3%
11850000 1
 
3.3%
12000000 1
 
3.3%
15000000 3
10.0%
15771428 1
 
3.3%
16983333 1
 
3.3%
17500000 2
6.7%
18720000 1
 
3.3%
18922222 1
 
3.3%
ValueCountFrequency (%)
78750000 1
3.3%
68750000 1
3.3%
55625000 1
3.3%
42500000 1
3.3%
31500000 1
3.3%
30000000 1
3.3%
25071428 1
3.3%
22200000 1
3.3%
21000000 1
3.3%
20463636 1
3.3%

Interactions

2023-12-10T23:09:41.942188image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T23:09:41.517669image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T23:09:42.155788image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T23:09:41.741698image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-10T23:09:45.784658image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
분석인덱스행정동명업종대분류명보증금액
분석인덱스1.0000.9330.0000.000
행정동명0.9331.0000.0000.508
업종대분류명0.0000.0001.0000.000
보증금액0.0000.5080.0001.000
2023-12-10T23:09:45.932773image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
분석인덱스보증금액행정동명
분석인덱스1.0000.1330.579
보증금액0.1331.0000.347
행정동명0.5790.3471.000

Missing values

2023-12-10T23:09:42.475481image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-10T23:09:42.734226image/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

분석인덱스시도명시군구명행정동명업종대분류명보증금액
00경기도가평군가평읍C제조업68750000
11경기도가평군가평읍E하수·폐기물처리;원료재생및환경복원업42500000
22경기도가평군가평읍F건설업17500000
33경기도가평군가평읍G도매및소매업20222222
44경기도가평군가평읍H운수및창고업9500000
55경기도가평군가평읍H운수업10000000
66경기도가평군가평읍I숙박및음식점업19640540
77경기도가평군가평읍K금융및보험업12000000
88경기도가평군가평읍L부동산업및임대업9500000
99경기도가평군가평읍M전문;과학및기술서비스업15000000
분석인덱스시도명시군구명행정동명업종대분류명보증금액
2020경기도가평군상면H운수및창고업15000000
2121경기도가평군상면I숙박및음식점업18922222
2222경기도가평군상면R예술;스포츠및여가관련서비스업20000000
2323경기도가평군설악면C제조업11850000
2424경기도가평군설악면F건설업9500000
2525경기도가평군설악면G도매및소매업15771428
2626경기도가평군설악면I숙박및음식점업20463636
2727경기도가평군설악면R예술;스포츠및여가관련서비스업20000000
2828경기도가평군설악면S협회및단체;수리및기타개인서비스업31500000
2929경기도가평군조종면C제조업30000000