Overview

Dataset statistics

Number of variables7
Number of observations114
Missing cells64
Missing cells (%)8.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory6.8 KiB
Average record size in memory61.2 B

Variable types

Numeric4
Categorical1
Text2

Dataset

Description충청남도 부여군 2015년 2월기준 정기물가표 조사정보입니다.(생필품, 공공서비스 등의 품목, 규격, 요금정보)
Author충청남도
URLhttps://alldam.chungnam.go.kr/index.chungnam?menuCd=DOM_000000201001001001&st=&cds=&orgCd=&apiType=&isOpen=Y&pageIndex=447&beforeMenuCd=DOM_000000201001001000&publicdatapk=15051996

Alerts

연 번 is highly overall correlated with 구분High correlation
초순 is highly overall correlated with 중순 and 1 other fieldsHigh correlation
중순 is highly overall correlated with 초순 and 1 other fieldsHigh correlation
하순 is highly overall correlated with 초순 and 1 other fieldsHigh correlation
구분 is highly overall correlated with 연 번High correlation
규 격 has 50 (43.9%) missing valuesMissing
초순 has 5 (4.4%) missing valuesMissing
중순 has 5 (4.4%) missing valuesMissing
하순 has 4 (3.5%) missing valuesMissing
연 번 has unique valuesUnique

Reproduction

Analysis started2024-01-09 22:56:25.490844
Analysis finished2024-01-09 22:56:27.762181
Duration2.27 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

연 번
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct114
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean57.5
Minimum1
Maximum114
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.1 KiB
2024-01-10T07:56:27.829345image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile6.65
Q129.25
median57.5
Q385.75
95-th percentile108.35
Maximum114
Range113
Interquartile range (IQR)56.5

Descriptive statistics

Standard deviation33.052988
Coefficient of variation (CV)0.57483457
Kurtosis-1.2
Mean57.5
Median Absolute Deviation (MAD)28.5
Skewness0
Sum6555
Variance1092.5
MonotonicityStrictly increasing
2024-01-10T07:56:27.955830image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 1
 
0.9%
87 1
 
0.9%
85 1
 
0.9%
84 1
 
0.9%
83 1
 
0.9%
82 1
 
0.9%
81 1
 
0.9%
80 1
 
0.9%
79 1
 
0.9%
78 1
 
0.9%
Other values (104) 104
91.2%
ValueCountFrequency (%)
1 1
0.9%
2 1
0.9%
3 1
0.9%
4 1
0.9%
5 1
0.9%
6 1
0.9%
7 1
0.9%
8 1
0.9%
9 1
0.9%
10 1
0.9%
ValueCountFrequency (%)
114 1
0.9%
113 1
0.9%
112 1
0.9%
111 1
0.9%
110 1
0.9%
109 1
0.9%
108 1
0.9%
107 1
0.9%
106 1
0.9%
105 1
0.9%

구분
Categorical

HIGH CORRELATION 

Distinct4
Distinct (%)3.5%
Missing0
Missing (%)0.0%
Memory size1.0 KiB
개인서비스
50 
농축수산물
44 
공산품
11 
지방공공요금

Length

Max length6
Median length5
Mean length4.8859649
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
개인서비스 50
43.9%
농축수산물 44
38.6%
공산품 11
 
9.6%
지방공공요금 9
 
7.9%

Length

2024-01-10T07:56:28.085452image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-01-10T07:56:28.176120image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
개인서비스 50
43.9%
농축수산물 44
38.6%
공산품 11
 
9.6%
지방공공요금 9
 
7.9%
Distinct113
Distinct (%)99.1%
Missing0
Missing (%)0.0%
Memory size1.0 KiB
2024-01-10T07:56:28.488955image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length31
Median length24
Mean length9.6403509
Min length1

Characters and Unicode

Total characters1099
Distinct characters240
Distinct categories10 ?
Distinct scripts3 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique112 ?
Unique (%)98.2%

Sample

1st row
2nd row배추
3rd row
4th row
5th row고추
ValueCountFrequency (%)
성인 9
 
4.0%
1회 9
 
4.0%
1그릇 7
 
3.1%
대중식당 6
 
2.7%
1인분 5
 
2.2%
중급 4
 
1.8%
전문점 4
 
1.8%
200∼250g정도 3
 
1.3%
중화요리집 3
 
1.3%
60분 3
 
1.3%
Other values (162) 170
76.2%
2024-01-10T07:56:28.942255image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
110
 
10.0%
( 65
 
5.9%
) 65
 
5.9%
1 38
 
3.5%
33
 
3.0%
0 25
 
2.3%
22
 
2.0%
2 18
 
1.6%
17
 
1.5%
16
 
1.5%
Other values (230) 690
62.8%

Most occurring categories

ValueCountFrequency (%)
Other Letter 725
66.0%
Space Separator 110
 
10.0%
Decimal Number 97
 
8.8%
Open Punctuation 65
 
5.9%
Close Punctuation 65
 
5.9%
Lowercase Letter 14
 
1.3%
Other Punctuation 10
 
0.9%
Uppercase Letter 5
 
0.5%
Dash Punctuation 4
 
0.4%
Math Symbol 4
 
0.4%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
33
 
4.6%
22
 
3.0%
17
 
2.3%
16
 
2.2%
16
 
2.2%
13
 
1.8%
13
 
1.8%
13
 
1.8%
13
 
1.8%
11
 
1.5%
Other values (205) 558
77.0%
Decimal Number
ValueCountFrequency (%)
1 38
39.2%
0 25
25.8%
2 18
18.6%
5 9
 
9.3%
6 3
 
3.1%
4 2
 
2.1%
3 1
 
1.0%
9 1
 
1.0%
Lowercase Letter
ValueCountFrequency (%)
g 7
50.0%
c 4
28.6%
m 2
 
14.3%
k 1
 
7.1%
Uppercase Letter
ValueCountFrequency (%)
D 2
40.0%
V 1
20.0%
P 1
20.0%
C 1
20.0%
Other Punctuation
ValueCountFrequency (%)
, 6
60.0%
. 2
 
20.0%
* 2
 
20.0%
Math Symbol
ValueCountFrequency (%)
3
75.0%
+ 1
 
25.0%
Space Separator
ValueCountFrequency (%)
110
100.0%
Open Punctuation
ValueCountFrequency (%)
( 65
100.0%
Close Punctuation
ValueCountFrequency (%)
) 65
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 4
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 725
66.0%
Common 355
32.3%
Latin 19
 
1.7%

Most frequent character per script

Hangul
ValueCountFrequency (%)
33
 
4.6%
22
 
3.0%
17
 
2.3%
16
 
2.2%
16
 
2.2%
13
 
1.8%
13
 
1.8%
13
 
1.8%
13
 
1.8%
11
 
1.5%
Other values (205) 558
77.0%
Common
ValueCountFrequency (%)
110
31.0%
( 65
18.3%
) 65
18.3%
1 38
 
10.7%
0 25
 
7.0%
2 18
 
5.1%
5 9
 
2.5%
, 6
 
1.7%
- 4
 
1.1%
3
 
0.8%
Other values (7) 12
 
3.4%
Latin
ValueCountFrequency (%)
g 7
36.8%
c 4
21.1%
m 2
 
10.5%
D 2
 
10.5%
V 1
 
5.3%
P 1
 
5.3%
C 1
 
5.3%
k 1
 
5.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 725
66.0%
ASCII 371
33.8%
Math Operators 3
 
0.3%

Most frequent character per block

ASCII
ValueCountFrequency (%)
110
29.6%
( 65
17.5%
) 65
17.5%
1 38
 
10.2%
0 25
 
6.7%
2 18
 
4.9%
5 9
 
2.4%
g 7
 
1.9%
, 6
 
1.6%
- 4
 
1.1%
Other values (14) 24
 
6.5%
Hangul
ValueCountFrequency (%)
33
 
4.6%
22
 
3.0%
17
 
2.3%
16
 
2.2%
16
 
2.2%
13
 
1.8%
13
 
1.8%
13
 
1.8%
13
 
1.8%
11
 
1.5%
Other values (205) 558
77.0%
Math Operators
ValueCountFrequency (%)
3
100.0%

규 격
Text

MISSING 

Distinct58
Distinct (%)90.6%
Missing50
Missing (%)43.9%
Memory size1.0 KiB
2024-01-10T07:56:29.206302image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length26
Median length16
Mean length12.125
Min length3

Characters and Unicode

Total characters776
Distinct characters171
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

Unique53 ?
Unique (%)82.8%

Sample

1st row처갓집쌀, 청결미20kg,1포
2nd row통배추 1kg
3rd row잎 없는 것, 1kg
4th row대파,1kg
5th row화건 600g정도
ValueCountFrequency (%)
1kg 15
 
8.6%
10
 
5.7%
1병 8
 
4.6%
신선한 6
 
3.4%
1마리 5
 
2.9%
10개 5
 
2.9%
100g 4
 
2.3%
1봉지 3
 
1.7%
길이 3
 
1.7%
정육 2
 
1.1%
Other values (103) 114
65.1%
2024-01-10T07:56:29.579988image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
112
 
14.4%
1 62
 
8.0%
0 59
 
7.6%
g 39
 
5.0%
k 23
 
3.0%
21
 
2.7%
17
 
2.2%
m 16
 
2.1%
2 14
 
1.8%
11
 
1.4%
Other values (161) 402
51.8%

Most occurring categories

ValueCountFrequency (%)
Other Letter 371
47.8%
Decimal Number 169
21.8%
Space Separator 112
 
14.4%
Lowercase Letter 94
 
12.1%
Other Punctuation 12
 
1.5%
Open Punctuation 7
 
0.9%
Close Punctuation 7
 
0.9%
Uppercase Letter 3
 
0.4%
Dash Punctuation 1
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
21
 
5.7%
17
 
4.6%
11
 
3.0%
11
 
3.0%
11
 
3.0%
9
 
2.4%
9
 
2.4%
9
 
2.4%
8
 
2.2%
8
 
2.2%
Other values (137) 257
69.3%
Decimal Number
ValueCountFrequency (%)
1 62
36.7%
0 59
34.9%
2 14
 
8.3%
3 10
 
5.9%
6 9
 
5.3%
5 9
 
5.3%
4 3
 
1.8%
8 1
 
0.6%
9 1
 
0.6%
7 1
 
0.6%
Lowercase Letter
ValueCountFrequency (%)
g 39
41.5%
k 23
24.5%
m 16
17.0%
c 9
 
9.6%
l 7
 
7.4%
Uppercase Letter
ValueCountFrequency (%)
L 1
33.3%
J 1
33.3%
M 1
33.3%
Other Punctuation
ValueCountFrequency (%)
, 9
75.0%
. 3
 
25.0%
Space Separator
ValueCountFrequency (%)
112
100.0%
Open Punctuation
ValueCountFrequency (%)
( 7
100.0%
Close Punctuation
ValueCountFrequency (%)
) 7
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 371
47.8%
Common 308
39.7%
Latin 97
 
12.5%

Most frequent character per script

Hangul
ValueCountFrequency (%)
21
 
5.7%
17
 
4.6%
11
 
3.0%
11
 
3.0%
11
 
3.0%
9
 
2.4%
9
 
2.4%
9
 
2.4%
8
 
2.2%
8
 
2.2%
Other values (137) 257
69.3%
Common
ValueCountFrequency (%)
112
36.4%
1 62
20.1%
0 59
19.2%
2 14
 
4.5%
3 10
 
3.2%
, 9
 
2.9%
6 9
 
2.9%
5 9
 
2.9%
( 7
 
2.3%
) 7
 
2.3%
Other values (6) 10
 
3.2%
Latin
ValueCountFrequency (%)
g 39
40.2%
k 23
23.7%
m 16
16.5%
c 9
 
9.3%
l 7
 
7.2%
L 1
 
1.0%
J 1
 
1.0%
M 1
 
1.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 405
52.2%
Hangul 371
47.8%

Most frequent character per block

ASCII
ValueCountFrequency (%)
112
27.7%
1 62
15.3%
0 59
14.6%
g 39
 
9.6%
k 23
 
5.7%
m 16
 
4.0%
2 14
 
3.5%
3 10
 
2.5%
, 9
 
2.2%
6 9
 
2.2%
Other values (14) 52
12.8%
Hangul
ValueCountFrequency (%)
21
 
5.7%
17
 
4.6%
11
 
3.0%
11
 
3.0%
11
 
3.0%
9
 
2.4%
9
 
2.4%
9
 
2.4%
8
 
2.2%
8
 
2.2%
Other values (137) 257
69.3%

초순
Real number (ℝ)

HIGH CORRELATION  MISSING 

Distinct63
Distinct (%)57.8%
Missing5
Missing (%)4.4%
Infinite0
Infinite (%)0.0%
Mean14271.835
Minimum300
Maximum295200
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.1 KiB
2024-01-10T07:56:29.712062image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum300
5-th percentile820
Q12500
median7000
Q312000
95-th percentile39600
Maximum295200
Range294900
Interquartile range (IQR)9500

Descriptive statistics

Standard deviation36079.288
Coefficient of variation (CV)2.5280063
Kurtosis45.453124
Mean14271.835
Median Absolute Deviation (MAD)4800
Skewness6.4937758
Sum1555630
Variance1.301715 × 109
MonotonicityNot monotonic
2024-01-10T07:56:29.833562image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
7000 10
 
8.8%
12000 6
 
5.3%
3000 4
 
3.5%
15000 4
 
3.5%
2500 4
 
3.5%
20000 3
 
2.6%
1500 3
 
2.6%
11000 3
 
2.6%
30000 3
 
2.6%
5000 3
 
2.6%
Other values (53) 66
57.9%
(Missing) 5
 
4.4%
ValueCountFrequency (%)
300 1
0.9%
350 1
0.9%
400 1
0.9%
550 1
0.9%
750 1
0.9%
800 1
0.9%
850 1
0.9%
890 1
0.9%
1000 1
0.9%
1100 2
1.8%
ValueCountFrequency (%)
295200 1
 
0.9%
230000 1
 
0.9%
56000 1
 
0.9%
50000 1
 
0.9%
47000 1
 
0.9%
40000 1
 
0.9%
39000 1
 
0.9%
35000 1
 
0.9%
34000 1
 
0.9%
30000 3
2.6%

중순
Real number (ℝ)

HIGH CORRELATION  MISSING 

Distinct63
Distinct (%)57.8%
Missing5
Missing (%)4.4%
Infinite0
Infinite (%)0.0%
Mean14271.835
Minimum300
Maximum295200
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.1 KiB
2024-01-10T07:56:29.953347image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum300
5-th percentile820
Q12500
median7000
Q312000
95-th percentile39600
Maximum295200
Range294900
Interquartile range (IQR)9500

Descriptive statistics

Standard deviation36079.288
Coefficient of variation (CV)2.5280063
Kurtosis45.453124
Mean14271.835
Median Absolute Deviation (MAD)4800
Skewness6.4937758
Sum1555630
Variance1.301715 × 109
MonotonicityNot monotonic
2024-01-10T07:56:30.075043image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
7000 10
 
8.8%
12000 6
 
5.3%
3000 4
 
3.5%
15000 4
 
3.5%
2500 4
 
3.5%
20000 3
 
2.6%
1500 3
 
2.6%
11000 3
 
2.6%
30000 3
 
2.6%
5000 3
 
2.6%
Other values (53) 66
57.9%
(Missing) 5
 
4.4%
ValueCountFrequency (%)
300 1
0.9%
350 1
0.9%
400 1
0.9%
550 1
0.9%
750 1
0.9%
800 1