Overview

Dataset statistics

Number of variables4
Number of observations10000
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory429.7 KiB
Average record size in memory44.0 B

Variable types

Numeric3
Categorical1

Dataset

Description사망인구(행정동, 성별, 인원) 정보를 제공합니다.
Author충청남도
URLhttps://alldam.chungnam.go.kr/bigdata/collect/view.chungnam?menuCd=DOM_000000201001001000&apiIdx=93

Alerts

인원수 has 897 (9.0%) zerosZeros

Reproduction

Analysis started2024-01-09 22:20:59.707668
Analysis finished2024-01-09 22:21:01.073368
Duration1.37 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

기준연월
Real number (ℝ)

Distinct9
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean201504.6
Minimum201501
Maximum201509
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-01-10T07:21:01.115943image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum201501
5-th percentile201501
Q1201503
median201505
Q3201507
95-th percentile201508
Maximum201509
Range8
Interquartile range (IQR)4

Descriptive statistics

Standard deviation2.3427558
Coefficient of variation (CV)1.1626315 × 10-5
Kurtosis-1.2133955
Mean201504.6
Median Absolute Deviation (MAD)2
Skewness0.00948324
Sum2.015046 × 109
Variance5.4885048
MonotonicityNot monotonic
2024-01-10T07:21:01.221191image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=9)
ValueCountFrequency (%)
201508 1267
12.7%
201507 1256
12.6%
201503 1253
12.5%
201506 1228
12.3%
201502 1226
12.3%
201505 1217
12.2%
201504 1202
12.0%
201501 1201
12.0%
201509 150
 
1.5%
ValueCountFrequency (%)
201501 1201
12.0%
201502 1226
12.3%
201503 1253
12.5%
201504 1202
12.0%
201505 1217
12.2%
201506 1228
12.3%
201507 1256
12.6%
201508 1267
12.7%
201509 150
 
1.5%
ValueCountFrequency (%)
201509 150
 
1.5%
201508 1267
12.7%
201507 1256
12.6%
201506 1228
12.3%
201505 1217
12.2%
201504 1202
12.0%
201503 1253
12.5%
201502 1226
12.3%
201501 1201
12.0%

행정동코드
Real number (ℝ)

Distinct3368
Distinct (%)33.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean3.697879 × 109
Minimum1.1110515 × 109
Maximum5.013062 × 109
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-01-10T07:21:01.328885image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1.1110515 × 109
5-th percentile1.1320681 × 109
Q12.820056 × 109
median4.2110605 × 109
Q34.6720322 × 109
95-th percentile4.833051 × 109
Maximum5.013062 × 109
Range3.9020105 × 109
Interquartile range (IQR)1.8519762 × 109

Descriptive statistics

Standard deviation1.2271877 × 109
Coefficient of variation (CV)0.3318626
Kurtosis-0.2284307
Mean3.697879 × 109
Median Absolute Deviation (MAD)5.11977 × 108
Skewness-1.0466658
Sum3.697879 × 1013
Variance1.5059897 × 1018
MonotonicityNot monotonic
2024-01-10T07:21:01.443452image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
3171025900 9
 
0.1%
1168067000 9
 
0.1%
4613082000 9
 
0.1%
1132068100 9
 
0.1%
1153053000 8
 
0.1%
4146359000 8
 
0.1%
1135069500 8
 
0.1%
4111572000 8
 
0.1%
4374031000 8
 
0.1%
5011055000 8
 
0.1%
Other values (3358) 9916
99.2%
ValueCountFrequency (%)
1111051500 2
 
< 0.1%
1111053000 1
 
< 0.1%
1111054000 3
< 0.1%
1111055000 4
< 0.1%
1111056000 1
 
< 0.1%
1111057000 2
 
< 0.1%
1111058000 5
0.1%
1111060000 4
< 0.1%
1111064000 2
 
< 0.1%
1111065000 2
 
< 0.1%
ValueCountFrequency (%)
5013062000 2
< 0.1%
5013061000 3
< 0.1%
5013060000 3
< 0.1%
5013059000 2
< 0.1%
5013058000 2
< 0.1%
5013057000 4
< 0.1%
5013056000 3
< 0.1%
5013055000 2
< 0.1%
5013054000 4
< 0.1%
5013052000 1
 
< 0.1%

성별코드
Categorical

Distinct3
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2
3381 
0
3329 
1
3290 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row1
3rd row1
4th row0
5th row2

Common Values

ValueCountFrequency (%)
2 3381
33.8%
0 3329
33.3%
1 3290
32.9%

Length

2024-01-10T07:21:01.547344image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-01-10T07:21:01.623362image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2 3381
33.8%
0 3329
33.3%
1 3290
32.9%

인원수
Real number (ℝ)

ZEROS 

Distinct33
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean4.4311
Minimum0
Maximum37
Zeros897
Zeros (%)9.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-01-10T07:21:01.703901image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q12
median3
Q36
95-th percentile12
Maximum37
Range37
Interquartile range (IQR)4

Descriptive statistics

Standard deviation3.8949416
Coefficient of variation (CV)0.87900105
Kurtosis4.457438
Mean4.4311
Median Absolute Deviation (MAD)2
Skewness1.7023558
Sum44311
Variance15.17057
MonotonicityNot monotonic
2024-01-10T07:21:01.798307image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=33)
ValueCountFrequency (%)
2 1474
14.7%
3 1364
13.6%
1 1326
13.3%
4 1113
11.1%
0 897
9.0%
5 895
8.9%
6 722
7.2%
7 486
 
4.9%
8 408
 
4.1%
9 307
 
3.1%
Other values (23) 1008
10.1%
ValueCountFrequency (%)
0 897
9.0%
1 1326
13.3%
2 1474
14.7%
3 1364
13.6%
4 1113
11.1%
5 895
8.9%
6 722
7.2%
7 486
 
4.9%
8 408
 
4.1%
9 307
 
3.1%
ValueCountFrequency (%)
37 1
 
< 0.1%
32 1
 
< 0.1%
31 2
 
< 0.1%
29 2
 
< 0.1%
28 1
 
< 0.1%
27 1
 
< 0.1%
26 3
< 0.1%
25 5
0.1%
24 4
< 0.1%
23 4
< 0.1%

Interactions

2024-01-10T07:21:00.703436image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T07:20:59.979477image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T07:21:00.233172image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T07:21:00.786924image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T07:21:00.066846image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T07:21:00.317962image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T07:21:00.867556image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T07:21:00.152624image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T07:21:00.399141image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-01-10T07:21:01.866093image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
기준연월행정동코드성별코드인원수
기준연월1.0000.3190.0210.086
행정동코드0.3191.0000.0170.211
성별코드0.0210.0171.0000.424
인원수0.0860.2110.4241.000
2024-01-10T07:21:01.937836image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
기준연월행정동코드인원수성별코드
기준연월1.000-0.052-0.0330.008
행정동코드-0.0521.000-0.2610.010
인원수-0.033-0.2611.0000.282
성별코드0.0080.0100.2821.000

Missing values

2024-01-10T07:21:00.963466image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-01-10T07:21:01.040556image/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

기준연월행정동코드성별코드인원수
77769201508301705550006
44584201505271406700014
20668201502482703800013
31236201503482503200000
55646201506281406050021
13519201502291555200010
24695201503311705800021
29159201503462303100021
96201501111705100004
77483201508291556300022
기준연월행정동코드성별코드인원수
16723201502437403350012
52530201505482405100008
68723201507415005200022
57108201506411715800004
86108201509115605350021
149852015024128756000010
66227201507277102570023
56769201506361105300005
9394201501478402500015
19264201502471302500013