Overview

Dataset statistics

Number of variables7
Number of observations114
Missing cells11
Missing cells (%)1.4%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory6.8 KiB
Average record size in memory61.2 B

Variable types

Numeric4
Text2
Categorical1

Dataset

Description충청남도 부여군 2014년 3월기준 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=445&beforeMenuCd=DOM_000000201001001000&publicdatapk=15051995

Alerts

기준일자 has constant value ""Constant
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
초순 has 5 (4.4%) missing valuesMissing
중순 has 3 (2.6%) missing valuesMissing
하순 has 3 (2.6%) missing valuesMissing
연번 has unique valuesUnique

Reproduction

Analysis started2024-01-09 20:20:48.998841
Analysis finished2024-01-09 20:20:50.983938
Duration1.99 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

연번
Real number (ℝ)

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
2024-01-10T05:20:51.044642image/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
2024-01-10T05:20:51.156701image/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%

품목
Text

Distinct65
Distinct (%)57.0%
Missing0
Missing (%)0.0%
Memory size1.0 KiB
2024-01-10T05:20:51.349299image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length8
Median length7.5
Mean length3.9912281
Min length1

Characters and Unicode

Total characters455
Distinct characters108
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

Unique64 ?
Unique (%)56.1%

Sample

1st row
2nd row배추
3rd row
4th row
5th row고추
ValueCountFrequency (%)
개인서비스 50
43.1%
명태(동태 1
 
0.9%
냉동오징어 1
 
0.9%
꽁치 1
 
0.9%
조개 1
 
0.9%
마른멸치 1
 
0.9%
마른오징어 1
 
0.9%
북어 1
 
0.9%
1
 
0.9%
멸치액젓 1
 
0.9%
Other values (57) 57
49.1%
2024-01-10T05:20:51.662912image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
52
 
11.4%
51
 
11.2%
50
 
11.0%
50
 
11.0%
50
 
11.0%
10
 
2.2%
9
 
2.0%
7
 
1.5%
7
 
1.5%
6
 
1.3%
Other values (98) 163
35.8%

Most occurring categories

ValueCountFrequency (%)
Other Letter 446
98.0%
Close Punctuation 3
 
0.7%
Open Punctuation 3
 
0.7%
Space Separator 3
 
0.7%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
52
 
11.7%
51
 
11.4%
50
 
11.2%
50
 
11.2%
50
 
11.2%
10
 
2.2%
9
 
2.0%
7
 
1.6%
7
 
1.6%
6
 
1.3%
Other values (95) 154
34.5%
Close Punctuation
ValueCountFrequency (%)
) 3
100.0%
Open Punctuation
ValueCountFrequency (%)
( 3
100.0%
Space Separator
ValueCountFrequency (%)
3
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 446
98.0%
Common 9
 
2.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
52
 
11.7%
51
 
11.4%
50
 
11.2%
50
 
11.2%
50
 
11.2%
10
 
2.2%
9
 
2.0%
7
 
1.6%
7
 
1.6%
6
 
1.3%
Other values (95) 154
34.5%
Common
ValueCountFrequency (%)
) 3
33.3%
( 3
33.3%
3
33.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 446
98.0%
ASCII 9
 
2.0%

Most frequent character per block

Hangul
ValueCountFrequency (%)
52
 
11.7%
51
 
11.4%
50
 
11.2%
50
 
11.2%
50
 
11.2%
10
 
2.2%
9
 
2.0%
7
 
1.6%
7
 
1.6%
6
 
1.3%
Other values (95) 154
34.5%
ASCII
ValueCountFrequency (%)
) 3
33.3%
( 3
33.3%
3
33.3%

규격
Text

Distinct105
Distinct (%)92.1%
Missing0
Missing (%)0.0%
Memory size1.0 KiB
2024-01-10T05:20:51.891337image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length31
Median length22
Mean length14.324561
Min length3

Characters and Unicode

Total characters1633
Distinct characters260
Distinct categories11 ?
Distinct scripts3 ?
Distinct blocks4 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique98 ?
Unique (%)86.0%

Sample

1st row청결미20kg,1포
2nd row통배추 1kg
3rd row잎 없는 것, 1kg
4th row대파,1kg
5th row화건 600g정도
ValueCountFrequency (%)
1kg 14
 
4.3%
10
 
3.0%
1회 10
 
3.0%
성인 9
 
2.7%
1병 8
 
2.4%
1그릇 7
 
2.1%
대중식당 6
 
1.8%
신선한 6
 
1.8%
1마리 6
 
1.8%
100g 6
 
1.8%
Other values (197) 247
75.1%
2024-01-10T05:20:52.240808image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
216
 
13.2%
1 100
 
6.1%
0 89
 
5.5%
( 66
 
4.0%
) 66
 
4.0%
g 46
 
2.8%
2 32
 
2.0%
27
 
1.7%
27
 
1.7%
25
 
1.5%
Other values (250) 939
57.5%

Most occurring categories

ValueCountFrequency (%)
Other Letter 874
53.5%
Decimal Number 269
 
16.5%
Space Separator 216
 
13.2%
Lowercase Letter 106
 
6.5%
Open Punctuation 66
 
4.0%
Close Punctuation 66
 
4.0%
Other Punctuation 20
 
1.2%
Uppercase Letter 6
 
0.4%
Dash Punctuation 5
 
0.3%
Math Symbol 4
 
0.2%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
27
 
3.1%
27
 
3.1%
25
 
2.9%
22
 
2.5%
22
 
2.5%
19
 
2.2%
19
 
2.2%
16
 
1.8%
15
 
1.7%
14
 
1.6%
Other values (221) 668
76.4%
Decimal Number
ValueCountFrequency (%)
1 100
37.2%
0 89
33.1%
2 32
 
11.9%
5 21
 
7.8%
3 11
 
4.1%
6 8
 
3.0%
4 5
 
1.9%
9 2
 
0.7%
8 1
 
0.4%
Lowercase Letter
ValueCountFrequency (%)
g 46
43.4%
k 22
20.8%
m 18
 
17.0%
c 13
 
12.3%
l 7
 
6.6%
Uppercase Letter
ValueCountFrequency (%)
D 2
33.3%
V 1
16.7%
L 1
16.7%
C 1
16.7%
P 1
16.7%
Other Punctuation
ValueCountFrequency (%)
, 14
70.0%
. 4
 
20.0%
* 2
 
10.0%
Math Symbol
ValueCountFrequency (%)
3
75.0%
+ 1
 
25.0%
Space Separator
ValueCountFrequency (%)
216
100.0%
Open Punctuation
ValueCountFrequency (%)
( 66
100.0%
Close Punctuation
ValueCountFrequency (%)
) 66
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 5
100.0%
Other Symbol
ValueCountFrequency (%)
1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 874
53.5%
Common 647
39.6%
Latin 112
 
6.9%

Most frequent character per script

Hangul
ValueCountFrequency (%)
27
 
3.1%
27
 
3.1%
25
 
2.9%
22
 
2.5%
22
 
2.5%
19
 
2.2%
19
 
2.2%
16
 
1.8%
15
 
1.7%
14
 
1.6%
Other values (221) 668
76.4%
Common
ValueCountFrequency (%)
216
33.4%
1 100
15.5%
0 89
13.8%
( 66
 
10.2%
) 66
 
10.2%
2 32
 
4.9%
5 21
 
3.2%
, 14
 
2.2%
3 11
 
1.7%
6 8
 
1.2%
Other values (9) 24
 
3.7%
Latin
ValueCountFrequency (%)
g 46
41.1%
k 22
19.6%
m 18
 
16.1%
c 13
 
11.6%
l 7
 
6.2%
D 2
 
1.8%
V 1
 
0.9%
L 1
 
0.9%
C 1
 
0.9%
P 1
 
0.9%

Most occurring blocks

ValueCountFrequency (%)
Hangul 874
53.5%
ASCII 755
46.2%
Math Operators 3
 
0.2%
CJK Compat 1
 
0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
216
28.6%
1 100
13.2%
0 89
11.8%
( 66
 
8.7%
) 66
 
8.7%
g 46
 
6.1%
2 32
 
4.2%
k 22
 
2.9%
5 21
 
2.8%
m 18
 
2.4%
Other values (17) 79
 
10.5%
Hangul
ValueCountFrequency (%)
27
 
3.1%
27
 
3.1%
25
 
2.9%
22
 
2.5%
22
 
2.5%
19
 
2.2%
19
 
2.2%
16
 
1.8%
15
 
1.7%
14
 
1.6%
Other values (221) 668
76.4%
Math Operators
ValueCountFrequency (%)
3
100.0%
CJK Compat
ValueCountFrequency (%)
1
100.0%

초순
Real number (ℝ)

HIGH CORRELATION  MISSING 

Distinct68
Distinct (%)62.4%
Missing5
Missing (%)4.4%
Infinite0
Infinite (%)0.0%
Mean13646.193
Minimum300
Maximum295200
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.1 KiB
2024-01-10T05:20:52.368615image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum300
5-th percentile790
Q12500
median6000
Q312000
95-th percentile35600
Maximum295200
Range294900
Interquartile range (IQR)9500

Descriptive statistics

Standard deviation35901.113
Coefficient of variation (CV)2.630852
Kurtosis46.894846
Mean13646.193
Median Absolute Deviation (MAD)4000
Skewness6.6340843
Sum1487435
Variance1.2888899 × 109
MonotonicityNot monotonic
2024-01-10T05:20:52.479102image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
12000 6
 
5.3%
8000 5
 
4.4%
7000 5
 
4.4%
2500 4
 
3.5%
5000 4
 
3.5%
3000 4
 
3.5%
2000 3
 
2.6%
4000 3
 
2.6%
6000 3
 
2.6%
11000 3
 
2.6%
Other values (58) 69
60.5%
(Missing) 5
 
4.4%
ValueCountFrequency (%)
300 1
0.9%
350 1
0.9%
380 1
0.9%
600 1
0.9%
640 1
0.9%
750 1
0.9%
850 1
0.9%
1000 1
0.9%
1025 1
0.9%
1100 1
0.9%
ValueCountFrequency (%)
295200 1
0.9%
230000 1
0.9%
58000 1
0.9%
47800 1
0.9%
40000 1
0.9%
36000 1
0.9%
35000 1
0.9%
30000 2
1.8%
25000 1
0.9%
23000 1
0.9%

중순
Real number (ℝ)

HIGH CORRELATION  MISSING 

Distinct68
Distinct (%)61.3%
Missing3
Missing (%)2.6%
Infinite0
Infinite (%)0.0%
Mean13466.802
Minimum300
Maximum295200
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.1 KiB
2024-01-10T05:20:52.597438image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum300
5-th percentile745
Q12000
median6000
Q312000
95-th percentile35500
Maximum295200
Range294900
Interquartile range (IQR)10000

Descriptive statistics

Standard deviation35654.453
Coefficient of variation (CV)2.6475813
Kurtosis47.448346
Mean13466.802
Median Absolute Deviation (MAD)4100
Skewness6.6621161
Sum1494815
Variance1.27124 × 109
MonotonicityNot monotonic
2024-01-10T05:20:52.728946image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
2000 6
 
5.3%
12000 6
 
5.3%
5000 5
 
4.4%
8000 5
 
4.4%
6000 4
 
3.5%
15000 4
 
3.5%
7000 4
 
3.5%
10000 3
 
2.6%
2500 3
 
2.6%
3500 3
 
2.6%
Other values (58) 68
59.6%
(Missing) 3
 
2.6%
ValueCountFrequency (%)
300 1
0.9%
350 1
0.9%
380 1
0.9%
500 1
0.9%
600 1
0.9%
640 1
0.9%
850 1
0.9%
900 1
0.9%
1000 2
1.8%
1025 1
0.9%
ValueCountFrequency (%)
295200 1
0.9%
230000 1
0.9%
58000 1
0.9%
47800 1
0.9%
40000 1
0.9%
36000 1
0.9%
35000 1
0.9%
30000 2
1.8%
26000 1
0.9%
25000 2
1.8%

하순
Real number (ℝ)

HIGH CORRELATION  MISSING 

Distinct68
Distinct (%)61.3%
Missing3
Missing (%)2.6%
Infinite0
Infinite (%)0.0%
Mean13466.802
Minimum300
Maximum295200
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.1 KiB
2024-01-10T05:20:52.853809image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum300
5-th percentile745
Q12000
median6000
Q312000
95-th percentile35500
Maximum295200
Range294900
Interquartile range (IQR)10000

Descriptive statistics

Standard deviation35654.453
Coefficient of variation (CV)2.6475813
Kurtosis47.448346
Mean13466.802
Median Absolute Deviation (MAD)4100
Skewness6.6621161
Sum1494815
Variance1.27124 × 109
MonotonicityNot monotonic
2024-01-10T05:20:52.996205image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
2000 6
 
5.3%
12000 6
 
5.3%
5000 5
 
4.4%
8000 5
 
4.4%
6000 4
 
3.5%
15000 4
 
3.5%
7000 4
 
3.5%
10000 3
 
2.6%
2500 3
 
2.6%
3500 3
 
2.6%
Other values (58) 68
59.6%
(Missing) 3
 
2.6%
ValueCountFrequency (%)
300 1
0.9%
350 1
0.9%
380 1
0.9%
500 1
0.9%
600 1
0.9%
640 1
0.9%
850 1
0.9%
900 1
0.9%
1000 2
1.8%
1025 1
0.9%
ValueCountFrequency (%)
295200 1
0.9%
230000 1
0.9%
58000 1
0.9%
47800 1
0.9%
40000 1
0.9%
36000 1
0.9%
35000 1
0.9%
30000 2
1.8%
26000 1
0.9%
25000 2
1.8%

기준일자
Categorical

CONSTANT 

Distinct1
Distinct (%)0.9%
Missing0
Missing (%)0.0%
Memory size1.0 KiB
2014-03
114 

Length

Max length7
Median length7
Mean length7
Min length7

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2014-03
2nd row2014-03
3rd row2014-03
4th row2014-03
5th row2014-03

Common Values

ValueCountFrequency (%)
2014-03 114
100.0%

Length

2024-01-10T05:20:53.100607image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-01-10T05:20:53.180077image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2014-03 114
100.0%

Interactions

2024-01-10T05:20:50.180913image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T05:20:49.295634image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T05:20:49.570120image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T05:20:49.872040image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T05:20:50.270942image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/