Overview

Dataset statistics

Number of variables4
Number of observations183
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory6.2 KiB
Average record size in memory34.7 B

Variable types

Numeric2
Text2

Dataset

Description공증업무 처리시 공증업무 처리 현황을 집계하고 있는 재외공관 정보를 제공 (국가번호, 국가명, 대사관번호, 대사관이름)
URLhttps://www.data.go.kr/data/15117889/fileData.do

Alerts

국가번호 is highly overall correlated with 대사관번호High correlation
대사관번호 is highly overall correlated with 국가번호High correlation
대사관번호 has unique valuesUnique
대사관이름 has unique valuesUnique

Reproduction

Analysis started2023-12-12 17:19:25.795364
Analysis finished2023-12-12 17:19:26.929957
Duration1.13 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

국가번호
Real number (ℝ)

HIGH CORRELATION 

Distinct120
Distinct (%)65.6%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean536.46448
Minimum101
Maximum914
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.7 KiB
2023-12-13T02:19:27.032747image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum101
5-th percentile107.1
Q1301
median519
Q3804.5
95-th percentile907.9
Maximum914
Range813
Interquartile range (IQR)503.5

Descriptive statistics

Standard deviation254.56929
Coefficient of variation (CV)0.4745315
Kurtosis-1.2117765
Mean536.46448
Median Absolute Deviation (MAD)218
Skewness-0.15560134
Sum98173
Variance64805.525
MonotonicityIncreasing
2023-12-13T02:19:27.246429image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
301 14
 
7.7%
702 10
 
5.5%
701 10
 
5.5%
602 5
 
2.7%
104 4
 
2.2%
813 4
 
2.2%
302 4
 
2.2%
819 3
 
1.6%
808 3
 
1.6%
205 3
 
1.6%
Other values (110) 123
67.2%
ValueCountFrequency (%)
101 1
 
0.5%
102 1
 
0.5%
103 1
 
0.5%
104 4
2.2%
105 1
 
0.5%
106 1
 
0.5%
107 1
 
0.5%
108 1
 
0.5%
109 1
 
0.5%
110 1
 
0.5%
ValueCountFrequency (%)
914 1
0.5%
913 2
1.1%
912 2
1.1%
911 1
0.5%
910 1
0.5%
909 1
0.5%
908 2
1.1%
907 2
1.1%
906 1
0.5%
905 1
0.5%

국가명
Text

Distinct120
Distinct (%)65.6%
Missing0
Missing (%)0.0%
Memory size1.6 KiB
2023-12-13T02:19:27.619174image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length8
Median length7
Mean length3.4808743
Min length2

Characters and Unicode

Total characters637
Distinct characters146
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique97 ?
Unique (%)53.0%

Sample

1st row네덜란드
2nd row영국
3rd row폴란드
4th row독일
5th row독일
ValueCountFrequency (%)
미국 14
 
7.7%
중국 10
 
5.5%
일본 10
 
5.5%
러시아 5
 
2.7%
독일 4
 
2.2%
캐나다 4
 
2.2%
오스트레일리아 4
 
2.2%
스페인 3
 
1.6%
인도 3
 
1.6%
베트남 3
 
1.6%
Other values (110) 123
67.2%
2023-12-13T02:19:28.192400image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
아 45
 
7.1%
국 29
 
4.6%
스 29
 
4.6%
리 23
 
3.6%
이 20
 
3.1%
일 19
 
3.0%
라 18
 
2.8%
미 18
 
2.8%
르 16
 
2.5%
트 15
 
2.4%
Other values (136) 405
63.6%

Most occurring categories

ValueCountFrequency (%)
Other Letter 637
100.0%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
아 45
 
7.1%
국 29
 
4.6%
스 29
 
4.6%
리 23
 
3.6%
이 20
 
3.1%
일 19
 
3.0%
라 18
 
2.8%
미 18
 
2.8%
르 16
 
2.5%
트 15
 
2.4%
Other values (136) 405
63.6%

Most occurring scripts

ValueCountFrequency (%)
Hangul 637
100.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
아 45
 
7.1%
국 29
 
4.6%
스 29
 
4.6%
리 23
 
3.6%
이 20
 
3.1%
일 19
 
3.0%
라 18
 
2.8%
미 18
 
2.8%
르 16
 
2.5%
트 15
 
2.4%
Other values (136) 405
63.6%

Most occurring blocks

ValueCountFrequency (%)
Hangul 637
100.0%

Most frequent character per block

Hangul
ValueCountFrequency (%)
아 45
 
7.1%
국 29
 
4.6%
스 29
 
4.6%
리 23
 
3.6%
이 20
 
3.1%
일 19
 
3.0%
라 18
 
2.8%
미 18
 
2.8%
르 16
 
2.5%
트 15
 
2.4%
Other values (136) 405
63.6%

대사관번호
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct183
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean53648.71
Minimum10101
Maximum91401
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.7 KiB
2023-12-13T02:19:28.370590image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum10101
5-th percentile10711
Q130113.5
median51901
Q380451
95-th percentile90791.1
Maximum91401
Range81300
Interquartile range (IQR)50337.5

Descriptive statistics

Standard deviation25456.818
Coefficient of variation (CV)0.47450942
Kurtosis-1.2117628
Mean53648.71
Median Absolute Deviation (MAD)21793
Skewness-0.15563949
Sum9817714
Variance6.480496 × 108
MonotonicityNot monotonic
2023-12-13T02:19:28.522183image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
10101 1
 
0.5%
70202 1
 
0.5%
70102 1
 
0.5%
70103 1
 
0.5%
70101 1
 
0.5%
70106 1
 
0.5%
70107 1
 
0.5%
70203 1
 
0.5%
70210 1
 
0.5%
70207 1
 
0.5%
Other values (173) 173
94.5%
ValueCountFrequency (%)
10101 1
0.5%
10201 1
0.5%
10301 1
0.5%
10401 1
0.5%
10402 1
0.5%
10403 1
0.5%
10404 1
0.5%
10501 1
0.5%
10601 1
0.5%
10701 1
0.5%
ValueCountFrequency (%)
91401 1
0.5%
91302 1
0.5%
91301 1
0.5%
91202 1
0.5%
91201 1
0.5%
91101 1
0.5%
91001 1
0.5%
90901 1
0.5%
90802 1
0.5%
90801 1
0.5%

대사관이름
Text

UNIQUE 

Distinct183
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size1.6 KiB
2023-12-13T02:19:28.784217image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length12
Median length11
Mean length6.8360656
Min length3

Characters and Unicode

Total characters1251
Distinct characters213
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique183 ?
Unique (%)100.0%

Sample

1st row네덜란드대사관
2nd row영국대사관
3rd row폴란드대사관
4th row독일대사관
5th row본분관
ValueCountFrequency (%)
네덜란드대사관 1
 
0.5%
미얀마대사관 1
 
0.5%
오사카총영사관 1
 
0.5%
요코하마총영사관 1
 
0.5%
일본대사관 1
 
0.5%
후쿠오카총영사관 1
 
0.5%
히로시마총영사관 1
 
0.5%
광저우총영사관 1
 
0.5%
다롄출장소 1
 
0.5%
상하이총영사관 1
 
0.5%
Other values (173) 173
94.5%
2023-12-13T02:19:29.170871image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
관 174
 
13.9%
사 166
 
13.3%
대 117
 
9.4%
영 47
 
3.8%
총 45
 
3.6%
스 35
 
2.8%
아 32
 
2.6%
이 24
 
1.9%
르 22
 
1.8%
라 22
 
1.8%
Other values (203) 567
45.3%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1251
100.0%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
관 174
 
13.9%
사 166
 
13.3%
대 117
 
9.4%
영 47
 
3.8%
총 45
 
3.6%
스 35
 
2.8%
아 32
 
2.6%
이 24
 
1.9%
르 22
 
1.8%
라 22
 
1.8%
Other values (203) 567
45.3%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1251
100.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
관 174
 
13.9%
사 166
 
13.3%
대 117
 
9.4%
영 47
 
3.8%
총 45
 
3.6%
스 35
 
2.8%
아 32
 
2.6%
이 24
 
1.9%
르 22
 
1.8%
라 22
 
1.8%
Other values (203) 567
45.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1251
100.0%

Most frequent character per block

Hangul
ValueCountFrequency (%)
관 174
 
13.9%
사 166
 
13.3%
대 117
 
9.4%
영 47
 
3.8%
총 45
 
3.6%
스 35
 
2.8%
아 32
 
2.6%
이 24
 
1.9%
르 22
 
1.8%
라 22
 
1.8%
Other values (203) 567
45.3%

Interactions

2023-12-13T02:19:26.445931image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T02:19:26.112998image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T02:19:26.556227image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T02:19:26.282032image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-13T02:19:29.269886image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
국가번호대사관번호
국가번호1.0001.000
대사관번호1.0001.000
2023-12-13T02:19:29.356678image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
국가번호대사관번호
국가번호1.0001.000
대사관번호1.0001.000

Missing values

2023-12-13T02:19:26.741307image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-13T02:19:26.879787image/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

국가번호국가명대사관번호대사관이름
0101네덜란드10101네덜란드대사관
1102영국10201영국대사관
2103폴란드10301폴란드대사관
3104독일10401독일대사관
4104독일10404본분관
5104독일10402프랑크푸르트총영사관
6104독일10403함부르크총영사관
7105아일랜드10501아일랜드대사관
8106벨라루스10601벨라루스대사관
9107노르웨이10701노르웨이대사관
국가번호국가명대사관번호대사관이름
173908아랍에미리트90802두바이총영사관
174908아랍에미리트90801아랍에미리트대사관
175909레바논90901레바논대사관
176910쿠웨이트91001쿠웨이트대사관
177911이란91101이란대사관
178912이라크91202아르빌사무소
179912이라크91201이라크대사관
180913터키91302이스탄불총영사관
181913터키91301터키대사관
182914바레인91401바레인