Overview

Dataset statistics

Number of variables5
Number of observations223
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory9.5 KiB
Average record size in memory43.6 B

Variable types

Text2
Numeric3

Dataset

Description세라믹 산업 對 중국 수출 현황 (분류, 광물, 무역수지 등 / 단위:천 달러 ) 통계 자료(기준 연도: 2014년도)입니다.
Author한국세라믹기술원
URLhttps://www.data.go.kr/data/15051231/fileData.do

Alerts

무역수지(2012 / 천달러) is highly overall correlated with 무역수지(2013 / 천달러) and 1 other fieldsHigh correlation
무역수지(2013 / 천달러) is highly overall correlated with 무역수지(2012 / 천달러) and 1 other fieldsHigh correlation
무역수지(2014 / 천달러) is highly overall correlated with 무역수지(2012 / 천달러) and 1 other fieldsHigh correlation
분 류 has unique valuesUnique
무역수지(2012 / 천달러) has 63 (28.3%) zerosZeros
무역수지(2013 / 천달러) has 66 (29.6%) zerosZeros
무역수지(2014 / 천달러) has 64 (28.7%) zerosZeros

Reproduction

Analysis started2023-12-12 15:10:11.082923
Analysis finished2023-12-12 15:10:12.874916
Duration1.79 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

분 류
Text

UNIQUE 

Distinct223
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size1.9 KiB
2023-12-13T00:10:13.223792image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length5
Median length5
Mean length4.5067265
Min length1

Characters and Unicode

Total characters1005
Distinct characters15
Distinct categories2 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique223 ?
Unique (%)100.0%

Sample

1st rowA
2nd rowA01
3rd rowA0101
4th rowA0102
5th rowA02
ValueCountFrequency (%)
a 1
 
0.4%
d0104 1
 
0.4%
d0201 1
 
0.4%
d0202 1
 
0.4%
d0203 1
 
0.4%
d0204 1
 
0.4%
d03 1
 
0.4%
d0301 1
 
0.4%
d0302 1
 
0.4%
d0303 1
 
0.4%
Other values (213) 213
95.5%
2023-12-13T00:10:13.744975image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 376
37.4%
1 90
 
9.0%
2 76
 
7.6%
3 61
 
6.1%
D 53
 
5.3%
4 52
 
5.2%
B 52
 
5.2%
A 50
 
5.0%
5 47
 
4.7%
E 35
 
3.5%
Other values (5) 113
 
11.2%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 782
77.8%
Uppercase Letter 223
 
22.2%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 376
48.1%
1 90
 
11.5%
2 76
 
9.7%
3 61
 
7.8%
4 52
 
6.6%
5 47
 
6.0%
6 30
 
3.8%
7 23
 
2.9%
8 17
 
2.2%
9 10
 
1.3%
Uppercase Letter
ValueCountFrequency (%)
D 53
23.8%
B 52
23.3%
A 50
22.4%
E 35
15.7%
C 33
14.8%

Most occurring scripts

ValueCountFrequency (%)
Common 782
77.8%
Latin 223
 
22.2%

Most frequent character per script

Common
ValueCountFrequency (%)
0 376
48.1%
1 90
 
11.5%
2 76
 
9.7%
3 61
 
7.8%
4 52
 
6.6%
5 47
 
6.0%
6 30
 
3.8%
7 23
 
2.9%
8 17
 
2.2%
9 10
 
1.3%
Latin
ValueCountFrequency (%)
D 53
23.8%
B 52
23.3%
A 50
22.4%
E 35
15.7%
C 33
14.8%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1005
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 376
37.4%
1 90
 
9.0%
2 76
 
7.6%
3 61
 
6.1%
D 53
 
5.3%
4 52
 
5.2%
B 52
 
5.2%
A 50
 
5.0%
5 47
 
4.7%
E 35
 
3.5%
Other values (5) 113
 
11.2%

광물
Text

Distinct212
Distinct (%)95.1%
Missing0
Missing (%)0.0%
Memory size1.9 KiB
2023-12-13T00:10:14.005810image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length33
Median length19
Mean length6.3497758
Min length2

Characters and Unicode

Total characters1416
Distinct characters221
Distinct categories8 ?
Distinct scripts3 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique206 ?
Unique (%)92.4%

Sample

1st row광물
2nd row규산질 원료
3rd row규사
4th row규조토
5th row규산알루미늄 원료
ValueCountFrequency (%)
기타 26
 
7.1%
부품 22
 
6.0%
원료 15
 
4.1%
13
 
3.6%
세라믹 12
 
3.3%
제품 6
 
1.6%
반도체 4
 
1.1%
도자기 4
 
1.1%
4
 
1.1%
복합산화물 4
 
1.1%
Other values (226) 254
69.8%
2023-12-13T00:10:14.385437image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
141
 
10.0%
50
 
3.5%
46
 
3.2%
45
 
3.2%
43
 
3.0%
35
 
2.5%
33
 
2.3%
32
 
2.3%
31
 
2.2%
28
 
2.0%
Other values (211) 932
65.8%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1237
87.4%
Space Separator 141
 
10.0%
Other Punctuation 10
 
0.7%
Uppercase Letter 10
 
0.7%
Close Punctuation 6
 
0.4%
Open Punctuation 6
 
0.4%
Lowercase Letter 5
 
0.4%
Decimal Number 1
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
50
 
4.0%
46
 
3.7%
45
 
3.6%
43
 
3.5%
35
 
2.8%
33
 
2.7%
32
 
2.6%
31
 
2.5%
28
 
2.3%
24
 
1.9%
Other values (196) 870
70.3%
Lowercase Letter
ValueCountFrequency (%)
e 1
20.0%
l 1
20.0%
u 1
20.0%
d 1
20.0%
o 1
20.0%
Uppercase Letter
ValueCountFrequency (%)
L 3
30.0%
E 3
30.0%
D 3
30.0%
M 1
 
10.0%
Other Punctuation
ValueCountFrequency (%)
/ 9
90.0%
· 1
 
10.0%
Space Separator
ValueCountFrequency (%)
141
100.0%
Close Punctuation
ValueCountFrequency (%)
) 6
100.0%
Open Punctuation
ValueCountFrequency (%)
( 6
100.0%
Decimal Number
ValueCountFrequency (%)
1 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1237
87.4%
Common 164
 
11.6%
Latin 15
 
1.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
50
 
4.0%
46
 
3.7%
45
 
3.6%
43
 
3.5%
35
 
2.8%
33
 
2.7%
32
 
2.6%
31
 
2.5%
28
 
2.3%
24
 
1.9%
Other values (196) 870
70.3%
Latin
ValueCountFrequency (%)
L 3
20.0%
E 3
20.0%
D 3
20.0%
e 1
 
6.7%
l 1
 
6.7%
u 1
 
6.7%
d 1
 
6.7%
o 1
 
6.7%
M 1
 
6.7%
Common
ValueCountFrequency (%)
141
86.0%
/ 9
 
5.5%
) 6
 
3.7%
( 6
 
3.7%
· 1
 
0.6%
1 1
 
0.6%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1237
87.4%
ASCII 178
 
12.6%
None 1
 
0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
141
79.2%
/ 9
 
5.1%
) 6
 
3.4%
( 6
 
3.4%
L 3
 
1.7%
E 3
 
1.7%
D 3
 
1.7%
1 1
 
0.6%
e 1
 
0.6%
l 1
 
0.6%
Other values (4) 4
 
2.2%
Hangul
ValueCountFrequency (%)
50
 
4.0%
46
 
3.7%
45
 
3.6%
43
 
3.5%
35
 
2.8%
33
 
2.7%
32
 
2.6%
31
 
2.5%
28
 
2.3%
24
 
1.9%
Other values (196) 870
70.3%
None
ValueCountFrequency (%)
· 1
100.0%

무역수지(2012 / 천달러)
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct146
Distinct (%)65.5%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean57094.117
Minimum0
Maximum3026922
Zeros63
Zeros (%)28.3%
Negative0
Negative (%)0.0%
Memory size2.1 KiB
2023-12-13T00:10:14.515979image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median847
Q312311
95-th percentile328630.7
Maximum3026922
Range3026922
Interquartile range (IQR)12311

Descriptive statistics

Standard deviation237694.71
Coefficient of variation (CV)4.1632084
Kurtosis112.29898
Mean57094.117
Median Absolute Deviation (MAD)847
Skewness9.5641085
Sum12731988
Variance5.6498774 × 1010
MonotonicityNot monotonic
2023-12-13T00:10:14.676767image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 63
28.3%
1 3
 
1.3%
73 3
 
1.3%
2 3
 
1.3%
3 2
 
0.9%
2019 2
 
0.9%
63 2
 
0.9%
5026 2
 
0.9%
1041 2
 
0.9%
13582 2
 
0.9%
Other values (136) 139
62.3%
ValueCountFrequency (%)
0 63
28.3%
1 3
 
1.3%
2 3
 
1.3%
3 2
 
0.9%
8 1
 
0.4%
21 1
 
0.4%
27 1
 
0.4%
39 1
 
0.4%
50 1
 
0.4%
58 1
 
0.4%
ValueCountFrequency (%)
3026922 1
0.4%
1147302 1
0.4%
608165 1
0.4%
554281 1
0.4%
537777 1
0.4%
533654 1
0.4%
477678 1
0.4%
439520 1
0.4%
349545 1
0.4%
336740 1
0.4%

무역수지(2013 / 천달러)
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct146
Distinct (%)65.5%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean59385.161
Minimum0
Maximum3215464
Zeros66
Zeros (%)29.6%
Negative0
Negative (%)0.0%
Memory size2.1 KiB
2023-12-13T00:10:14.994152image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median743
Q313175.5
95-th percentile356077.8
Maximum3215464
Range3215464
Interquartile range (IQR)13175.5

Descriptive statistics

Standard deviation244941.19
Coefficient of variation (CV)4.1246194
Kurtosis125.67636
Mean59385.161
Median Absolute Deviation (MAD)743
Skewness10.151718
Sum13242891
Variance5.9996187 × 1010
MonotonicityNot monotonic
2023-12-13T00:10:15.143343image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 66
29.6%
173 2
 
0.9%
14 2
 
0.9%
1244 2
 
0.9%
49243 2
 
0.9%
2709 2
 
0.9%
7545 2
 
0.9%
60 2
 
0.9%
12824 2
 
0.9%
8803 2
 
0.9%
Other values (136) 139
62.3%
ValueCountFrequency (%)
0 66
29.6%
2 1
 
0.4%
4 1
 
0.4%
5 1
 
0.4%
13 1
 
0.4%
14 2
 
0.9%
15 1
 
0.4%
24 1
 
0.4%
32 1
 
0.4%
53 1
 
0.4%
ValueCountFrequency (%)
3215464 1
0.4%
929868 1
0.4%
644659 1
0.4%
582717 1
0.4%
438300 1
0.4%
437895 1
0.4%
383804 1
0.4%
383557 1
0.4%
370529 1
0.4%
366251 1
0.4%

무역수지(2014 / 천달러)
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct149
Distinct (%)66.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean62435.054
Minimum0
Maximum3045031
Zeros64
Zeros (%)28.7%
Negative0
Negative (%)0.0%
Memory size2.1 KiB
2023-12-13T00:10:15.290200image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median619
Q313569
95-th percentile329335.9
Maximum3045031
Range3045031
Interquartile range (IQR)13569

Descriptive statistics

Standard deviation242587.71
Coefficient of variation (CV)3.8854409
Kurtosis104.34702
Mean62435.054
Median Absolute Deviation (MAD)619
Skewness9.0540016
Sum13923017
Variance5.8848798 × 1010
MonotonicityNot monotonic
2023-12-13T00:10:15.444077image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 64
28.7%
107 3
 
1.3%
2424 2
 
0.9%
62 2
 
0.9%
8 2
 
0.9%
3319 2
 
0.9%
52421 2
 
0.9%
10256 2
 
0.9%
3267 2
 
0.9%
2534 2
 
0.9%
Other values (139) 140
62.8%
ValueCountFrequency (%)
0 64
28.7%
1 1
 
0.4%
2 1
 
0.4%
4 1
 
0.4%
8 2
 
0.9%
14 1
 
0.4%
27 1
 
0.4%
31 2
 
0.9%
32 1
 
0.4%
34 1
 
0.4%
ValueCountFrequency (%)
3045031 1
0.4%
880684 1
0.4%
764776 1
0.4%
709425 1
0.4%
665272 1
0.4%
596507 1
0.4%
539811 1
0.4%
442182 1
0.4%
441232 1
0.4%
394763 1
0.4%

Interactions

2023-12-13T00:10:12.004476image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/