Overview

Dataset statistics

Number of variables4
Number of observations258
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory8.4 KiB
Average record size in memory33.5 B

Variable types

Numeric1
Categorical1
Text2

Dataset

Description인천광역시 각 구의 연번 법정동(리)명, 관할 행정 읍·면·동 현황 등이다.
Author인천광역시
URLhttps://data.incheon.go.kr/findData/publicDataDetail?dataId=15062332&srcSe=7661IVAWM27C61E190

Alerts

연번 is highly overall correlated with 군구명High correlation
군구명 is highly overall correlated with 연번High correlation
연번 has unique valuesUnique

Reproduction

Analysis started2024-01-28 15:12:12.414328
Analysis finished2024-01-28 15:12:12.886893
Duration0.47 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

연번
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct258
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean129.5
Minimum1
Maximum258
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size2.4 KiB
2024-01-29T00:12:12.943829image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile13.85
Q165.25
median129.5
Q3193.75
95-th percentile245.15
Maximum258
Range257
Interquartile range (IQR)128.5

Descriptive statistics

Standard deviation74.622383
Coefficient of variation (CV)0.57623462
Kurtosis-1.2
Mean129.5
Median Absolute Deviation (MAD)64.5
Skewness0
Sum33411
Variance5568.5
MonotonicityStrictly increasing
2024-01-29T00:12:13.053036image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 1
 
0.4%
195 1
 
0.4%
165 1
 
0.4%
166 1
 
0.4%
167 1
 
0.4%
168 1
 
0.4%
169 1
 
0.4%
170 1
 
0.4%
171 1
 
0.4%
172 1
 
0.4%
Other values (248) 248
96.1%
ValueCountFrequency (%)
1 1
0.4%
2 1
0.4%
3 1
0.4%
4 1
0.4%
5 1
0.4%
6 1
0.4%
7 1
0.4%
8 1
0.4%
9 1
0.4%
10 1
0.4%
ValueCountFrequency (%)
258 1
0.4%
257 1
0.4%
256 1
0.4%
255 1
0.4%
254 1
0.4%
253 1
0.4%
252 1
0.4%
251 1
0.4%
250 1
0.4%
249 1
0.4%

군구명
Categorical

HIGH CORRELATION 

Distinct10
Distinct (%)3.9%
Missing0
Missing (%)0.0%
Memory size2.1 KiB
강화군
96 
중구
52 
옹진군
26 
계양구
23 
서구
21 
Other values (5)
40 

Length

Max length4
Median length3
Mean length2.7170543
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
강화군 96
37.2%
중구 52
20.2%
옹진군 26
 
10.1%
계양구 23
 
8.9%
서구 21
 
8.1%
남동구 11
 
4.3%
부평구 9
 
3.5%
동구 7
 
2.7%
미추홀구 7
 
2.7%
연수구 6
 
2.3%

Length

2024-01-29T00:12:13.163617image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-01-29T00:12:13.268829image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
강화군 96
37.2%
중구 52
20.2%
옹진군 26
 
10.1%
계양구 23
 
8.9%
서구 21
 
8.1%
남동구 11
 
4.3%
부평구 9
 
3.5%
동구 7
 
2.7%
미추홀구 7
 
2.7%
연수구 6
 
2.3%

법정동(리)명
Text

Distinct255
Distinct (%)98.8%
Missing0
Missing (%)0.0%
Memory size2.1 KiB
2024-01-29T00:12:13.523138image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length12
Median length8
Mean length8.3023256
Min length6

Characters and Unicode

Total characters2142
Distinct characters406
Distinct categories4 ?
Distinct scripts3 ?
Distinct blocks4 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique252 ?
Unique (%)97.7%

Sample

1st row관동1가(官洞1街)
2nd row관동2가(官洞2街)
3rd row관동3가(官洞3街)
4th row중앙동1가(中央洞1街)
5th row중앙동2가(中央洞2街)
ValueCountFrequency (%)
내리(內里 2
 
0.8%
오류동(梧柳洞 2
 
0.8%
금곡동(金谷洞 2
 
0.8%
승봉리(昇鳳里 1
 
0.4%
하일리(霞逸里 1
 
0.4%
하리(下里 1
 
0.4%
조산리(造山里 1
 
0.4%
관동1가(官洞1街 1
 
0.4%
도장리(道場里 1
 
0.4%
길직리(吉稷里 1
 
0.4%
Other values (245) 245
95.0%
2024-01-29T00:12:13.876139image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
( 258
 
12.0%
) 258
 
12.0%
동 142
 
6.6%
洞 136
 
6.3%
리 122
 
5.7%
里 122
 
5.7%
가 33
 
1.5%
街 30
 
1.4%
山 17
 
0.8%
산 17
 
0.8%
Other values (396) 1007
47.0%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1566
73.1%
Open Punctuation 258
 
12.0%
Close Punctuation 258
 
12.0%
Decimal Number 60
 
2.8%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
동 142
 
9.1%
洞 136
 
8.7%
리 122
 
7.8%
里 122
 
7.8%
가 33
 
2.1%
街 30
 
1.9%
山 17
 
1.1%
산 17
 
1.1%
도 15
 
1.0%
신 14
 
0.9%
Other values (387) 918
58.6%
Decimal Number
ValueCountFrequency (%)
2 16
26.7%
1 16
26.7%
3 16
26.7%
4 6
 
10.0%
6 2
 
3.3%
7 2
 
3.3%
5 2
 
3.3%
Open Punctuation
ValueCountFrequency (%)
( 258
100.0%
Close Punctuation
ValueCountFrequency (%)
) 258
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 783
36.6%
Han 783
36.6%
Common 576
26.9%

Most frequent character per script

Han
ValueCountFrequency (%)
洞 136
 
17.4%
里 122
 
15.6%
街 30
 
3.8%
山 17
 
2.2%
新 11
 
1.4%
鶴 9
 
1.1%
島 9
 
1.1%
松 9
 
1.1%
北 8
 
1.0%
月 8
 
1.0%
Other values (225) 424
54.2%
Hangul
ValueCountFrequency (%)
동 142
 
18.1%
리 122
 
15.6%
가 33
 
4.2%
산 17
 
2.2%
도 15
 
1.9%
신 14
 
1.8%
학 9
 
1.1%
정 9
 
1.1%
송 9
 
1.1%
화 9
 
1.1%
Other values (152) 404
51.6%
Common
ValueCountFrequency (%)
( 258
44.8%
) 258
44.8%
2 16
 
2.8%
1 16
 
2.8%
3 16
 
2.8%
4 6
 
1.0%
6 2
 
0.3%
7 2
 
0.3%
5 2
 
0.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 783
36.6%
CJK 765
35.7%
ASCII 576
26.9%
CJK Compat Ideographs 18
 
0.8%

Most frequent character per block

ASCII
ValueCountFrequency (%)
( 258
44.8%
) 258
44.8%
2 16
 
2.8%
1 16
 
2.8%
3 16
 
2.8%
4 6
 
1.0%
6 2
 
0.3%
7 2
 
0.3%
5 2
 
0.3%
Hangul
ValueCountFrequency (%)
동 142
 
18.1%
리 122
 
15.6%
가 33
 
4.2%
산 17
 
2.2%
도 15
 
1.9%
신 14
 
1.8%
학 9
 
1.1%
정 9
 
1.1%
송 9
 
1.1%
화 9
 
1.1%
Other values (152) 404
51.6%
CJK
ValueCountFrequency (%)
洞 136
 
17.8%
里 122
 
15.9%
街 30
 
3.9%
山 17
 
2.2%
新 11
 
1.4%
鶴 9
 
1.2%
島 9
 
1.2%
松 9
 
1.2%
北 8
 
1.0%
月 8
 
1.0%
Other values (214) 406
53.1%
CJK Compat Ideographs
ValueCountFrequency (%)
龍 6
33.3%
林 2
 
11.1%
梨 2
 
11.1%
率 1
 
5.6%
蓮 1
 
5.6%
兩 1
 
5.6%
論 1
 
5.6%
栗 1
 
5.6%
柳 1
 
5.6%
老 1
 
5.6%

관할 행정 읍·면·동
Text

Distinct93
Distinct (%)36.0%
Missing0
Missing (%)0.0%
Memory size2.1 KiB
2024-01-29T00:12:14.130271image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length34
Median length3
Mean length5.120155
Min length3

Characters and Unicode

Total characters1321
Distinct characters109
Distinct categories5 ?
Distinct scripts2 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique54 ?
Unique (%)20.9%

Sample

1st row신포동
2nd row신포동
3rd row신포동
4th row신포동
5th row신포동
ValueCountFrequency (%)
63
 
16.4%
신포동 25
 
6.5%
교동면 13
 
3.4%
계양1동 12
 
3.1%
강화읍 9
 
2.3%
화도면 9
 
2.3%
하점면 8
 
2.1%
덕적면 8
 
2.1%
불은면 8
 
2.1%
양도면 8
 
2.1%
Other values (116) 221
57.6%
2024-01-29T00:12:14.474458image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
동 219
 
16.6%
126
 
9.5%
면 113
 
8.6%
1 50
 
3.8%
/ 48
 
3.6%
양 34
 
2.6%
도 33
 
2.5%
신 29
 
2.2%
화 28
 
2.1%
포 25
 
1.9%
Other values (99) 616
46.6%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1014
76.8%
Space Separator 126
 
9.5%
Decimal Number 108
 
8.2%
Other Punctuation 58
 
4.4%
Math Symbol 15
 
1.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
동 219
21.6%
면 113
 
11.1%
양 34
 
3.4%
도 33
 
3.3%
신 29
 
2.9%
화 28
 
2.8%
포 25
 
2.5%
계 24
 
2.4%
송 20
 
2.0%
산 18
 
1.8%
Other values (88) 471
46.4%
Decimal Number
ValueCountFrequency (%)
1 50
46.3%
2 23
21.3%
3 19
 
17.6%
4 10
 
9.3%
6 3
 
2.8%
5 2
 
1.9%
8 1
 
0.9%
Other Punctuation
ValueCountFrequency (%)
/ 48
82.8%
· 10
 
17.2%
Space Separator
ValueCountFrequency (%)
126
100.0%
Math Symbol
ValueCountFrequency (%)
~ 15
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1014
76.8%
Common 307
 
23.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
동 219
21.6%
면 113
 
11.1%
양 34
 
3.4%
도 33
 
3.3%
신 29
 
2.9%
화 28
 
2.8%
포 25
 
2.5%
계 24
 
2.4%
송 20
 
2.0%
산 18
 
1.8%
Other values (88) 471
46.4%
Common
ValueCountFrequency (%)
126
41.0%
1 50
 
16.3%
/ 48
 
15.6%
2 23
 
7.5%
3 19
 
6.2%
~ 15
 
4.9%
· 10
 
3.3%
4 10
 
3.3%
6 3
 
1.0%
5 2
 
0.7%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1014
76.8%
ASCII 297
 
22.5%
None 10
 
0.8%

Most frequent character per block

Hangul
ValueCountFrequency (%)
동 219
21.6%
면 113
 
11.1%
양 34
 
3.4%
도 33
 
3.3%
신 29
 
2.9%
화 28
 
2.8%
포 25
 
2.5%
계 24
 
2.4%
송 20
 
2.0%
산 18
 
1.8%
Other values (88) 471
46.4%
ASCII
ValueCountFrequency (%)
126
42.4%
1 50
 
16.8%
/ 48
 
16.2%
2 23
 
7.7%
3 19
 
6.4%
~ 15
 
5.1%
4 10
 
3.4%
6 3
 
1.0%
5 2
 
0.7%
8 1
 
0.3%
None
ValueCountFrequency (%)
· 10
100.0%

Interactions

2024-01-29T00:12:12.713362image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-01-29T00:12:14.549024image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연번군구명관할 행정 읍·면·동
연번1.0000.9630.996
군구명0.9631.0001.000
관할 행정 읍·면·동0.9961.0001.000
2024-01-29T00:12:14.615299image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연번군구명
연번1.0000.668
군구명0.6681.000

Missing values

2024-01-29T00:12:12.794683image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-01-29T00:12:12.859601image/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

연번군구명법정동(리)명관할 행정 읍·면·동
01중구관동1가(官洞1街)신포동
12중구관동2가(官洞2街)신포동
23중구관동3가(官洞3街)신포동
34중구중앙동1가(中央洞1街)신포동
45중구중앙동2가(中央洞2街)신포동
56중구중앙동3가(中央洞3街)신포동
67중구중앙동4가(中央洞4街)신포동
78중구해안동1가(海岸洞1街)신포동
89중구해안동2가(海岸洞2街)신포동
910중구해안동3가(海岸洞3街)신포동
연번군구명법정동(리)명관할 행정 읍·면·동
248249옹진군문갑리(文甲里)덕적면
249250옹진군백아리(白牙里)덕적면
250251옹진군울도리(蔚島里)덕적면
251252옹진군굴업리(堀業里)덕적면
252253옹진군자월리(紫月里)자월면
253254옹진군이작리(伊作里)자월면
254255옹진군승봉리(昇鳳里)자월면
255256옹진군내리(內里)영흥면
256257옹진군외리(外里)영흥면
257258옹진군선재리(仙才里)영흥면