Overview

Dataset statistics

Number of variables3
Number of observations5020
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory127.6 KiB
Average record size in memory26.0 B

Variable types

Numeric2
Text1

Dataset

Description국토지리정보원의 구지형도 관련 메타데이터 중 읍면동코드 입니다. (시군구코드, 읍면동코드, 읍면동명 등 포함)
Author국토교통부 국토지리정보원
URLhttps://www.data.go.kr/data/15067695/fileData.do

Alerts

시군구코드 is highly overall correlated with 음면동코드High correlation
음면동코드 is highly overall correlated with 시군구코드High correlation
음면동코드 has unique valuesUnique

Reproduction

Analysis started2023-12-12 05:34:25.472959
Analysis finished2023-12-12 05:34:26.562445
Duration1.09 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

시군구코드
Real number (ℝ)

HIGH CORRELATION 

Distinct252
Distinct (%)5.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean38593.247
Minimum11110
Maximum50130
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size44.2 KiB
2023-12-12T14:34:26.656229image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum11110
5-th percentile11290
Q130110
median43111
Q346860
95-th percentile48730
Maximum50130
Range39020
Interquartile range (IQR)16750

Descriptive statistics

Standard deviation11251.378
Coefficient of variation (CV)0.29153747
Kurtosis0.56857537
Mean38593.247
Median Absolute Deviation (MAD)4059
Skewness-1.2933169
Sum1.937381 × 108
Variance1.265935 × 108
MonotonicityNot monotonic
2023-12-12T14:34:26.872683image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
11110 87
 
1.7%
29200 79
 
1.6%
11140 74
 
1.5%
48160 73
 
1.5%
48190 65
 
1.3%
48110 64
 
1.3%
46110 64
 
1.3%
45130 63
 
1.3%
46130 58
 
1.2%
27110 57
 
1.1%
Other values (242) 4336
86.4%
ValueCountFrequency (%)
11110 87
1.7%
11140 74
1.5%
11170 36
0.7%
11200 17
 
0.3%
11215 9
 
0.2%
11230 10
 
0.2%
11260 6
 
0.1%
11290 39
0.8%
11305 4
 
0.1%
11320 4
 
0.1%
ValueCountFrequency (%)
50130 27
0.5%
50110 47
0.9%
49720 5
 
0.1%
49710 7
 
0.1%
49130 22
0.4%
49110 40
0.8%
48890 17
 
0.3%
48880 12
 
0.2%
48870 11
 
0.2%
48860 11
 
0.2%

음면동코드
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct5020
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean38593428
Minimum11110101
Maximum50130320
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size44.2 KiB
2023-12-12T14:34:27.095606image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum11110101
5-th percentile11290113
Q130110132
median43111138
Q346860362
95-th percentile48730380
Maximum50130320
Range39020219
Interquartile range (IQR)16750231

Descriptive statistics

Standard deviation11251414
Coefficient of variation (CV)0.29153705
Kurtosis0.56856339
Mean38593428
Median Absolute Deviation (MAD)4058992
Skewness-1.2933131
Sum1.9373901 × 1011
Variance1.2659432 × 1014
MonotonicityNot monotonic
2023-12-12T14:34:27.601222image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
41550400 1
 
< 0.1%
46130115 1
 
< 0.1%
46130113 1
 
< 0.1%
46130109 1
 
< 0.1%
46130110 1
 
< 0.1%
46130104 1
 
< 0.1%
46130114 1
 
< 0.1%
46130108 1
 
< 0.1%
46130107 1
 
< 0.1%
46130101 1
 
< 0.1%
Other values (5010) 5010
99.8%
ValueCountFrequency (%)
11110101 1
< 0.1%
11110102 1
< 0.1%
11110103 1
< 0.1%
11110104 1
< 0.1%
11110105 1
< 0.1%
11110106 1
< 0.1%
11110107 1
< 0.1%
11110108 1
< 0.1%
11110109 1
< 0.1%
11110110 1
< 0.1%
ValueCountFrequency (%)
50130320 1
< 0.1%
50130310 1
< 0.1%
50130259 1
< 0.1%
50130253 1
< 0.1%
50130250 1
< 0.1%
50130122 1
< 0.1%
50130121 1
< 0.1%
50130120 1
< 0.1%
50130119 1
< 0.1%
50130118 1
< 0.1%

읍면동명
Text

Distinct3882
Distinct (%)77.3%
Missing0
Missing (%)0.0%
Memory size39.3 KiB
2023-12-12T14:34:28.046935image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length6
Median length3
Mean length3.1468127
Min length2

Characters and Unicode

Total characters15797
Distinct characters359
Distinct categories2 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique3236 ?
Unique (%)64.5%

Sample

1st row죽산면
2nd row일죽면
3rd row풍도동
4th row선감동
5th row대부남동
ValueCountFrequency (%)
교동 17
 
0.3%
남면 16
 
0.3%
송정동 14
 
0.3%
중동 13
 
0.3%
서면 12
 
0.2%
북면 10
 
0.2%
중앙동 10
 
0.2%
신흥동 9
 
0.2%
내동 9
 
0.2%
금곡동 9
 
0.2%
Other values (3872) 4901
97.6%
2023-12-12T14:34:28.610525image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
동 3703
23.4%
면 1218
 
7.7%
가 505
 
3.2%
산 363
 
2.3%
남 228
 
1.4%
읍 227
 
1.4%
성 213
 
1.3%
신 212
 
1.3%
대 194
 
1.2%
천 187
 
1.2%
Other values (349) 8747
55.4%

Most occurring categories

ValueCountFrequency (%)
Other Letter 15363
97.3%
Decimal Number 434
 
2.7%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
동 3703
24.1%
면 1218
 
7.9%
가 505
 
3.3%
산 363
 
2.4%
남 228
 
1.5%
읍 227
 
1.5%
성 213
 
1.4%
신 212
 
1.4%
대 194
 
1.3%
천 187
 
1.2%
Other values (341) 8313
54.1%
Decimal Number
ValueCountFrequency (%)
1 133
30.6%
2 131
30.2%
3 87
20.0%
4 40
 
9.2%
5 24
 
5.5%
6 12
 
2.8%
7 6
 
1.4%
8 1
 
0.2%

Most occurring scripts

ValueCountFrequency (%)
Hangul 15363
97.3%
Common 434
 
2.7%

Most frequent character per script

Hangul
ValueCountFrequency (%)
동 3703
24.1%
면 1218
 
7.9%
가 505
 
3.3%
산 363
 
2.4%
남 228
 
1.5%
읍 227
 
1.5%
성 213
 
1.4%
신 212
 
1.4%
대 194
 
1.3%
천 187
 
1.2%
Other values (341) 8313
54.1%
Common
ValueCountFrequency (%)
1 133
30.6%
2 131
30.2%
3 87
20.0%
4 40
 
9.2%
5 24
 
5.5%
6 12
 
2.8%
7 6
 
1.4%
8 1
 
0.2%

Most occurring blocks

ValueCountFrequency (%)
Hangul 15363
97.3%
ASCII 434
 
2.7%

Most frequent character per block

Hangul
ValueCountFrequency (%)
동 3703
24.1%
면 1218
 
7.9%
가 505
 
3.3%
산 363
 
2.4%
남 228
 
1.5%
읍 227
 
1.5%
성 213
 
1.4%
신 212
 
1.4%
대 194
 
1.3%
천 187
 
1.2%
Other values (341) 8313
54.1%
ASCII
ValueCountFrequency (%)
1 133
30.6%
2 131
30.2%
3 87
20.0%
4 40
 
9.2%
5 24
 
5.5%
6 12
 
2.8%
7 6
 
1.4%
8 1
 
0.2%

Interactions

2023-12-12T14:34:26.092118image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T14:34:25.808611image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T14:34:26.233710image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T14:34:25.944697image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-12T14:34:28.730285image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
시군구코드음면동코드
시군구코드1.0001.000
음면동코드1.0001.000
2023-12-12T14:34:28.829458image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
시군구코드음면동코드
시군구코드1.0001.000
음면동코드1.0001.000

Missing values

2023-12-12T14:34:26.422370image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-12T14:34:26.527036image/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

시군구코드음면동코드읍면동명
04155041550400죽산면
14155041550390일죽면
24127341273114풍도동
34127341273113선감동
44127341273112대부남동
54127341273110대부동동
64127341273111대부북동
74127341273105원시동
84127341273106목내동
94127341273104성곡동
시군구코드음면동코드읍면동명
50105011050110111화북일동
50115011050110103이도일동
50125011050110106삼도이동
50135011050110131도련이동
50145011050110130도련일동
50155011050110108용담일동
50165011050110133회천동
50175011050110112화북이동
50185011050110101일도일동
50195011050110105삼도일동