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

Description출생인구(행정동, 성별, 인원) 정보를 제공합니다.
Author충청남도
URLhttps://alldam.chungnam.go.kr/bigdata/collect/view.chungnam?menuCd=DOM_000000201001001000&apiIdx=92

Alerts

인원수 has 2161 (21.6%) zerosZeros

Reproduction

Analysis started2024-01-09 21:02:15.842229
Analysis finished2024-01-09 21:02:17.125952
Duration1.28 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%
Mean201504.59
Minimum201501
Maximum201509
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-01-10T06:02:17.182223image/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 deviation2.3267271
Coefficient of variation (CV)1.154677 × 10-5
Kurtosis-1.2031842
Mean201504.59
Median Absolute Deviation (MAD)2
Skewness0.0081636514
Sum2.0150459 × 109
Variance5.413659
MonotonicityNot monotonic
2024-01-10T06:02:17.313131image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=9)
ValueCountFrequency (%)
201507 1291
12.9%
201503 1243
12.4%
201502 1239
12.4%
201505 1236
12.4%
201504 1233
12.3%
201508 1224
12.2%
201506 1219
12.2%
201501 1172
11.7%
201509 143
 
1.4%
ValueCountFrequency (%)
201501 1172
11.7%
201502 1239
12.4%
201503 1243
12.4%
201504 1233
12.3%
201505 1236
12.4%
201506 1219
12.2%
201507 1291
12.9%
201508 1224
12.2%
201509 143
 
1.4%
ValueCountFrequency (%)
201509 143
 
1.4%
201508 1224
12.2%
201507 1291
12.9%
201506 1219
12.2%
201505 1236
12.4%
201504 1233
12.3%
201503 1243
12.4%
201502 1239
12.4%
201501 1172
11.7%

행정동코드
Real number (ℝ)

Distinct3385
Distinct (%)33.9%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean3.7031634 × 109
Minimum1.1110515 × 109
Maximum5.013062 × 109
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-01-10T06:02:17.472335image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1.1110515 × 109
5-th percentile1.1350621 × 109
Q12.820066 × 109
median4.211036 × 109
Q34.672036 × 109
95-th percentile4.831054 × 109
Maximum5.013062 × 109
Range3.9020105 × 109
Interquartile range (IQR)1.85197 × 109

Descriptive statistics

Standard deviation1.2189185 × 109
Coefficient of variation (CV)0.32915601
Kurtosis-0.18716584
Mean3.7031634 × 109
Median Absolute Deviation (MAD)5.080235 × 108
Skewness-1.0607275
Sum3.7031634 × 1013
Variance1.4857623 × 1018
MonotonicityNot monotonic
2024-01-10T06:02:17.648008image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
4119956000 12
 
0.1%
1162068500 8
 
0.1%
4690035000 8
 
0.1%
4136051000 8
 
0.1%
1165055000 8
 
0.1%
4278025900 8
 
0.1%
4122025600 8
 
0.1%
4519031000 8
 
0.1%
4113554000 8
 
0.1%
4611051000 8
 
0.1%
Other values (3375) 9916
99.2%
ValueCountFrequency (%)
1111051500 1
 
< 0.1%
1111053000 3
< 0.1%
1111054000 5
0.1%
1111055000 2
 
< 0.1%
1111056000 2
 
< 0.1%
1111057000 2
 
< 0.1%
1111058000 3
< 0.1%
1111060000 2
 
< 0.1%
1111061500 5
0.1%
1111063000 1
 
< 0.1%
ValueCountFrequency (%)
5013062000 1
 
< 0.1%
5013060000 4
< 0.1%
5013059000 3
< 0.1%
5013058000 5
0.1%
5013057000 3
< 0.1%
5013056000 4
< 0.1%
5013055000 2
 
< 0.1%
5013054000 2
 
< 0.1%
5013053000 5
0.1%
5013052000 1
 
< 0.1%

성별코드
Categorical

Distinct3
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
1
3421 
2
3294 
0
3285 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
1 3421
34.2%
2 3294
32.9%
0 3285
32.9%

Length

2024-01-10T06:02:17.810801image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-01-10T06:02:17.929153image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
1 3421
34.2%
2 3294
32.9%
0 3285
32.9%

인원수
Real number (ℝ)

ZEROS 

Distinct84
Distinct (%)0.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean7.0624
Minimum0
Maximum109
Zeros2161
Zeros (%)21.6%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-01-10T06:02:18.045359image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q11
median4
Q310
95-th percentile25
Maximum109
Range109
Interquartile range (IQR)9

Descriptive statistics

Standard deviation9.4633113
Coefficient of variation (CV)1.3399569
Kurtosis15.264818
Mean7.0624
Median Absolute Deviation (MAD)4
Skewness2.9758196
Sum70624
Variance89.554262
MonotonicityNot monotonic
2024-01-10T06:02:18.179830image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 2161
21.6%
1 1276
12.8%
2 859
 
8.6%
3 603
 
6.0%
5 490
 
4.9%
4 485
 
4.9%
6 418
 
4.2%
7 373
 
3.7%
8 373
 
3.7%
11 293
 
2.9%
Other values (74) 2669
26.7%
ValueCountFrequency (%)
0 2161
21.6%
1 1276
12.8%
2 859
 
8.6%
3 603
 
6.0%
4 485
 
4.9%
5 490
 
4.9%
6 418
 
4.2%
7 373
 
3.7%
8 373
 
3.7%
9 289
 
2.9%
ValueCountFrequency (%)
109 1
< 0.1%
101 2
< 0.1%
100 1
< 0.1%
98 1
< 0.1%
93 1
< 0.1%
90 1
< 0.1%
89 1
< 0.1%
87 1
< 0.1%
85 1
< 0.1%
84 1
< 0.1%

Interactions

2024-01-10T06:02:16.688707image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T06:02:16.113107image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T06:02:16.391046image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T06:02:16.787516image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T06:02:16.210286image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T06:02:16.489444image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T06:02:16.887440image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T06:02:16.306315image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T06:02:16.584980image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-01-10T06:02:18.272059image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
기준연월행정동코드성별코드인원수
기준연월1.0000.3140.0000.034
행정동코드0.3141.0000.0000.255
성별코드0.0000.0001.0000.292
인원수0.0340.2550.2921.000
2024-01-10T06:02:18.379275image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
기준연월행정동코드인원수성별코드
기준연월1.000-0.0330.0040.000
행정동코드-0.0331.000-0.4380.000
인원수0.004-0.4381.0000.182
성별코드0.0000.0000.1821.000

Missing values

2024-01-10T06:02:16.984288image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-01-10T06:02:17.083634image/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
46465201505411716100018
579812015064148032000010
49955201505457104100020
20274201502481255400004
31157201503482203500020
676802015074113563000016
20027201502478303200020
45572015014143055000034
472712015054146357000025
441152015052626075000020
기준연월행정동코드성별코드인원수
429842015051129071500026
26735201503421906150020
39801201504461706000004
68305201507412905600012
84152201508479403100020
823872015084615066100111
28572201503452104200000
34700201504287104250020
53110201505488903700010
82726201508468003100010