Overview

Dataset statistics

Number of variables3
Number of observations30
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory852.0 B
Average record size in memory28.4 B

Variable types

Numeric1
Categorical1
Text1

Dataset

Description샘플 데이터
Author국토연구원
URLhttps://www.bigdata-region.kr/#/dataset/776d810a-35dd-4c76-9cb4-9043ef754ee0

Alerts

관리번호 is highly overall correlated with 시도명High correlation
시도명 is highly overall correlated with 관리번호High correlation

Reproduction

Analysis started2023-12-10 14:14:23.079605
Analysis finished2023-12-10 14:14:24.590572
Duration1.51 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

관리번호
Real number (ℝ)

HIGH CORRELATION 

Distinct26
Distinct (%)86.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1.8738316 × 1024
Minimum1.1110121 × 1024
Maximum3.0200111 × 1024
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size402.0 B
2023-12-10T23:14:24.689136image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1.1110121 × 1024
5-th percentile1.1123649 × 1024
Q11.1290101 × 1024
median1.1740107 × 1024
Q32.8567714 × 1024
95-th percentile2.9170117 × 1024
Maximum3.0200111 × 1024
Range1.908999 × 1024
Interquartile range (IQR)1.7277613 × 1024

Descriptive statistics

Standard deviation8.5981864 × 1023
Coefficient of variation (CV)0.45885587
Kurtosis-2.0111346
Mean1.8738316 × 1024
Median Absolute Deviation (MAD)6.149615 × 1022
Skewness0.30646457
Sum5.6214949 × 1025
Variance7.3928809 × 1047
MonotonicityIncreasing
2023-12-10T23:14:24.921621image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=26)
ValueCountFrequency (%)
1.12901010010081e+24 3
 
10.0%
1.17401070010139e+24 3
 
10.0%
1.11101210010001e+24 1
 
3.3%
2.67103202110442e+24 1
 
3.3%
3.02001110010541e+24 1
 
3.3%
2.91701170020083e+24 1
 
3.3%
2.91701160010779e+24 1
 
3.3%
2.91551230010127e+24 1
 
3.3%
2.91401200011161e+24 1
 
3.3%
2.87103902710643e+24 1
 
3.3%
Other values (16) 16
53.3%
ValueCountFrequency (%)
1.11101210010001e+24 1
 
3.3%
1.11101840010239e+24 1
 
3.3%
1.11401070010117e+24 1
 
3.3%
1.11701190010255e+24 1
 
3.3%
1.11701310010742e+24 1
 
3.3%
1.11701350010168e+24 1
 
3.3%
1.12901010010081e+24 3
10.0%
1.1290101001033004e+24 1
 
3.3%
1.14401220010096e+24 1
 
3.3%
1.15001030011097e+24 1
 
3.3%
ValueCountFrequency (%)
3.02001110010541e+24 1
3.3%
2.91701170020083e+24 1
3.3%
2.91701160010779e+24 1
3.3%
2.91551230010127e+24 1
3.3%
2.91401200011161e+24 1
3.3%
2.87103902710643e+24 1
3.3%
2.87103702310814e+24 1
3.3%
2.87102502511006e+24 1
3.3%
2.81401060010033e+24 1
3.3%
2.81101380010102e+24 1
3.3%

시도명
Categorical

HIGH CORRELATION 

Distinct5
Distinct (%)16.7%
Missing0
Missing (%)0.0%
Memory size372.0 B
서울특별시
17 
인천광역시
5 
광주광역시
4 
부산광역시
3 
대전광역시
 
1

Length

Max length5
Median length5
Mean length5
Min length5

Unique

Unique1 ?
Unique (%)3.3%

Sample

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

Common Values

ValueCountFrequency (%)
서울특별시 17
56.7%
인천광역시 5
 
16.7%
광주광역시 4
 
13.3%
부산광역시 3
 
10.0%
대전광역시 1
 
3.3%

Length

2023-12-10T23:14:25.197434image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T23:14:25.409764image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
서울특별시 17
56.7%
인천광역시 5
 
16.7%
광주광역시 4
 
13.3%
부산광역시 3
 
10.0%
대전광역시 1
 
3.3%

시군구명
Text

Distinct15
Distinct (%)50.0%
Missing0
Missing (%)0.0%
Memory size372.0 B
2023-12-10T23:14:25.663793image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length3
Median length3
Mean length2.7333333
Min length2

Characters and Unicode

Total characters82
Distinct characters21
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

Unique6 ?
Unique (%)20.0%

Sample

1st row종로구
2nd row종로구
3rd row중구
4th row용산구
5th row용산구
ValueCountFrequency (%)
성북구 4
13.3%
중구 3
10.0%
용산구 3
10.0%
강동구 3
10.0%
강화군 3
10.0%
종로구 2
 
6.7%
강서구 2
 
6.7%
기장군 2
 
6.7%
북구 2
 
6.7%
마포구 1
 
3.3%
Other values (5) 5
16.7%
2023-12-10T23:14:26.237540image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
구 25
30.5%
강 8
 
9.8%
북 6
 
7.3%
성 5
 
6.1%
군 5
 
6.1%
동 4
 
4.9%
중 3
 
3.7%
용 3
 
3.7%
산 3
 
3.7%
화 3
 
3.7%
Other values (11) 17
20.7%

Most occurring categories

ValueCountFrequency (%)
Other Letter 82
100.0%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
구 25
30.5%
강 8
 
9.8%
북 6
 
7.3%
성 5
 
6.1%
군 5
 
6.1%
동 4
 
4.9%
중 3
 
3.7%
용 3
 
3.7%
산 3
 
3.7%
화 3
 
3.7%
Other values (11) 17
20.7%

Most occurring scripts

ValueCountFrequency (%)
Hangul 82
100.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
구 25
30.5%
강 8
 
9.8%
북 6
 
7.3%
성 5
 
6.1%
군 5
 
6.1%
동 4
 
4.9%
중 3
 
3.7%
용 3
 
3.7%
산 3
 
3.7%
화 3
 
3.7%
Other values (11) 17
20.7%

Most occurring blocks

ValueCountFrequency (%)
Hangul 82
100.0%

Most frequent character per block

Hangul
ValueCountFrequency (%)
구 25
30.5%
강 8
 
9.8%
북 6
 
7.3%
성 5
 
6.1%
군 5
 
6.1%
동 4
 
4.9%
중 3
 
3.7%
용 3
 
3.7%
산 3
 
3.7%
화 3
 
3.7%
Other values (11) 17
20.7%

Interactions

2023-12-10T23:14:23.773543image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-10T23:14:26.404207image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
관리번호시도명시군구명
관리번호1.0000.7610.841
시도명0.7611.0000.995
시군구명0.8410.9951.000
2023-12-10T23:14:26.551490image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
관리번호시도명
관리번호1.0001.000
시도명1.0001.000

Missing values

2023-12-10T23:14:24.387750image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-10T23:14:24.521714image/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

관리번호시도명시군구명
01111012100100010126028567서울특별시종로구
11111018400102390011025617서울특별시종로구
21114010700101170000018957서울특별시중구
31117011900102550000017081서울특별시용산구
41117013100107420001005841서울특별시용산구
51117013500101680006028327서울특별시용산구
61129010100100810001051882서울특별시성북구
71129010100100810001052079서울특별시성북구
81129010100100810001052089서울특별시성북구
91129010100103300484000001서울특별시성북구
관리번호시도명시군구명
202811013800101020002240022인천광역시중구
212814010600100330003122177인천광역시동구
222871025025110060000016965인천광역시강화군
232871037023108140000000001인천광역시강화군
242871039027106430001042402인천광역시강화군
252914012000111610006003647광주광역시서구
262915512300101270001014493광주광역시남구
272917011600107790001000001광주광역시북구
282917011700200830003037028광주광역시북구
293020011100105410016000001대전광역시유성구