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

행정동 코드 is highly overall correlated with 법정동 코드 and 1 other fieldsHigh correlation
법정동 코드 is highly overall correlated with 행정동 코드 and 1 other fieldsHigh correlation
총 인구수 is highly overall correlated with 총 가구수 and 2 other fieldsHigh correlation
총 가구수 is highly overall correlated with 총 인구수 and 2 other fieldsHigh correlation
가구당 인구 수 is highly overall correlated with 총 인구수 and 3 other fieldsHigh correlation
평균소득금액 is highly overall correlated with 가구당 인구 수High correlation
행정동 명 is highly overall correlated with 행정동 코드 and 4 other fieldsHigh correlation
법정동 코드 has unique valuesUnique
평균소득금액 has unique valuesUnique

Reproduction

Analysis started2023-12-10 10:32:07.718853
Analysis finished2023-12-10 10:32:15.391578
Duration7.67 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

행정동 명
Categorical

HIGH CORRELATION 

Distinct14
Distinct (%)14.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
강원도 양양군 서면
20 
강원도 양구군 남면
14 
강원도 인제군 남면
13 
강원도 춘천시 동면
9 
강원도 양구군 동면
7 
Other values (9)
37 

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 양구군 남면 14
14.0%
강원도 인제군 남면 13
13.0%
강원도 춘천시 동면 9
9.0%
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 (4) 9
9.0%

Length

2023-12-10T19:32:15.512599image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
강원도 100
33.3%
남면 45
15.0%
서면 22
 
7.3%
양구군 21
 
7.0%
양양군 20
 
6.7%
인제군 17
 
5.7%
춘천시 17
 
5.7%
동면 16
 
5.3%
영월군 11
 
3.7%
북면 9
 
3.0%
Other values (5) 22
 
7.3%

행정동 코드
Real number (ℝ)

HIGH CORRELATION 

Distinct14
Distinct (%)14.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean4.2643035 × 109
Minimum4.211031 × 109
Maximum4.283031 × 109
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.0 KiB
2023-12-10T19:32:16.142064image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum4.211031 × 109
5-th percentile4.211031 × 109
Q14.275033 × 109
median4.280031 × 109
Q34.281031 × 109
95-th percentile4.283031 × 109
Maximum4.283031 × 109
Range72000000
Interquartile range (IQR)5998000

Descriptive statistics

Standard deviation28410575
Coefficient of variation (CV)0.0066624186
Kurtosis-0.39500973
Mean4.2643035 × 109
Median Absolute Deviation (MAD)3000000
Skewness-1.2408945
Sum4.2643035 × 1011
Variance8.0716076 × 1014
MonotonicityNot monotonic
2023-12-10T19:32:16.385619image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=14)
ValueCountFrequency (%)
4283031000 20
20.0%
4280031000 14
14.0%
4281031000 13
13.0%
4211031000 9
9.0%
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 (4) 9
9.0%
ValueCountFrequency (%)
4211031000 9
9.0%
4211034000 7
7.0%
4211052000 1
 
1.0%
4221056000 2
 
2.0%
4223053000 5
 
5.0%
4275033000 5
 
5.0%
4275034000 6
6.0%
4277032000 5
 
5.0%
4278031000 2
 
2.0%
4280031000 14
14.0%
ValueCountFrequency (%)
4283031000 20
20.0%
4281032000 4
 
4.0%
4281031000 13
13.0%
4280032000 7
 
7.0%
4280031000 14
14.0%
4278031000 2
 
2.0%
4277032000 5
 
5.0%
4275034000 6
 
6.0%
4275033000 5
 
5.0%
4223053000 5
 
5.0%

법정동 명
Text

Distinct97
Distinct (%)97.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
2023-12-10T19:32:16.924119image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length4
Median length3
Mean length2.96
Min length2

Characters and Unicode

Total characters296
Distinct characters104
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 row갈천동
2nd row교동
3rd row우지동
4th row증산동
5th row마달동
ValueCountFrequency (%)
교동 3
 
3.0%
문곡리 2
 
2.0%
한계리 1
 
1.0%
원통리 1
 
1.0%
부평리 1
 
1.0%
갑둔리 1
 
1.0%
관대리 1
 
1.0%
정자리 1
 
1.0%
신풍리 1
 
1.0%
신월리 1
 
1.0%
Other values (87) 87
87.0%
2023-12-10T19:32:17.735050image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
리 92
31.1%
동 10
 
3.4%
천 8
 
2.7%
수 6
 
2.0%
덕 6
 
2.0%
평 5
 
1.7%
곡 5
 
1.7%
교 4
 
1.4%
신 4
 
1.4%
내 4
 
1.4%
Other values (94) 152
51.4%

Most occurring categories

ValueCountFrequency (%)
Other Letter 296
100.0%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
리 92
31.1%
동 10
 
3.4%
천 8
 
2.7%
수 6
 
2.0%
덕 6
 
2.0%
평 5
 
1.7%
곡 5
 
1.7%
교 4
 
1.4%
신 4
 
1.4%
내 4
 
1.4%
Other values (94) 152
51.4%

Most occurring scripts

ValueCountFrequency (%)
Hangul 296
100.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
리 92
31.1%
동 10
 
3.4%
천 8
 
2.7%
수 6
 
2.0%
덕 6
 
2.0%
평 5
 
1.7%
곡 5
 
1.7%
교 4
 
1.4%
신 4
 
1.4%
내 4
 
1.4%
Other values (94) 152
51.4%

Most occurring blocks

ValueCountFrequency (%)
Hangul 296
100.0%

Most frequent character per block

Hangul
ValueCountFrequency (%)
리 92
31.1%
동 10
 
3.4%
천 8
 
2.7%
수 6
 
2.0%
덕 6
 
2.0%
평 5
 
1.7%
곡 5
 
1.7%
교 4
 
1.4%
신 4
 
1.4%
내 4
 
1.4%
Other values (94) 152
51.4%

법정동 코드
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct100
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean4.2643001 × 109
Minimum4.2110122 × 109
Maximum4.283031 × 109
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.0 KiB
2023-12-10T19:32:18.055853image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum4.2110122 × 109
5-th percentile4.211031 × 109
Q14.275033 × 109
median4.280031 × 109
Q34.281031 × 109
95-th percentile4.283031 × 109
Maximum4.283031 × 109
Range72018840
Interquartile range (IQR)5998010.5

Descriptive statistics

Standard deviation28415826
Coefficient of variation (CV)0.0066636554
Kurtosis-0.39576651
Mean4.2643001 × 109
Median Absolute Deviation (MAD)2999997
Skewness-1.2407048
Sum4.2643001 × 1011
Variance8.0745919 × 1014
MonotonicityNot monotonic
2023-12-10T19:32:18.377142image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
4223010700 1
 
1.0%
4281031031 1
 
1.0%
4281032024 1
 
1.0%
4281032021 1
 
1.0%
4281032022 1
 
1.0%
4281031021 1
 
1.0%
4281031024 1
 
1.0%
4281031025 1
 
1.0%
4281031028 1
 
1.0%
4281031026 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%
4211031026 1
1.0%
4211031027 1
1.0%
4211031028 1
1.0%
4211031029 1
1.0%
4211031030 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%

총 인구수
Real number (ℝ)

HIGH CORRELATION 

Distinct14
Distinct (%)14.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean5412.4
Minimum1109
Maximum19844
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.0 KiB
2023-12-10T19:32:18.648155image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1109
5-th percentile1109
Q12277
median3325
Q34192
95-th percentile19844
Maximum19844
Range18735
Interquartile range (IQR)1915

Descriptive statistics

Standard deviation5476.0615
Coefficient of variation (CV)1.0117622
Kurtosis2.1468691
Mean5412.4
Median Absolute Deviation (MAD)867
Skewness1.8851898
Sum541240
Variance29987249
MonotonicityNot monotonic
2023-12-10T19:32:18.852647image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=14)
ValueCountFrequency (%)
2957 20
20.0%
3417 14
14.0%
4192 13
13.0%
19844 9
9.0%
2191 7
 
7.0%
1109 7
 
7.0%
2277 6
 
6.0%
14973 5
 
5.0%
2184 5
 
5.0%
3325 5
 
5.0%
Other values (4) 9
9.0%
ValueCountFrequency (%)
1109 7
 
7.0%
2057 2
 
2.0%
2184 5
 
5.0%
2191 7
 
7.0%
2277 6
 
6.0%
2957 20
20.0%
3325 5
 
5.0%
3417 14
14.0%
3748 1
 
1.0%
4192 13
13.0%
ValueCountFrequency (%)
19844 9
9.0%
14973 5
 
5.0%
10012 2
 
2.0%
8528 4
 
4.0%
4192 13
13.0%
3748 1
 
1.0%
3417 14
14.0%
3325 5
 
5.0%
2957 20
20.0%
2277 6
 
6.0%

총 가구수
Real number (ℝ)

HIGH CORRELATION 

Distinct14
Distinct (%)14.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2499.56
Minimum651
Maximum7653
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.0 KiB
2023-12-10T19:32:19.117113image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum651
5-th percentile651
Q11336
median1808
Q32073
95-th percentile7653
Maximum7653
Range7002
Interquartile range (IQR)737

Descriptive statistics

Standard deviation2031.249
Coefficient of variation (CV)0.81264263
Kurtosis1.56879
Mean2499.56
Median Absolute Deviation (MAD)286
Skewness1.7166878
Sum249956
Variance4125972.6
MonotonicityNot monotonic
2023-12-10T19:32:19.400129image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=14)
ValueCountFrequency (%)
1522 20
20.0%
1829 14
14.0%
2073 13
13.0%
7653 9
9.0%
1283 7
 
7.0%
651 7
 
7.0%
1336 6
 
6.0%
6064 5
 
5.0%
1256 5
 
5.0%
1808 5
 
5.0%
Other values (4) 9
9.0%
ValueCountFrequency (%)
651 7
 
7.0%
1157 2
 
2.0%
1256 5
 
5.0%
1283 7
 
7.0%
1336 6
 
6.0%
1522 20
20.0%
1808 5
 
5.0%
1829 14
14.0%
2073 13
13.0%
2266 1
 
1.0%
ValueCountFrequency (%)
7653 9
9.0%
6064 5
 
5.0%
4845 2
 
2.0%
4155 4
 
4.0%
2266 1
 
1.0%
2073 13
13.0%
1829 14
14.0%
1808 5
 
5.0%
1522 20
20.0%
1336 6
 
6.0%

가구당 인구 수
Real number (ℝ)

HIGH CORRELATION 

Distinct13
Distinct (%)13.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1.9642
Minimum1.65
Maximum2.59
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.0 KiB
2023-12-10T19:32:19.694419image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1.65
5-th percentile1.7
Q11.74
median1.94
Q32.02
95-th percentile2.59
Maximum2.59
Range0.94
Interquartile range (IQR)0.28

Descriptive statistics

Standard deviation0.26374988
Coefficient of variation (CV)0.13427853
Kurtosis0.96041503
Mean1.9642
Median Absolute Deviation (MAD)0.1
Skewness1.3391119
Sum196.42
Variance0.069564
MonotonicityNot monotonic
2023-12-10T19:32:19.906250image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=13)
ValueCountFrequency (%)
1.94 20
20.0%
1.87 14
14.0%
1.7 13
13.0%
2.02 13
13.0%
2.59 9
9.0%
1.71 7
 
7.0%
2.47 5
 
5.0%
1.74 5
 
5.0%
1.84 5
 
5.0%
2.05 4
 
4.0%
Other values (3) 5
 
5.0%
ValueCountFrequency (%)
1.65 1
 
1.0%
1.7 13
13.0%
1.71 7
 
7.0%
1.74 5
 
5.0%
1.78 2
 
2.0%
1.84 5
 
5.0%
1.87 14
14.0%
1.94 20
20.0%
2.02 13
13.0%
2.05 4
 
4.0%
ValueCountFrequency (%)
2.59 9
9.0%
2.47 5
 
5.0%
2.07 2
 
2.0%
2.05 4
 
4.0%
2.02 13
13.0%
1.94 20
20.0%
1.87 14
14.0%
1.84 5
 
5.0%
1.78 2
 
2.0%
1.74 5
 
5.0%

평균소득금액
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct100
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2110.3806
Minimum1276.56
Maximum5671.34
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.0 KiB
2023-12-10T19:32:20.130493image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1276.56
5-th percentile1499.5585
Q11699.88
median1964.295
Q32245.8175
95-th percentile3165.089
Maximum5671.34
Range4394.78
Interquartile range (IQR)545.9375

Descriptive statistics

Standard deviation715.13651
Coefficient of variation (CV)0.33886613
Kurtosis10.229505
Mean2110.3806
Median Absolute Deviation (MAD)268.67
Skewness2.8536741
Sum211038.06
Variance511420.23
MonotonicityNot monotonic
2023-12-10T19:32:20.406083image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
3141.88 1
 
1.0%
1932.86 1
 
1.0%
2356.27 1
 
1.0%
2572.88 1
 
1.0%
2024.03 1
 
1.0%
2287.75 1
 
1.0%
1960.07 1
 
1.0%
2398.5 1
 
1.0%
2151.76 1
 
1.0%
2016.41 1
 
1.0%
Other values (90) 90
90.0%
ValueCountFrequency (%)
1276.56 1
1.0%
1364.01 1
1.0%
1418.21 1
1.0%
1432.99 1
1.0%
1485.85 1
1.0%
1500.28 1
1.0%
1507.6 1
1.0%
1533.29 1
1.0%
1541.42 1
1.0%
1546.94 1
1.0%
ValueCountFrequency (%)
5671.34 1
1.0%
5307.82 1
1.0%
4586.25 1
1.0%
3879.85 1
1.0%
3606.06 1
1.0%
3141.88 1
1.0%
3122.56 1
1.0%
3027.1 1
1.0%
2866.55 1
1.0%
2789.37 1
1.0%

Interactions

2023-12-10T19:32:14.077652image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:32:08.380483image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:32:09.452766image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:32:10.628287image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:32:11.878090image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:32:13.022798image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:32:14.258439image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:32:08.564743image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:32:09.642594image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:32:10.844217image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:32:12.069540image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:32:13.224294image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:32:14.430219image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:32:08.732586image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:32:09.829571image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:32:11.053161image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:32:12.305070image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:32:13.420529image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:32:14.587263image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:32:08.916201image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:32:10.023043image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:32:11.338361image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:32:12.508577image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:32:13.604340image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:32:14.738129image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:32:09.100789image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:32:10.239030image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:32:11.560191image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:32:12.692890image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:32:13.780245image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:32:14.871276image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:32:09.274920image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:32:10.440090image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:32:11.727054image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:32:12.871742image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:32:13.916833image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-10T19:32:20.572984image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
행정동 명행정동 코드법정동 명법정동 코드총 인구수총 가구수가구당 인구 수평균소득금액
행정동 명1.0001.0000.0001.0001.0001.0001.0000.764
행정동 코드1.0001.0000.0001.0000.6670.7050.8170.613
법정동 명0.0000.0001.0000.8820.0000.0000.0000.000
법정동 코드1.0001.0000.8821.0000.9390.9550.8450.838
총 인구수1.0000.6670.0000.9391.0000.9860.9150.605
총 가구수1.0000.7050.0000.9550.9861.0000.9500.651
가구당 인구 수1.0000.8170.0000.8450.9150.9501.0000.624
평균소득금액0.7640.6130.0000.8380.6050.6510.6241.000
2023-12-10T19:32:20.817104image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
행정동 코드법정동 코드총 인구수총 가구수가구당 인구 수평균소득금액행정동 명
행정동 코드1.0000.991-0.119-0.1270.109-0.0040.946
법정동 코드0.9911.000-0.120-0.1310.119-0.0200.946
총 인구수-0.119-0.1201.0000.9990.8630.4360.957
총 가구수-0.127-0.1310.9991.0000.8520.4410.957
가구당 인구 수0.1090.1190.8630.8521.0000.5270.962
평균소득금액-0.004-0.0200.4360.4410.5271.0000.456
행정동 명0.9460.9460.9570.9570.9620.4561.000

Missing values

2023-12-10T19:32:15.064238image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-10T19:32:15.297176image/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

행정동 명행정동 코드법정동 명법정동 코드총 인구수총 가구수가구당 인구 수평균소득금액
0강원도 삼척시 교동4223053000갈천동42230107001497360642.473141.88
1강원도 삼척시 교동4223053000교동42230106001497360642.474586.25
2강원도 삼척시 교동4223053000우지동42230109001497360642.472406.05
3강원도 삼척시 교동4223053000증산동42230108001497360642.472515.18
4강원도 삼척시 교동4223053000마달동42230110001497360642.473879.85
5강원도 속초시 교동4221056000교동42210106001001248452.073606.06
6강원도 속초시 교동4221056000청학동42210105001001248452.072247.31
7강원도 양구군 남면4280031000창리4280031028341718291.871741.89
8강원도 양구군 남면4280031000용하리4280031024341718291.871987.76
9강원도 양구군 남면4280031000황강리4280031027341718291.871706.14
행정동 명행정동 코드법정동 명법정동 코드총 인구수총 가구수가구당 인구 수평균소득금액
90강원도 춘천시 남면4211034000가정리421103402311096511.71934.7
91강원도 춘천시 동면4211031000상걸리42110310301984476532.591865.96
92강원도 춘천시 동면4211031000만천리42110310221984476532.595307.82
93강원도 춘천시 동면4211031000장학리42110310231984476532.595671.34
94강원도 춘천시 동면4211031000지내리42110310211984476532.592783.35
95강원도 춘천시 동면4211031000품걸리42110310271984476532.591981.33
96강원도 춘천시 동면4211031000평촌리42110310291984476532.591798.95
97강원도 춘천시 동면4211031000품안리42110310261984476532.591549.0
98강원도 춘천시 동면4211031000감정리42110310241984476532.592314.11
99강원도 춘천시 동면4211031000신이리42110310281984476532.592245.32