Overview

Dataset statistics

Number of variables10
Number of observations156
Missing cells540
Missing cells (%)34.6%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory13.2 KiB
Average record size in memory86.8 B

Variable types

Numeric6
Text2
DateTime2

Dataset

Description인천광역시 미추홀구 학익동 이행보증보험증권관리대장에 대한 데이터로 연번, 증권번호, 증권발급일,1년치금액, 2년치금액, 10년치금액, 수령일, 좌표값 등을 제공합니다.
Author인천광역시 미추홀구
URLhttps://data.incheon.go.kr/findData/publicDataDetail?dataId=15072182&srcSe=7661IVAWM27C61E190

Alerts

연번 is highly overall correlated with 10년치 금액High correlation
2년치 금액 is highly overall correlated with 10년치 금액High correlation
10년치 금액 is highly overall correlated with 연번 and 1 other fieldsHigh correlation
증권발급일 has 31 (19.9%) missing valuesMissing
1년치 금액 has 139 (89.1%) missing valuesMissing
2년치 금액 has 149 (95.5%) missing valuesMissing
10년치 금액 has 146 (93.6%) missing valuesMissing
수령일 has 71 (45.5%) missing valuesMissing
위도 has 2 (1.3%) missing valuesMissing
경도 has 2 (1.3%) missing valuesMissing
연번 has unique valuesUnique

Reproduction

Analysis started2024-01-28 09:29:13.869831
Analysis finished2024-01-28 09:29:17.292280
Duration3.42 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

연번
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct156
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean78.5
Minimum1
Maximum156
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.5 KiB
2024-01-28T18:29:17.361497image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile8.75
Q139.75
median78.5
Q3117.25
95-th percentile148.25
Maximum156
Range155
Interquartile range (IQR)77.5

Descriptive statistics

Standard deviation45.177428
Coefficient of variation (CV)0.57550864
Kurtosis-1.2
Mean78.5
Median Absolute Deviation (MAD)39
Skewness0
Sum12246
Variance2041
MonotonicityStrictly increasing
2024-01-28T18:29:17.472593image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 1
 
0.6%
109 1
 
0.6%
102 1
 
0.6%
103 1
 
0.6%
104 1
 
0.6%
105 1
 
0.6%
106 1
 
0.6%
107 1
 
0.6%
108 1
 
0.6%
110 1
 
0.6%
Other values (146) 146
93.6%
ValueCountFrequency (%)
1 1
0.6%
2 1
0.6%
3 1
0.6%
4 1
0.6%
5 1
0.6%
6 1
0.6%
7 1
0.6%
8 1
0.6%
9 1
0.6%
10 1
0.6%
ValueCountFrequency (%)
156 1
0.6%
155 1
0.6%
154 1
0.6%
153 1
0.6%
152 1
0.6%
151 1
0.6%
150 1
0.6%
149 1
0.6%
148 1
0.6%
147 1
0.6%

지번주소
Text

Distinct154
Distinct (%)98.7%
Missing0
Missing (%)0.0%
Memory size1.3 KiB
2024-01-28T18:29:17.662853image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length50
Median length48
Mean length22.673077
Min length18

Characters and Unicode

Total characters3537
Distinct characters67
Distinct categories8 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique152 ?
Unique (%)97.4%

Sample

1st row인천광역시 미추홀구 학익동 322-22
2nd row인천광역시 미추홀구 학익동 322-25
3rd row인천광역시 미추홀구 학익동 687-1
4th row인천광역시 미추홀구 학익동 322-31,48
5th row인천광역시 미추홀구 학익동 697-4
ValueCountFrequency (%)
인천광역시 156
23.5%
미추홀구 156
23.5%
학익동 153
23.0%
2동 3
 
0.5%
27bl 3
 
0.5%
외 3
 
0.5%
1동 2
 
0.3%
668-2 2
 
0.3%
학익2동 2
 
0.3%
9lt 2
 
0.3%
Other values (177) 182
27.4%
2024-01-28T18:29:17.958980image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
509
 
14.4%
동 171
 
4.8%
시 158
 
4.5%
학 157
 
4.4%
익 157
 
4.4%
미 157
 
4.4%
추 157
 
4.4%
홀 157
 
4.4%
천 156
 
4.4%
인 156
 
4.4%
Other values (57) 1602
45.3%

Most occurring categories

ValueCountFrequency (%)
Other Letter 2020
57.1%
Decimal Number 748
 
21.1%
Space Separator 509
 
14.4%
Dash Punctuation 151
 
4.3%
Uppercase Letter 42
 
1.2%
Close Punctuation 27
 
0.8%
Open Punctuation 27
 
0.8%
Other Punctuation 13
 
0.4%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
동 171
 
8.5%
시 158
 
7.8%
학 157
 
7.8%
익 157
 
7.8%
미 157
 
7.8%
추 157
 
7.8%
홀 157
 
7.8%
천 156
 
7.7%
인 156
 
7.7%
구 156
 
7.7%
Other values (38) 438
21.7%
Decimal Number
ValueCountFrequency (%)
1 126
16.8%
3 105
14.0%
2 102
13.6%
6 89
11.9%
0 80
10.7%
5 58
7.8%
7 56
7.5%
4 53
7.1%
8 46
 
6.1%
9 33
 
4.4%
Uppercase Letter
ValueCountFrequency (%)
L 20
47.6%
B 11
26.2%
T 10
23.8%
A 1
 
2.4%
Space Separator
ValueCountFrequency (%)
509
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 151
100.0%
Close Punctuation
ValueCountFrequency (%)
) 27
100.0%
Open Punctuation
ValueCountFrequency (%)
( 27
100.0%
Other Punctuation
ValueCountFrequency (%)
, 13
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 2020
57.1%
Common 1475
41.7%
Latin 42
 
1.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
동 171
 
8.5%
시 158
 
7.8%
학 157
 
7.8%
익 157
 
7.8%
미 157
 
7.8%
추 157
 
7.8%
홀 157
 
7.8%
천 156
 
7.7%
인 156
 
7.7%
구 156
 
7.7%
Other values (38) 438
21.7%
Common
ValueCountFrequency (%)
509
34.5%
- 151
 
10.2%
1 126
 
8.5%
3 105
 
7.1%
2 102
 
6.9%
6 89
 
6.0%
0 80
 
5.4%
5 58
 
3.9%
7 56
 
3.8%
4 53
 
3.6%
Other values (5) 146
 
9.9%
Latin
ValueCountFrequency (%)
L 20
47.6%
B 11
26.2%
T 10
23.8%
A 1
 
2.4%

Most occurring blocks

ValueCountFrequency (%)
Hangul 2020
57.1%
ASCII 1517
42.9%

Most frequent character per block

ASCII
ValueCountFrequency (%)
509
33.6%
- 151
 
10.0%
1 126
 
8.3%
3 105
 
6.9%
2 102
 
6.7%
6 89
 
5.9%
0 80
 
5.3%
5 58
 
3.8%
7 56
 
3.7%
4 53
 
3.5%
Other values (9) 188
 
12.4%
Hangul
ValueCountFrequency (%)
동 171
 
8.5%
시 158
 
7.8%
학 157
 
7.8%
익 157
 
7.8%
미 157
 
7.8%
추 157
 
7.8%
홀 157
 
7.8%
천 156
 
7.7%
인 156
 
7.7%
구 156
 
7.7%
Other values (38) 438
21.7%

증권번호
Text

Distinct153
Distinct (%)98.1%
Missing0
Missing (%)0.0%
Memory size1.3 KiB
2024-01-28T18:29:18.135764image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length23
Median length22
Mean length20.634615
Min length10

Characters and Unicode

Total characters3219
Distinct characters16
Distinct categories5 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique150 ?
Unique (%)96.2%

Sample

1st row310-023-200100021617-21
2nd row310-023-200100021628
3rd row310-023-200100016046-49
4th row310-023-200000005293-94
5th row310-023-200000019919
ValueCountFrequency (%)
100-000-2015 8
 
3.7%
0000 6
 
2.8%
100-000-2013 5
 
2.3%
100-000-2014 4
 
1.8%
100-000-2016 3
 
1.4%
100-000-2020 3
 
1.4%
0232 2
 
0.9%
0260 2
 
0.9%
0247 2
 
0.9%
0513 2
 
0.9%
Other values (173) 181
83.0%
2024-01-28T18:29:18.421022image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 1138
35.4%
2 402
 
12.5%
- 351
 
10.9%
1 341
 
10.6%
3 298
 
9.3%
9 111
 
3.4%
6 108
 
3.4%
5 106
 
3.3%
7 102
 
3.2%
4 99
 
3.1%
Other values (6) 163
 
5.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 2787
86.6%
Dash Punctuation 351
 
10.9%
Space Separator 62
 
1.9%
Other Letter 15
 
0.5%
Math Symbol 4
 
0.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 1138
40.8%
2 402
 
14.4%
1 341
 
12.2%
3 298
 
10.7%
9 111
 
4.0%
6 108
 
3.9%
5 106
 
3.8%
7 102
 
3.7%
4 99
 
3.6%
8 82
 
2.9%
Other Letter
ValueCountFrequency (%)
인 7
46.7%
하 7
46.7%
동 1
 
6.7%
Dash Punctuation
ValueCountFrequency (%)
- 351
100.0%
Space Separator
ValueCountFrequency (%)
62
100.0%
Math Symbol
ValueCountFrequency (%)
~ 4
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 3204
99.5%
Hangul 15
 
0.5%

Most frequent character per script

Common
ValueCountFrequency (%)
0 1138
35.5%
2 402
 
12.5%
- 351
 
11.0%
1 341
 
10.6%
3 298
 
9.3%
9 111
 
3.5%
6 108
 
3.4%
5 106
 
3.3%
7 102
 
3.2%
4 99
 
3.1%
Other values (3) 148
 
4.6%
Hangul
ValueCountFrequency (%)
인 7
46.7%
하 7
46.7%
동 1
 
6.7%

Most occurring blocks

ValueCountFrequency (%)
ASCII 3204
99.5%
Hangul 15
 
0.5%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 1138
35.5%
2 402
 
12.5%
- 351
 
11.0%
1 341
 
10.6%
3 298
 
9.3%
9 111
 
3.5%
6 108
 
3.4%
5 106
 
3.3%
7 102
 
3.2%
4 99
 
3.1%
Other values (3) 148
 
4.6%
Hangul
ValueCountFrequency (%)
인 7
46.7%
하 7
46.7%
동 1
 
6.7%

증권발급일
Date

MISSING 

Distinct104
Distinct (%)83.2%
Missing31
Missing (%)19.9%
Memory size1.3 KiB
Minimum1998-01-19 00:00:00
Maximum2022-09-23 00:00:00
2024-01-28T18:29:18.530118image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-28T18:29:18.667522image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

1년치 금액
Real number (ℝ)

MISSING 

Distinct17
Distinct (%)100.0%
Missing139
Missing (%)89.1%
Infinite0
Infinite (%)0.0%
Mean2126660.8
Minimum956240
Maximum4946290
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.5 KiB
2024-01-28T18:29:18.765352image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum956240
5-th percentile1356952
Q11638620
median1922830
Q32170850
95-th percentile3296618
Maximum4946290
Range3990050
Interquartile range (IQR)532230

Descriptive statistics

Standard deviation887176.45
Coefficient of variation (CV)0.41716876
Kurtosis6.1021754
Mean2126660.8
Median Absolute Deviation (MAD)284210
Skewness2.1389362
Sum36153234
Variance7.8708205 × 1011
MonotonicityNot monotonic
2024-01-28T18:29:18.860925image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=17)
ValueCountFrequency (%)
1941370 1
 
0.6%
1922830 1
 
0.6%
956240 1
 
0.6%
4946290 1
 
0.6%
1869440 1
 
0.6%
1913640 1
 
0.6%
2170850 1
 
0.6%
1638620 1
 
0.6%
2884200 1
 
0.6%
1965190 1
 
0.6%
Other values (7) 7
 
4.5%
(Missing) 139
89.1%
ValueCountFrequency (%)
956240 1
0.6%
1457130 1
0.6%
1584380 1
0.6%
1591088 1
0.6%
1638620 1
0.6%
1684900 1
0.6%
1869440 1
0.6%
1913640 1
0.6%
1922830 1
0.6%
1941370 1
0.6%
ValueCountFrequency (%)
4946290 1
0.6%
2884200 1
0.6%
2857486 1
0.6%
2805460 1
0.6%
2170850 1
0.6%
1965190 1
0.6%
1964120 1
0.6%
1941370 1
0.6%
1922830 1
0.6%
1913640 1
0.6%

2년치 금액
Real number (ℝ)

HIGH CORRELATION  MISSING 

Distinct7
Distinct (%)100.0%
Missing149
Missing (%)95.5%
Infinite0
Infinite (%)0.0%
Mean36501834
Minimum3022690
Maximum2.0493919 × 108
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.5 KiB
2024-01-28T18:29:18.964236image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum3022690
5-th percentile3024538
Q15173015
median9231100
Q313986915
95-th percentile1.4898396 × 108
Maximum2.0493919 × 108
Range2.019165 × 108
Interquartile range (IQR)8813900

Descriptive statistics

Standard deviation74454742
Coefficient of variation (CV)2.0397535
Kurtosis6.8905614
Mean36501834
Median Absolute Deviation (MAD)6202250
Skewness2.6192209
Sum2.5551284 × 108
Variance5.5435087 × 1015
MonotonicityNot monotonic
2024-01-28T18:29:19.054443image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=7)
ValueCountFrequency (%)
9231100 1
 
0.6%
3022690 1
 
0.6%
7317180 1
 
0.6%
9552080 1
 
0.6%
18421750 1
 
0.6%
204939189 1
 
0.6%
3028850 1
 
0.6%
(Missing) 149
95.5%
ValueCountFrequency (%)
3022690 1
0.6%
3028850 1
0.6%
7317180 1
0.6%
9231100 1
0.6%
9552080 1
0.6%
18421750 1
0.6%
204939189 1
0.6%
ValueCountFrequency (%)
204939189 1
0.6%
18421750 1
0.6%
9552080 1
0.6%
9231100 1
0.6%
7317180 1
0.6%
3028850 1
0.6%
3022690 1
0.6%

10년치 금액
Real number (ℝ)

HIGH CORRELATION  MISSING 

Distinct10
Distinct (%)100.0%
Missing146
Missing (%)93.6%
Infinite0
Infinite (%)0.0%
Mean35561245
Minimum3757450
Maximum2.7325225 × 108
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.5 KiB
2024-01-28T18:29:19.147859image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum3757450
5-th percentile3855154
Q14032305
median8476445
Q312629115
95-th percentile1.6134179 × 108
Maximum2.7325225 × 108
Range2.694948 × 108
Interquartile range (IQR)8596810

Descriptive statistics

Standard deviation83763702
Coefficient of variation (CV)2.3554772
Kurtosis9.8369058
Mean35561245
Median Absolute Deviation (MAD)4442085
Skewness3.1280873
Sum3.5561245 × 108
Variance7.0163578 × 1015
MonotonicityNot monotonic
2024-01-28T18:29:19.235469image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=10)
ValueCountFrequency (%)
3974570 1
 
0.6%
7196650 1
 
0.6%
3757450 1
 
0.6%
12308130 1
 
0.6%
4030250 1
 
0.6%
9756240 1
 
0.6%
12736110 1
 
0.6%
24562330 1
 
0.6%
273252249 1
 
0.6%
4038470 1
 
0.6%
(Missing) 146
93.6%
ValueCountFrequency (%)
3757450 1
0.6%
3974570 1
0.6%
4030250 1
0.6%
4038470 1
0.6%
7196650 1
0.6%
9756240 1
0.6%
12308130 1
0.6%
12736110 1
0.6%
24562330 1
0.6%
273252249 1
0.6%
ValueCountFrequency (%)
273252249 1
0.6%
24562330 1
0.6%
12736110 1
0.6%
12308130 1
0.6%
9756240 1
0.6%
7196650 1
0.6%
4038470 1
0.6%
4030250 1
0.6%
3974570 1
0.6%
3757450 1
0.6%

수령일
Date

MISSING 

Distinct79
Distinct (%)92.9%
Missing71
Missing (%)45.5%
Memory size1.3 KiB
Minimum2003-04-14 00:00:00
Maximum2020-06-01 00:00:00
2024-01-28T18:29:19.340080image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-28T18:29:19.452712image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

위도
Real number (ℝ)

MISSING 

Distinct127
Distinct (%)82.5%
Missing2
Missing (%)1.3%
Infinite0
Infinite (%)0.0%
Mean37.44213
Minimum37.437697
Maximum37.449239
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.5 KiB
2024-01-28T18:29:19.859144image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum37.437697
5-th percentile37.437897
Q137.438976
median37.439732
Q337.445948
95-th percentile37.448841
Maximum37.449239
Range0.0115416
Interquartile range (IQR)0.0069716175

Descriptive statistics

Standard deviation0.0037859934
Coefficient of variation (CV)0.00010111587
Kurtosis-1.3912803
Mean37.44213
Median Absolute Deviation (MAD)0.001812005
Skewness0.44815834
Sum5766.0879
Variance1.4333746 × 10-5
MonotonicityNot monotonic
2024-01-28T18:29:19.972789image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
37.4394588 19
 
12.2%
37.4447391 3
 
1.9%
37.4407637 2
 
1.3%
37.43797397 2
 
1.3%
37.43796566 2
 
1.3%
37.4378971 2
 
1.3%
37.43796989 2
 
1.3%
37.44664178 2
 
1.3%
37.4491491 2
 
1.3%
37.4418569 1
 
0.6%
Other values (117) 117
75.0%
(Missing) 2
 
1.3%
ValueCountFrequency (%)
37.437697 1
0.6%
37.43770886 1
0.6%
37.43771712 1
0.6%
37.43773293 1
0.6%
37.43775134 1
0.6%
37.43782873 1
0.6%
37.43785391 1
0.6%
37.4378971 2
1.3%
37.43794313 1
0.6%
37.43795438 1
0.6%
ValueCountFrequency (%)
37.4492386 1
0.6%
37.4492209 1
0.6%
37.4491491 2
1.3%
37.4491479 1
0.6%
37.449004 1
0.6%
37.4489503 1
0.6%
37.4488875 1
0.6%
37.4488158 1
0.6%
37.4487352 1
0.6%
37.4486725 1
0.6%

경도
Real number (ℝ)

MISSING 

Distinct126
Distinct (%)81.8%
Missing2
Missing (%)1.3%
Infinite0
Infinite (%)0.0%
Mean126.66403
Minimum126.65254
Maximum126.67716
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.5 KiB
2024-01-28T18:29:20.098009image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum126.65254
5-th percentile126.65473
Q1126.65906
median126.66468
Q3126.66896
95-th percentile126.67623
Maximum126.67716
Range0.0246222
Interquartile range (IQR)0.00989715

Descriptive statistics

Standard deviation0.0066320944
Coefficient of variation (CV)5.2359728 × 10-5
Kurtosis-0.88076285
Mean126.66403
Median Absolute Deviation (MAD)0.0053815
Skewness0.17570548
Sum19506.261
Variance4.3984676 × 10-5
MonotonicityNot monotonic
2024-01-28T18:29:20.213667image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
126.654729 19
 
12.2%
126.670593 3
 
1.9%
126.659363 2
 
1.3%
126.6763216 2
 
1.3%
126.6761509 2
 
1.3%
126.670487 2
 
1.3%
126.6703182 2
 
1.3%
126.67313 2
 
1.3%
126.6651324 2
 
1.3%
126.668962 2
 
1.3%
Other values (116) 116
74.4%
(Missing) 2
 
1.3%
ValueCountFrequency (%)
126.6525388 1
 
0.6%
126.6529136 1
 
0.6%
126.6533037 1
 
0.6%
126.654729 19
12.2%
126.6553331 1
 
0.6%
126.6553596 1
 
0.6%
126.6554788 1
 
0.6%
126.6555296 1
 
0.6%
126.6557183 1
 
0.6%
126.6560659 1
 
0.6%
ValueCountFrequency (%)
126.677161 1
0.6%
126.6771284 1
0.6%
126.6770678 1
0.6%
126.6765715 1
0.6%
126.6763964 1
0.6%
126.6763216 2
1.3%
126.6762324 1
0.6%
126.6762315 1
0.6%
126.6761509 2
1.3%
126.6759103 1
0.6%

Interactions

2024-01-28T18:29:16.500144image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-28T18:29:14.172575image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-28T18:29:14.634001image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-28T18:29:15.273948image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-28T18:29:15.708741image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-28T18:29:16.090843image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-28T18:29:16.585464image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-28T18:29:14.270565image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-28T18:29:14.708489image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-28T18:29:15.341763image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-28T18:29:15.773546image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-28T18:29:16.165969image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-28T18:29:16.673335image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-28T18:29:14.356174image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-28T18:29:14.785617image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-28T18:29:15.399664image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-28T18:29:15.829195image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-28T18:29:16.235602image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-28T18:29:16.761334image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-28T18:29:14.440750image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-28T18:29:14.839550image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-28T18:29:15.472954image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-28T18:29:15.901034image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-28T18:29:16.304169image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-28T18:29:16.826059image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-28T18:29:14.500423image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-28T18:29:15.140688image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-28T18:29:15.548349image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-28T18:29:15.965000image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-28T18:29:16.372895image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-28T18:29:16.890189image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-28T18:29:14.570543image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-28T18:29:15.206190image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-28T18:29:15.619272image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-28T18:29:16.029494image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-28T18:29:16.437352image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-01-28T18:29:20.286546image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연번1년치 금액2년치 금액10년치 금액수령일위도경도
연번1.0000.534NaNNaN0.9670.7250.805
1년치 금액0.5341.000NaNNaN1.0000.8170.240
2년치 금액NaNNaN1.0000.000NaNNaNNaN
10년치 금액NaNNaN0.0001.000NaNNaNNaN
수령일0.9671.000NaNNaN1.0000.9500.792
위도0.7250.817NaNNaN0.9501.0000.880
경도0.8050.240NaNNaN0.7920.8801.000
2024-01-28T18:29:20.390231image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연번1년치 금액2년치 금액10년치 금액위도경도
연번1.000-0.1990.3210.6000.0800.365
1년치 금액-0.1991.000NaNNaN-0.1240.053
2년치 금액0.321NaN1.0001.0000.2000.200
10년치 금액0.600NaN1.0001.000-0.4290.143
위도0.080-0.1240.200-0.4291.000-0.061
경도0.3650.0530.2000.143-0.0611.000

Missing values

2024-01-28T18:29:16.992784image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-01-28T18:29:17.118819image/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.
2024-01-28T18:29:17.220344image/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

연번지번주소증권번호증권발급일1년치 금액2년치 금액10년치 금액수령일위도경도
01인천광역시 미추홀구 학익동 322-22310-023-200100021617-212001-11-28<NA><NA><NA><NA>37.4457126.660523
12인천광역시 미추홀구 학익동 322-25310-023-200100021628<NA><NA><NA><NA><NA>37.445759126.660377
23인천광역시 미추홀구 학익동 687-1310-023-200100016046-492001-09-30<NA><NA><NA>2004-10-0537.438989126.664887
34인천광역시 미추홀구 학익동 322-31,48310-023-200000005293-94<NA><NA><NA><NA><NA>37.446135126.660059
45인천광역시 미추홀구 학익동 697-4310-023-200000019919<NA><NA><NA><NA>2006-04-2837.439674126.661102
56인천광역시 미추홀구 학익동 705-16310-023-2001000220532001-11-15<NA><NA><NA>2004-06-0937.438574126.658634
67인천광역시 미추홀구 학익동 700-3310-023-200200000029-332002-01-02<NA><NA><NA>2006-03-2237.439034126.661297
78인천광역시 미추홀구 학익동 694-3310-023-200200001071-752002-01-10<NA><NA><NA><NA>37.438972126.662273
89인천광역시 미추홀구 학익동 705-1310-023-200100027271-752002-01-15<NA><NA><NA>2004-07-0237.438679126.657471
910인천광역시 미추홀구 학익동 696-3310-023-200200001539-432002-01-21<NA><NA><NA>2004-05-0737.439679126.6618
연번지번주소증권번호증권발급일1년치 금액2년치 금액10년치 금액수령일위도경도
146147인천광역시 미추홀구 학익동 2-34(9세대)100-000-2016 0402 78062016-10-04<NA><NA>3974570<NA>37.447314126.666449
147148인천광역시 미추홀구 학익동 265-1 업무시설(공동주택) 신축공사(19세대)100-000-2017 0763 61862017-02-28<NA><NA>71966502019-09-2337.443582126.665942
148149인천광역시 미추홀구 학익동 302-5(8세대)100-000-2017 0512 48942017-12-06<NA><NA>37574502018-10-2637.447178126.666182
149150인천광역시 미추홀구 학익동 138-10외1필지 공동주택(다세대주택) 신축공사(36세대)100-000-2018 0115 27062018-03-15<NA>9231100123081302019-03-0837.437989126.670046
150151인천광역시 미추홀구 학익동 311-9외 1필지(8세대) 다세대 신축100-000-2018 0536 16552018-12-18<NA>302269040302502020-06-0137.445886126.665265
151152인천광역시 미추홀구 학익동 2-10 외4필지 공동주택(도시형생활주택)신축공사(20세대)100-000-2020 0285 60552020-06-25<NA>73171809756240<NA>37.44717126.666615
152153인천광역시 미추홀구 학익동 303-10외 2필지 공동주택(연립주택) 신축공사(27세대)100-000-2020 0304 63692020-07-13<NA>955208012736110<NA>37.446663126.665849
153154인천광역시 미추홀구 학익동 301-1 외 13필지(47세대)100-000-2020 0519 76002020-12-02<NA>1842175024562330<NA>37.446889126.666244
154155인천광역시 미추홀구 학익동 학익2 주택재개발정비사업(공동주택) - 미추홀 트루엘파크 아파트2022 0000 00002022-06-07<NA>204939189273252249<NA><NA><NA>
155156인천광역시 미추홀구 학익동 312-13외 2필지(8세대)100-000-2022 0409 69292022-09-23<NA>30288504038470<NA><NA><NA>