Overview

Dataset statistics

Number of variables8
Number of observations100
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory7.0 KiB
Average record size in memory71.3 B

Variable types

Categorical1
Numeric6
Text1

Dataset

Description샘플 데이터
Author지디에스컨설팅그룹
URLhttps://www.bigdata-environment.kr/user/data_market/detail.do?id=8cee0160-2dff-11ea-9713-eb3e5186fb38

Alerts

행정동코드 is highly overall correlated with 법정동코드 and 1 other fieldsHigh correlation
법정동코드 is highly overall correlated with 행정동코드 and 1 other fieldsHigh correlation
총인구수 is highly overall correlated with 총가구수 and 3 other fieldsHigh correlation
총가구수 is highly overall correlated with 총인구수 and 1 other fieldsHigh correlation
가구당인구수 is highly overall correlated with 총인구수 and 1 other fieldsHigh correlation
평균소득금액 is highly overall correlated with 총인구수 and 1 other fieldsHigh correlation
행정동명 is highly overall correlated with 행정동코드 and 5 other fieldsHigh correlation
법정동코드 has unique valuesUnique
평균소득금액 has unique valuesUnique

Reproduction

Analysis started2023-12-10 10:31:52.374353
Analysis finished2023-12-10 10:32:00.674047
Duration8.3 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

행정동명
Categorical

HIGH CORRELATION 

Distinct15
Distinct (%)15.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
강원도 양양군 서면
20 
강원도 인제군 남면
13 
강원도 춘천시 동면
10 
강원도 춘천시 서면
10 
강원도 양구군 동면
7 
Other values (10)
40 

Length

Max length10
Median length10
Mean length10
Min length10

Unique

Unique1 ?
Unique (%)1.0%

Sample

1st row강원도 삼척시 교동
2nd row강원도 삼척시 교동
3rd row강원도 삼척시 교동
4th row강원도 삼척시 교동
5th row강원도 삼척시 교동

Common Values

ValueCountFrequency (%)
강원도 양양군 서면 20
20.0%
강원도 인제군 남면 13
13.0%
강원도 춘천시 동면 10
10.0%
강원도 춘천시 서면 10
10.0%
강원도 양구군 동면 7
 
7.0%
강원도 춘천시 남면 7
 
7.0%
강원도 영월군 남면 6
 
6.0%
강원도 삼척시 교동 5
 
5.0%
강원도 영월군 북면 5
 
5.0%
강원도 정선군 남면 5
 
5.0%
Other values (5) 12
12.0%

Length

2023-12-10T19:32:00.799065image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
강원도 100
33.3%
남면 34
 
11.3%
서면 32
 
10.7%
춘천시 28
 
9.3%
양양군 20
 
6.7%
인제군 17
 
5.7%
동면 17
 
5.7%
영월군 11
 
3.7%
북면 9
 
3.0%
교동 8
 
2.7%
Other values (6) 24
 
8.0%

행정동코드
Real number (ℝ)

HIGH CORRELATION 

Distinct15
Distinct (%)15.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean4.256474 × 109
Minimum4.211031 × 109
Maximum4.283031 × 109
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.0 KiB
2023-12-10T19:32:01.026377image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum4.211031 × 109
5-th percentile4.211031 × 109
Q14.211035 × 109
median4.277032 × 109
Q34.281031 × 109
95-th percentile4.283031 × 109
Maximum4.283031 × 109
Range72000000
Interquartile range (IQR)69996000

Descriptive statistics

Standard deviation32052439
Coefficient of variation (CV)0.0075302796
Kurtosis-1.56936
Mean4.256474 × 109
Median Absolute Deviation (MAD)5999000
Skewness-0.63841663
Sum4.256474 × 1011
Variance1.0273589 × 1015
MonotonicityNot monotonic
2023-12-10T19:32:01.261579image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=15)
ValueCountFrequency (%)
4283031000 20
20.0%
4281031000 13
13.0%
4211031000 10
10.0%
4211035000 10
10.0%
4280032000 7
 
7.0%
4211034000 7
 
7.0%
4275034000 6
 
6.0%
4223053000 5
 
5.0%
4275033000 5
 
5.0%
4277032000 5
 
5.0%
Other values (5) 12
12.0%
ValueCountFrequency (%)
4211031000 10
10.0%
4211034000 7
7.0%
4211035000 10
10.0%
4211052000 1
 
1.0%
4221056000 2
 
2.0%
4223053000 5
5.0%
4272036000 3
 
3.0%
4275033000 5
5.0%
4275034000 6
6.0%
4277032000 5
5.0%
ValueCountFrequency (%)
4283031000 20
20.0%
4281032000 4
 
4.0%
4281031000 13
13.0%
4280032000 7
 
7.0%
4278031000 2
 
2.0%
4277032000 5
 
5.0%
4275034000 6
 
6.0%
4275033000 5
 
5.0%
4272036000 3
 
3.0%
4223053000 5
 
5.0%

법정동명
Text

Distinct97
Distinct (%)97.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
2023-12-10T19:32:01.738059image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length4
Median length3
Mean length3.01
Min length2

Characters and Unicode

Total characters301
Distinct characters99
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

Unique95 ?
Unique (%)95.0%

Sample

1st row교동
2nd row증산동
3rd row마달동
4th row우지동
5th row갈천동
ValueCountFrequency (%)
교동 3
 
3.0%
문곡리 2
 
2.0%
신이리 1
 
1.0%
후동리 1
 
1.0%
추곡리 1
 
1.0%
가정리 1
 
1.0%
한덕리 1
 
1.0%
자등리 1
 
1.0%
와수리 1
 
1.0%
광덕리 1
 
1.0%
Other values (87) 87
87.0%
2023-12-10T19:32:02.570477image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
리 92
30.6%
동 12
 
4.0%
천 9
 
3.0%
월 7
 
2.3%
덕 7
 
2.3%
곡 6
 
2.0%
수 6
 
2.0%
신 5
 
1.7%
평 5
 
1.7%
상 5
 
1.7%
Other values (89) 147
48.8%

Most occurring categories

ValueCountFrequency (%)
Other Letter 301
100.0%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
리 92
30.6%
동 12
 
4.0%
천 9
 
3.0%
월 7
 
2.3%
덕 7
 
2.3%
곡 6
 
2.0%
수 6
 
2.0%
신 5
 
1.7%
평 5
 
1.7%
상 5
 
1.7%
Other values (89) 147
48.8%

Most occurring scripts

ValueCountFrequency (%)
Hangul 301
100.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
리 92
30.6%
동 12
 
4.0%
천 9
 
3.0%
월 7
 
2.3%
덕 7
 
2.3%
곡 6
 
2.0%
수 6
 
2.0%
신 5
 
1.7%
평 5
 
1.7%
상 5
 
1.7%
Other values (89) 147
48.8%

Most occurring blocks

ValueCountFrequency (%)
Hangul 301
100.0%

Most frequent character per block

Hangul
ValueCountFrequency (%)
리 92
30.6%
동 12
 
4.0%
천 9
 
3.0%
월 7
 
2.3%
덕 7
 
2.3%
곡 6
 
2.0%
수 6
 
2.0%
신 5
 
1.7%
평 5
 
1.7%
상 5
 
1.7%
Other values (89) 147
48.8%

법정동코드
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct100
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean4.2564706 × 109
Minimum4.2110122 × 109
Maximum4.283031 × 109
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.0 KiB
2023-12-10T19:32:02.869423image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum4.2110122 × 109
5-th percentile4.211031 × 109
Q14.211035 × 109
median4.277032 × 109
Q34.281031 × 109
95-th percentile4.283031 × 109
Maximum4.283031 × 109
Range72018840
Interquartile range (IQR)69996004

Descriptive statistics

Standard deviation32056251
Coefficient of variation (CV)0.0075311811
Kurtosis-1.5697305
Mean4.2564706 × 109
Median Absolute Deviation (MAD)5999004
Skewness-0.63826852
Sum4.2564706 × 1011
Variance1.0276032 × 1015
MonotonicityNot monotonic
2023-12-10T19:32:03.326181image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
4223010600 1
 
1.0%
4277032021 1
 
1.0%
4211034022 1
 
1.0%
4211034021 1
 
1.0%
4211034026 1
 
1.0%
4211034023 1
 
1.0%
4211034027 1
 
1.0%
4211012200 1
 
1.0%
4278031021 1
 
1.0%
4278031022 1
 
1.0%
Other values (90) 90
90.0%
ValueCountFrequency (%)
4211012200 1
1.0%
4211031021 1
1.0%
4211031022 1
1.0%
4211031023 1
1.0%
4211031024 1
1.0%
4211031025 1
1.0%
4211031026 1
1.0%
4211031027 1
1.0%
4211031028 1
1.0%
4211031029 1
1.0%
ValueCountFrequency (%)
4283031040 1
1.0%
4283031039 1
1.0%
4283031038 1
1.0%
4283031037 1
1.0%
4283031036 1
1.0%
4283031035 1
1.0%
4283031034 1
1.0%
4283031033 1
1.0%
4283031032 1
1.0%
4283031031 1
1.0%

총인구수
Real number (ℝ)

HIGH CORRELATION 

Distinct15
Distinct (%)15.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean5615.94
Minimum1127
Maximum19718
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.0 KiB
2023-12-10T19:32:03.595162image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1127
5-th percentile1127
Q12502.25
median3503
Q35600
95-th percentile19718
Maximum19718
Range18591
Interquartile range (IQR)3097.75

Descriptive statistics

Standard deviation5655.3305
Coefficient of variation (CV)1.0070141
Kurtosis1.6326163
Mean5615.94
Median Absolute Deviation (MAD)1381
Skewness1.7522363
Sum561594
Variance31982764
MonotonicityNot monotonic
2023-12-10T19:32:03.823237image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=15)
ValueCountFrequency (%)
2629 20
20.0%
3875 13
13.0%
19718 10
10.0%
4091 10
10.0%
1953 7
 
7.0%
1127 7
 
7.0%
2122 6
 
6.0%
15445 5
 
5.0%
2004 5
 
5.0%
3131 5
 
5.0%
Other values (5) 12
12.0%
ValueCountFrequency (%)
1127 7
 
7.0%
1953 7
 
7.0%
2004 5
 
5.0%
2122 6
 
6.0%
2629 20
20.0%
3131 5
 
5.0%
3875 13
13.0%
4091 10
10.0%
4183 1
 
1.0%
5600 2
 
2.0%
ValueCountFrequency (%)
19718 10
10.0%
15445 5
 
5.0%
9255 2
 
2.0%
7860 4
 
4.0%
6008 3
 
3.0%
5600 2
 
2.0%
4183 1
 
1.0%
4091 10
10.0%
3875 13
13.0%
3131 5
 
5.0%

총가구수
Real number (ℝ)

HIGH CORRELATION 

Distinct15
Distinct (%)15.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2339.37
Minimum521
Maximum7455
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.0 KiB
2023-12-10T19:32:04.051257image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum521
5-th percentile521
Q11165.5
median1546
Q32263.25
95-th percentile7455
Maximum7455
Range6934
Interquartile range (IQR)1097.75

Descriptive statistics

Standard deviation2179.5367
Coefficient of variation (CV)0.93167678
Kurtosis1.1557129
Mean2339.37
Median Absolute Deviation (MAD)517
Skewness1.6418065
Sum233937
Variance4750380.3
MonotonicityNot monotonic
2023-12-10T19:32:04.290809image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=15)
ValueCountFrequency (%)
1211 20
20.0%
1610 13
13.0%
7455 10
10.0%
1546 10
10.0%
817 7
 
7.0%
521 7
 
7.0%
1025 6
 
6.0%
6732 5
 
5.0%
1029 5
 
5.0%
1553 5
 
5.0%
Other values (5) 12
12.0%
ValueCountFrequency (%)
521 7
 
7.0%
817 7
 
7.0%
1025 6
 
6.0%
1029 5
 
5.0%
1211 20
20.0%
1546 10
10.0%
1553 5
 
5.0%
1610 13
13.0%
2249 2
 
2.0%
2306 1
 
1.0%
ValueCountFrequency (%)
7455 10
10.0%
6732 5
 
5.0%
4330 2
 
2.0%
3311 4
 
4.0%
2661 3
 
3.0%
2306 1
 
1.0%
2249 2
 
2.0%
1610 13
13.0%
1553 5
 
5.0%
1546 10
10.0%

가구당인구수
Real number (ℝ)

HIGH CORRELATION 

Distinct15
Distinct (%)15.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2.3053
Minimum1.81
Maximum2.65
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.0 KiB
2023-12-10T19:32:04.864164image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1.81
5-th percentile1.95
Q12.16
median2.29
Q32.41
95-th percentile2.65
Maximum2.65
Range0.84
Interquartile range (IQR)0.25

Descriptive statistics

Standard deviation0.21968046
Coefficient of variation (CV)0.095293654
Kurtosis-0.91022868
Mean2.3053
Median Absolute Deviation (MAD)0.12
Skewness0.19151059
Sum230.53
Variance0.048259505
MonotonicityNot monotonic
2023-12-10T19:32:05.071664image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=15)
ValueCountFrequency (%)
2.17 20
20.0%
2.41 13
13.0%
2.64 10
10.0%
2.65 10
10.0%
2.39 7
 
7.0%
2.16 7
 
7.0%
2.07 6
 
6.0%
2.29 5
 
5.0%
1.95 5
 
5.0%
2.02 5
 
5.0%
Other values (5) 12
12.0%
ValueCountFrequency (%)
1.81 1
 
1.0%
1.95 5
 
5.0%
2.02 5
 
5.0%
2.07 6
 
6.0%
2.14 2
 
2.0%
2.16 7
 
7.0%
2.17 20
20.0%
2.26 3
 
3.0%
2.29 5
 
5.0%
2.37 4
 
4.0%
ValueCountFrequency (%)
2.65 10
10.0%
2.64 10
10.0%
2.49 2
 
2.0%
2.41 13
13.0%
2.39 7
 
7.0%
2.37 4
 
4.0%
2.29 5
 
5.0%
2.26 3
 
3.0%
2.17 20
20.0%
2.16 7
 
7.0%

평균소득금액
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct100
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2014.7409
Minimum1283.15
Maximum3711.9
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.0 KiB
2023-12-10T19:32:05.325582image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1283.15
5-th percentile1441.446
Q11755.67
median1933.165
Q32218.475
95-th percentile2885.7675
Maximum3711.9
Range2428.75
Interquartile range (IQR)462.805

Descriptive statistics

Standard deviation452.5714
Coefficient of variation (CV)0.22463007
Kurtosis2.5215042
Mean2014.7409
Median Absolute Deviation (MAD)240.265
Skewness1.3187509
Sum201474.09
Variance204820.87
MonotonicityNot monotonic
2023-12-10T19:32:05.601579image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
3415.86 1
 
1.0%
1544.59 1
 
1.0%
2160.14 1
 
1.0%
1815.28 1
 
1.0%
1813.49 1
 
1.0%
1923.91 1
 
1.0%
2195.57 1
 
1.0%
3094.31 1
 
1.0%
2164.91 1
 
1.0%
2300.62 1
 
1.0%
Other values (90) 90
90.0%
ValueCountFrequency (%)
1283.15 1
1.0%
1369.69 1
1.0%
1374.09 1
1.0%
1400.58 1
1.0%
1408.12 1
1.0%
1443.2 1
1.0%
1478.95 1
1.0%
1486.32 1
1.0%
1497.86 1
1.0%
1516.68 1
1.0%
ValueCountFrequency (%)
3711.9 1
1.0%
3435.07 1
1.0%
3415.86 1
1.0%
3094.31 1
1.0%
2968.94 1
1.0%
2881.39 1
1.0%
2800.18 1
1.0%
2720.65 1
1.0%
2642.36 1
1.0%
2557.67 1
1.0%

Interactions

2023-12-10T19:31:59.237901image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:31:53.245759image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:31:54.468414image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:31:55.613825image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:31:56.935173image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:31:58.181429image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:31:59.427282image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:31:53.610959image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:31:54.690718image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:31:55.789747image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:31:57.203326image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:31:58.338459image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:31:59.605026image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:31:53.821650image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:31:54.908637image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:31:56.048660image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:31:57.412269image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:31:58.503520image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:31:59.758763image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:31:53.983262image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:31:55.110738image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:31:56.302721image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:31:57.602011image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:31:58.664890image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:31:59.909666image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:31:54.148782image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:31:55.297257image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:31:56.556888image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:31:57.787520image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:31:58.807782image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:32:00.075474image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:31:54.310491image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:31:55.465180image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:31:56.720584image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:31:57.980550image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:31:59.001594image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-10T19:32:05.795310image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
행정동명행정동코드법정동명법정동코드총인구수총가구수가구당인구수평균소득금액
행정동명1.0001.0000.0001.0001.0001.0001.0000.843
행정동코드1.0001.0000.0001.0000.8120.7870.8920.622
법정동명0.0000.0001.0000.9160.0000.0000.0000.000
법정동코드1.0001.0000.9161.0000.8280.9680.8840.572
총인구수1.0000.8120.0000.8281.0000.9900.8640.506
총가구수1.0000.7870.0000.9680.9901.0000.8910.592
가구당인구수1.0000.8920.0000.8840.8640.8911.0000.872
평균소득금액0.8430.6220.0000.5720.5060.5920.8721.000
2023-12-10T19:32:05.999383image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
행정동코드법정동코드총인구수총가구수가구당인구수평균소득금액행정동명
행정동코드1.0000.989-0.326-0.235-0.245-0.2820.941
법정동코드0.9891.000-0.327-0.241-0.220-0.2900.941
총인구수-0.326-0.3271.0000.9670.5950.5890.956
총가구수-0.235-0.2410.9671.0000.5000.4850.961
가구당인구수-0.245-0.2200.5950.5001.0000.4890.972
평균소득금액-0.282-0.2900.5890.4850.4891.0000.500
행정동명0.9410.9410.9560.9610.9720.5001.000

Missing values

2023-12-10T19:32:00.288153image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-10T19:32:00.527123image/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

행정동명행정동코드법정동명법정동코드총인구수총가구수가구당인구수평균소득금액
0강원도 삼척시 교동4223053000교동42230106001544567322.293415.86
1강원도 삼척시 교동4223053000증산동42230108001544567322.292453.85
2강원도 삼척시 교동4223053000마달동42230110001544567322.292881.39
3강원도 삼척시 교동4223053000우지동42230109001544567322.292351.63
4강원도 삼척시 교동4223053000갈천동42230107001544567322.292968.94
5강원도 속초시 교동4221056000교동4221010600925543302.142557.67
6강원도 속초시 교동4221056000청학동4221010500925543302.142047.72
7강원도 양구군 동면4280032000원당리428003202319538172.391527.23
8강원도 양구군 동면4280032000팔랑리428003202619538172.391580.23
9강원도 양구군 동면4280032000지석리428003202219538172.391478.95
행정동명행정동코드법정동명법정동코드총인구수총가구수가구당인구수평균소득금액
90강원도 춘천시 서면4211035000현암리4211035021409115462.652800.18
91강원도 춘천시 서면4211035000월송리4211035026409115462.652208.44
92강원도 춘천시 서면4211035000금산리4211035022409115462.652720.65
93강원도 춘천시 서면4211035000당림리4211035029409115462.652166.6
94강원도 춘천시 서면4211035000안보리4211035030409115462.652465.0
95강원도 춘천시 서면4211035000신매리4211035023409115462.652642.36
96강원도 춘천시 서면4211035000덕두원리4211035028409115462.652447.96
97강원도 홍천군 남면4272036000월천리4272036026600826612.261848.54
98강원도 홍천군 남면4272036000유치리4272036025600826612.261923.44
99강원도 홍천군 남면4272036000명동리4272036027600826612.261767.97