Overview

Dataset statistics

Number of variables15
Number of observations10000
Missing cells49982
Missing cells (%)33.3%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory1.3 MiB
Average record size in memory139.0 B

Variable types

Numeric5
Categorical3
Text3
Unsupported4

Dataset

Description2013, 2014년 1월 1일 기준 경상북도 고령군 운수면 개별공시지가
Author경상북도 고령군
URLhttps://www.data.go.kr/data/15051163/fileData.do

Alerts

법정동 has constant value ""Constant
No is highly overall correlated with 일련번호 and 1 other fieldsHigh correlation
일련번호 is highly overall correlated with No and 2 other fieldsHigh correlation
리 is highly overall correlated with No and 1 other fieldsHigh correlation
행정동 is highly overall correlated with 일련번호High correlation
행정동 is highly imbalanced (88.9%)Imbalance
Unnamed: 10 has 10000 (100.0%) missing valuesMissing
Unnamed: 11 has 10000 (100.0%) missing valuesMissing
Unnamed: 12 has 10000 (100.0%) missing valuesMissing
Unnamed: 13 has 9991 (99.9%) missing valuesMissing
Unnamed: 14 has 9991 (99.9%) missing valuesMissing
No has unique valuesUnique
Unnamed: 10 is an unsupported type, check if it needs cleaning or further analysisUnsupported
Unnamed: 11 is an unsupported type, check if it needs cleaning or further analysisUnsupported
Unnamed: 12 is an unsupported type, check if it needs cleaning or further analysisUnsupported
Unnamed: 13 is an unsupported type, check if it needs cleaning or further analysisUnsupported
부번 has 5253 (52.5%) zerosZeros

Reproduction

Analysis started2023-12-12 03:51:15.272897
Analysis finished2023-12-12 03:51:21.399542
Duration6.13 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

No
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct10000
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean5610.5473
Minimum1
Maximum11216
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2023-12-12T12:51:21.521777image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile544.95
Q12807.75
median5616.5
Q38422.75
95-th percentile10661.05
Maximum11216
Range11215
Interquartile range (IQR)5615

Descriptive statistics

Standard deviation3239.5559
Coefficient of variation (CV)0.57740462
Kurtosis-1.2013757
Mean5610.5473
Median Absolute Deviation (MAD)2808.5
Skewness-0.0009921215
Sum56105473
Variance10494723
MonotonicityNot monotonic
2023-12-12T12:51:21.748139image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
5379 1
 
< 0.1%
9704 1
 
< 0.1%
4364 1
 
< 0.1%
5069 1
 
< 0.1%
6757 1
 
< 0.1%
8153 1
 
< 0.1%
28 1
 
< 0.1%
5765 1
 
< 0.1%
2420 1
 
< 0.1%
3815 1
 
< 0.1%
Other values (9990) 9990
99.9%
ValueCountFrequency (%)
1 1
< 0.1%
2 1
< 0.1%
3 1
< 0.1%
4 1
< 0.1%
6 1
< 0.1%
7 1
< 0.1%
8 1
< 0.1%
9 1
< 0.1%
10 1
< 0.1%
12 1
< 0.1%
ValueCountFrequency (%)
11216 1
< 0.1%
11215 1
< 0.1%
11214 1
< 0.1%
11212 1
< 0.1%
11211 1
< 0.1%
11210 1
< 0.1%
11209 1
< 0.1%
11208 1
< 0.1%
11206 1
< 0.1%
11205 1
< 0.1%

일련번호
Real number (ℝ)

HIGH CORRELATION 

Distinct9844
Distinct (%)98.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean44028.753
Minimum23257
Maximum999999
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2023-12-12T12:51:21.971206image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum23257
5-th percentile23800.95
Q126063.75
median28872.5
Q331684.25
95-th percentile33915.05
Maximum999999
Range976742
Interquartile range (IQR)5620.5

Descriptive statistics

Standard deviation120781.75
Coefficient of variation (CV)2.7432471
Kurtosis58.655497
Mean44028.753
Median Absolute Deviation (MAD)2811
Skewness7.7845606
Sum4.4028753 × 108
Variance1.4588231 × 1010
MonotonicityNot monotonic
2023-12-12T12:51:22.201772image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
999999 157
 
1.6%
28554 1
 
< 0.1%
23284 1
 
< 0.1%
32480 1
 
< 0.1%
28544 1
 
< 0.1%
27548 1
 
< 0.1%
28247 1
 
< 0.1%
29908 1
 
< 0.1%
31288 1
 
< 0.1%
28936 1
 
< 0.1%
Other values (9834) 9834
98.3%
ValueCountFrequency (%)
23257 1
< 0.1%
23258 1
< 0.1%
23259 1
< 0.1%
23260 1
< 0.1%
23262 1
< 0.1%
23263 1
< 0.1%
23264 1
< 0.1%
23265 1
< 0.1%
23266 1
< 0.1%
23268 1
< 0.1%
ValueCountFrequency (%)
999999 157
1.6%
34298 1
 
< 0.1%
34297 1
 
< 0.1%
34296 1
 
< 0.1%
34294 1
 
< 0.1%
34293 1
 
< 0.1%
34292 1
 
< 0.1%
34291 1
 
< 0.1%
34290 1
 
< 0.1%
34288 1
 
< 0.1%

법정동
Categorical

CONSTANT 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
320
10000 

Length

Max length3
Median length3
Mean length3
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row320
2nd row320
3rd row320
4th row320
5th row320

Common Values

ValueCountFrequency (%)
320 10000
100.0%

Length

2023-12-12T12:51:22.411665image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T12:51:22.556180image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
320 10000
100.0%

행정동
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
0
9852 
320
 
148

Length

Max length3
Median length1
Mean length1.0296
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
0 9852
98.5%
320 148
 
1.5%

Length

2023-12-12T12:51:22.702456image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T12:51:22.857813image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 9852
98.5%
320 148
 
1.5%

리
Real number (ℝ)

HIGH CORRELATION 

Distinct9
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean33.7693
Minimum30
Maximum38
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2023-12-12T12:51:22.999345image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum30
5-th percentile30
Q131
median33
Q336
95-th percentile38
Maximum38
Range8
Interquartile range (IQR)5

Descriptive statistics

Standard deviation2.7870512
Coefficient of variation (CV)0.082532098
Kurtosis-1.4462968
Mean33.7693
Median Absolute Deviation (MAD)2
Skewness0.14882088
Sum337693
Variance7.7676543
MonotonicityNot monotonic
2023-12-12T12:51:23.149913image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=9)
ValueCountFrequency (%)
31 1637
16.4%
32 1399
14.0%
30 1347
13.5%
38 1266
12.7%
36 1178
11.8%
37 1088
10.9%
35 833
8.3%
33 727
7.3%
34 525
 
5.2%
ValueCountFrequency (%)
30 1347
13.5%
31 1637
16.4%
32 1399
14.0%
33 727
7.3%
34 525
 
5.2%
35 833
8.3%
36 1178
11.8%
37 1088
10.9%
38 1266
12.7%
ValueCountFrequency (%)
38 1266
12.7%
37 1088
10.9%
36 1178
11.8%
35 833
8.3%
34 525
 
5.2%
33 727
7.3%
32 1399
14.0%
31 1637
16.4%
30 1347
13.5%

구분
Categorical

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
1
8703 
2
1297 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
1 8703
87.0%
2 1297
 
13.0%

Length

2023-12-12T12:51:23.328049image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T12:51:23.451948image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
1 8703
87.0%
2 1297
 
13.0%

본번
Real number (ℝ)

Distinct1205
Distinct (%)12.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean402.3267
Minimum1
Maximum1272
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2023-12-12T12:51:23.561949image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile21
Q1109.75
median346
Q3606
95-th percentile1060
Maximum1272
Range1271
Interquartile range (IQR)496.25

Descriptive statistics

Standard deviation322.03509
Coefficient of variation (CV)0.80043181
Kurtosis-0.4276388
Mean402.3267
Median Absolute Deviation (MAD)242
Skewness0.71247212
Sum4023267
Variance103706.6
MonotonicityNot monotonic
2023-12-12T12:51:23.706051image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
718 73
 
0.7%
43 62
 
0.6%
106 51
 
0.5%
47 51
 
0.5%
66 48
 
0.5%
65 45
 
0.4%
62 43
 
0.4%
11 40
 
0.4%
64 40
 
0.4%
69 39
 
0.4%
Other values (1195) 9508
95.1%
ValueCountFrequency (%)
1 32
0.3%
2 17
0.2%
3 16
0.2%
4 22
0.2%
5 21
0.2%
6 15
0.1%
7 28
0.3%
8 18
0.2%
9 26
0.3%
10 24
0.2%
ValueCountFrequency (%)
1272 11
0.1%
1265 1
 
< 0.1%
1264 1
 
< 0.1%
1263 1
 
< 0.1%
1262 1
 
< 0.1%
1261 1
 
< 0.1%
1260 1
 
< 0.1%
1259 1
 
< 0.1%
1257 1
 
< 0.1%
1256 1
 
< 0.1%

부번
Real number (ℝ)

ZEROS 

Distinct128
Distinct (%)1.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean3.4072
Minimum0
Maximum228
Zeros5253
Zeros (%)52.5%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2023-12-12T12:51:23.874593image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q32
95-th percentile15
Maximum228
Range228
Interquartile range (IQR)2

Descriptive statistics

Standard deviation12.00634
Coefficient of variation (CV)3.5238143
Kurtosis105.38001
Mean3.4072
Median Absolute Deviation (MAD)0
Skewness9.0343217
Sum34072
Variance144.1522
MonotonicityNot monotonic
2023-12-12T12:51:24.489640image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 5253
52.5%
1 1663
 
16.6%
2 789
 
7.9%
3 499
 
5.0%
4 293
 
2.9%
5 213
 
2.1%
6 155
 
1.6%
7 116
 
1.2%
8 104
 
1.0%
9 91
 
0.9%
Other values (118) 824
 
8.2%
ValueCountFrequency (%)
0 5253
52.5%
1 1663
 
16.6%
2 789
 
7.9%
3 499
 
5.0%
4 293
 
2.9%
5 213
 
2.1%
6 155
 
1.6%
7 116
 
1.2%
8 104
 
1.0%
9 91
 
0.9%
ValueCountFrequency (%)
228 1
< 0.1%
226 1
< 0.1%
206 1
< 0.1%
190 1
< 0.1%
166 1
< 0.1%
164 1
< 0.1%
163 1
< 0.1%
158 1
< 0.1%
155 1
< 0.1%
154 2
< 0.1%

결정지가
Text

Distinct1081
Distinct (%)10.8%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2023-12-12T12:51:24.998586image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length7
Median length6
Mean length5.3463
Min length3

Characters and Unicode

Total characters53463
Distinct characters11
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique343 ?
Unique (%)3.4%

Sample

1st row13,600
2nd row19,700
3rd row11,500
4th row9,710
5th row21,300
ValueCountFrequency (%)
13,500 222
 
2.2%
11,500 200
 
2.0%
14,700 192
 
1.9%
13,700 183
 
1.8%
12,800 178
 
1.8%
13,000 177
 
1.8%
14,500 140
 
1.4%
12,500 139
 
1.4%
19,700 139
 
1.4%
13,300 138
 
1.4%
Other values (1071) 8292
82.9%
2023-12-12T12:51:25.795321image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 17271
32.3%
, 8665
16.2%
1 7263
13.6%
2 3163
 
5.9%
3 3147
 
5.9%
5 2783
 
5.2%
4 2535
 
4.7%
7 2356
 
4.4%
9 2313
 
4.3%
6 2109
 
3.9%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 44798
83.8%
Other Punctuation 8665
 
16.2%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 17271
38.6%
1 7263
16.2%
2 3163
 
7.1%
3 3147
 
7.0%
5 2783
 
6.2%
4 2535
 
5.7%
7 2356
 
5.3%
9 2313
 
5.2%
6 2109
 
4.7%
8 1858
 
4.1%
Other Punctuation
ValueCountFrequency (%)
, 8665
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 53463
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 17271
32.3%
, 8665
16.2%
1 7263
13.6%
2 3163
 
5.9%
3 3147
 
5.9%
5 2783
 
5.2%
4 2535
 
4.7%
7 2356
 
4.4%
9 2313
 
4.3%
6 2109
 
3.9%

Most occurring blocks

ValueCountFrequency (%)
ASCII 53463
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 17271
32.3%
, 8665
16.2%
1 7263
13.6%
2 3163
 
5.9%
3 3147
 
5.9%
5 2783
 
5.2%
4 2535
 
4.7%
7 2356
 
4.4%
9 2313
 
4.3%
6 2109
 
3.9%

전년지가
Text

Distinct1155
Distinct (%)11.6%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2023-12-12T12:51:26.289383image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length7
Median length6
Mean length5.3128
Min length1

Characters and Unicode

Total characters53128
Distinct characters11
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique372 ?
Unique (%)3.7%

Sample

1st row13,200
2nd row17,900
3rd row11,000
4th row12,000
5th row20,000
ValueCountFrequency (%)
13,000 222
 
2.2%
13,500 188
 
1.9%
13,200 173
 
1.7%
12,500 168
 
1.7%
14,200 152
 
1.5%
11,000 147
 
1.5%
11,400 146
 
1.5%
12,100 145
 
1.5%
11,500 136
 
1.4%
19,500 135
 
1.4%
Other values (1145) 8388
83.9%
2023-12-12T12:51:26.987140image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 17336
32.6%
, 8653
16.3%
1 7221
13.6%
2 3292
 
6.2%
3 2983
 
5.6%
5 2831
 
5.3%
4 2818
 
5.3%
8 2121
 
4.0%
9 2068
 
3.9%
6 2001
 
3.8%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 44475
83.7%
Other Punctuation 8653
 
16.3%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 17336
39.0%
1 7221
16.2%
2 3292
 
7.4%
3 2983
 
6.7%
5 2831
 
6.4%
4 2818
 
6.3%
8 2121
 
4.8%
9 2068
 
4.6%
6 2001
 
4.5%
7 1804
 
4.1%
Other Punctuation
ValueCountFrequency (%)
, 8653
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 53128
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 17336
32.6%
, 8653
16.3%
1 7221
13.6%
2 3292
 
6.2%
3 2983
 
5.6%
5 2831
 
5.3%
4 2818
 
5.3%
8 2121
 
4.0%
9 2068
 
3.9%
6 2001
 
3.8%

Most occurring blocks

ValueCountFrequency (%)
ASCII 53128
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 17336
32.6%
, 8653
16.3%
1 7221
13.6%
2 3292
 
6.2%
3 2983
 
5.6%
5 2831
 
5.3%
4 2818
 
5.3%
8 2121
 
4.0%
9 2068
 
3.9%
6 2001
 
3.8%

Unnamed: 10
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing10000
Missing (%)100.0%
Memory size166.0 KiB

Unnamed: 11
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing10000
Missing (%)100.0%
Memory size166.0 KiB

Unnamed: 12
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing10000
Missing (%)100.0%
Memory size166.0 KiB

Unnamed: 13
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing9991
Missing (%)99.9%
Memory size156.2 KiB

Unnamed: 14
Text

MISSING 

Distinct9
Distinct (%)100.0%
Missing9991
Missing (%)99.9%
Memory size156.2 KiB
2023-12-12T12:51:27.318043image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length3
Median length3
Mean length2.8888889
Min length2

Characters and Unicode

Total characters26
Distinct characters15
Distinct categories2 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique9 ?
Unique (%)100.0%

Sample

1st row운산리
2nd row신간리
3rd row봉평리
4th row리 명
5th row대평리
ValueCountFrequency (%)
운산리 1
10.0%
신간리 1
10.0%
봉평리 1
10.0%
리 1
10.0%
명 1
10.0%
대평리 1
10.0%
월산리 1
10.0%
화암리 1
10.0%
팔산리 1
10.0%
유리 1
10.0%
2023-12-12T12:51:27.727246image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
리 9
34.6%
산 3
 
11.5%
평 2
 
7.7%
운 1
 
3.8%
신 1
 
3.8%
간 1
 
3.8%
봉 1
 
3.8%
1
 
3.8%
명 1
 
3.8%
대 1
 
3.8%
Other values (5) 5
19.2%

Most occurring categories

ValueCountFrequency (%)
Other Letter 25
96.2%
Space Separator 1
 
3.8%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
리 9
36.0%
산 3
 
12.0%
평 2
 
8.0%
운 1
 
4.0%
신 1
 
4.0%
간 1
 
4.0%
봉 1
 
4.0%
명 1
 
4.0%
대 1
 
4.0%
월 1
 
4.0%
Other values (4) 4
16.0%
Space Separator
ValueCountFrequency (%)
1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 25
96.2%
Common 1
 
3.8%

Most frequent character per script

Hangul
ValueCountFrequency (%)
리 9
36.0%
산 3
 
12.0%
평 2
 
8.0%
운 1
 
4.0%
신 1
 
4.0%
간 1
 
4.0%
봉 1
 
4.0%
명 1
 
4.0%
대 1
 
4.0%
월 1
 
4.0%
Other values (4) 4
16.0%
Common
ValueCountFrequency (%)
1
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 25
96.2%
ASCII 1
 
3.8%

Most frequent character per block

Hangul
ValueCountFrequency (%)
리 9
36.0%
산 3
 
12.0%
평 2
 
8.0%
운 1
 
4.0%
신 1
 
4.0%
간 1
 
4.0%
봉 1
 
4.0%
명 1
 
4.0%
대 1
 
4.0%
월 1
 
4.0%
Other values (4) 4
16.0%
ASCII
ValueCountFrequency (%)
1
100.0%

Interactions

2023-12-12T12:51:19.970124image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T12:51:16.818253image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T12:51:17.545158image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T12:51:18.354661image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T12:51:19.168895image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T12:51:20.127969image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T12:51:16.951442image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T12:51:17.715927image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T12:51:18.527529image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T12:51:19.333220image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T12:51:20.286001image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T12:51:17.074375image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T12:51:17.848953image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T12:51:18.685879image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T12:51:19.496222image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T12:51:20.444144image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T12:51:17.249932image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T12:51:18.019911image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T12:51:18.869667image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T12:51:19.656297image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T12:51:20.603419image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T12:51:17.413337image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T12:51:18.192244image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T12:51:19.020158image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T12:51:19.811713image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-12T12:51:27.878847image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
No일련번호행정동리구분본번부번Unnamed: 14
No1.0000.0000.0000.9390.4000.6570.256NaN
일련번호0.0001.0000.8450.0000.0000.0000.000NaN
행정동0.0000.8451.0000.0000.0190.0040.000NaN
리0.9390.0000.0001.0000.1970.4350.206NaN
구분0.4000.0000.0190.1971.0000.5890.078NaN
본번0.6570.0000.0040.4350.5891.0000.343NaN
부번0.2560.0000.0000.2060.0780.3431.000NaN
Unnamed: 14NaNNaNNaNNaNNaNNaNNaN1.000
2023-12-12T12:51:28.053039image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
구분행정동
구분1.0000.012
행정동0.0121.000
2023-12-12T12:51:28.162216image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
No일련번호리본번부번행정동구분
No1.0000.9680.992-0.1000.0960.0000.307
일련번호0.9681.0000.960-0.0980.0850.6410.000
리0.9920.9601.000-0.1460.0950.0000.196
본번-0.100-0.098-0.1461.000-0.0320.0030.455
부번0.0960.0850.095-0.0321.0000.0000.059
행정동0.0000.6410.0000.0030.0001.0000.012
구분0.3070.0000.1960.4550.0590.0121.000

Missing values

2023-12-12T12:51:20.787220image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-12T12:51:21.099005image/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.
2023-12-12T12:51:21.320200image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
The correlation heatmap measures nullity correlation: how strongly the presence or absence of one variable affects the presence of another.

Sample

No일련번호법정동행정동리구분본번부번결정지가전년지가Unnamed: 10Unnamed: 11Unnamed: 12Unnamed: 13Unnamed: 14
53785379285543200331416013,60013,200<NA><NA><NA>NaN<NA>
26112612258213200311930119,70017,900<NA><NA><NA>NaN<NA>
20712072252913200311471011,50011,000<NA><NA><NA>NaN<NA>
3613361426809320032124649,71012,000<NA><NA><NA>NaN<NA>
89518952320723200371167321,30020,000<NA><NA><NA>NaN<NA>
494949502812932003313005,8309,070<NA><NA><NA>NaN<NA>
38873888270803200321415910,6008,970<NA><NA><NA>NaN<NA>
1872187325096320031132319,6709,270<NA><NA><NA>NaN<NA>
92389239323543200371404113,70013,300<NA><NA><NA>NaN<NA>
4472447327657320032184906,4406,440<NA><NA><NA>NaN<NA>
No일련번호법정동행정동리구분본번부번결정지가전년지가Unnamed: 10Unnamed: 11Unnamed: 12Unnamed: 13Unnamed: 14
37873788269813200321363322,20015,400<NA><NA><NA>NaN<NA>
330833092650932003122490363346<NA><NA><NA>NaN<NA>
30573058262623200312403536486<NA><NA><NA>NaN<NA>
3474347526672320032112105,1404,960<NA><NA><NA>NaN<NA>
565723313320030152012,50011,500<NA><NA><NA>NaN<NA>
160616072483532003119025,7908,190<NA><NA><NA>NaN<NA>
946947241883200301705923,70022,300<NA><NA><NA>NaN<NA>
81418142312773200361410013,50013,500<NA><NA><NA>NaN<NA>
9649965032758320037171811312,10011,100<NA><NA><NA>NaN<NA>
93029303324173200371468118,80017,900<NA><NA><NA>NaN<NA>