Overview

Dataset statistics

Number of variables10
Number of observations619
Missing cells1871
Missing cells (%)30.2%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory52.1 KiB
Average record size in memory86.2 B

Variable types

Numeric6
Text3
DateTime1

Dataset

Description인천광역시 미추홀구 용현동 이행보증보험증권관리대장에 대한 데이터로 증권번호, 증권발급일,1년치금액, 2년치금액, 10년치금액, 수령일,위도,경도 등을 제공합니다.
URLhttps://www.data.go.kr/data/15071382/fileData.do

Alerts

2년치 금액(예치금액의 0_45퍼센트) is highly overall correlated with 10년치 금액(예치금액의0_6퍼센트)High correlation
10년치 금액(예치금액의0_6퍼센트) is highly overall correlated with 2년치 금액(예치금액의 0_45퍼센트)High correlation
1년치 금액(예치금액의 0_3퍼센트) has 518 (83.7%) missing valuesMissing
2년치 금액(예치금액의 0_45퍼센트) has 572 (92.4%) missing valuesMissing
10년치 금액(예치금액의0_6퍼센트) has 525 (84.8%) missing valuesMissing
수령일 has 224 (36.2%) missing valuesMissing
위도 has 13 (2.1%) missing valuesMissing
경도 has 13 (2.1%) missing valuesMissing
연번 has unique valuesUnique

Reproduction

Analysis started2023-12-12 05:13:40.991918
Analysis finished2023-12-12 05:13:46.101258
Duration5.11 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

연번
Real number (ℝ)

UNIQUE 

Distinct619
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean310
Minimum1
Maximum619
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size5.6 KiB
2023-12-12T14:13:46.173739image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile31.9
Q1155.5
median310
Q3464.5
95-th percentile588.1
Maximum619
Range618
Interquartile range (IQR)309

Descriptive statistics

Standard deviation178.83419
Coefficient of variation (CV)0.57688448
Kurtosis-1.2
Mean310
Median Absolute Deviation (MAD)155
Skewness0
Sum191890
Variance31981.667
MonotonicityStrictly increasing
2023-12-12T14:13:46.361611image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 1
 
0.2%
417 1
 
0.2%
410 1
 
0.2%
411 1
 
0.2%
412 1
 
0.2%
413 1
 
0.2%
414 1
 
0.2%
415 1
 
0.2%
416 1
 
0.2%
418 1
 
0.2%
Other values (609) 609
98.4%
ValueCountFrequency (%)
1 1
0.2%
2 1
0.2%
3 1
0.2%
4 1
0.2%
5 1
0.2%
6 1
0.2%
7 1
0.2%
8 1
0.2%
9 1
0.2%
10 1
0.2%
ValueCountFrequency (%)
619 1
0.2%
618 1
0.2%
617 1
0.2%
616 1
0.2%
615 1
0.2%
614 1
0.2%
613 1
0.2%
612 1
0.2%
611 1
0.2%
610 1
0.2%

지번주소
Text

Distinct615
Distinct (%)99.4%
Missing0
Missing (%)0.0%
Memory size5.0 KiB
2023-12-12T14:13:46.621468image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length63
Median length58
Mean length23.840065
Min length19

Characters and Unicode

Total characters14757
Distinct characters70
Distinct categories7 ?
Distinct scripts2 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique611 ?
Unique (%)98.7%

Sample

1st row인천광역시 미추홀구 용현동 629-107
2nd row인천광역시 미추홀구 용현동 617-100
3rd row인천광역시 미추홀구 용현동 629-73외1필지
4th row인천광역시 미추홀구 용현동 147-71외1필지
5th row인천광역시 미추홀구 용현동 177-40외1필지
ValueCountFrequency (%)
인천광역시 619
23.5%
미추홀구 619
23.5%
용현동 580
22.0%
외 22
 
0.8%
1필지 21
 
0.8%
용현5동 17
 
0.6%
신축공사(8세대 8
 
0.3%
용현1·4동 7
 
0.3%
공동주택 6
 
0.2%
신축공사 5
 
0.2%
Other values (699) 735
27.9%
2023-12-12T14:13:46.984968image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
2020
 
13.7%
동 661
 
4.5%
- 641
 
4.3%
시 621
 
4.2%
인 619
 
4.2%
홀 619
 
4.2%
천 619
 
4.2%
구 619
 
4.2%
추 619
 
4.2%
미 619
 
4.2%
Other values (60) 7100
48.1%

Most occurring categories

ValueCountFrequency (%)
Other Letter 8409
57.0%
Decimal Number 3392
23.0%
Space Separator 2020
 
13.7%
Dash Punctuation 641
 
4.3%
Open Punctuation 140
 
0.9%
Close Punctuation 140
 
0.9%
Other Punctuation 15
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
동 661
 
7.9%
시 621
 
7.4%
인 619
 
7.4%
홀 619
 
7.4%
천 619
 
7.4%
구 619
 
7.4%
추 619
 
7.4%
미 619
 
7.4%
역 619
 
7.4%
광 619
 
7.4%
Other values (42) 2175
25.9%
Decimal Number
ValueCountFrequency (%)
1 596
17.6%
2 511
15.1%
6 504
14.9%
5 338
10.0%
4 298
8.8%
8 277
8.2%
7 272
8.0%
3 258
7.6%
0 172
 
5.1%
9 166
 
4.9%
Open Punctuation
ValueCountFrequency (%)
( 138
98.6%
[ 2
 
1.4%
Close Punctuation
ValueCountFrequency (%)
) 138
98.6%
] 2
 
1.4%
Other Punctuation
ValueCountFrequency (%)
, 8
53.3%
· 7
46.7%
Space Separator
ValueCountFrequency (%)
2020
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 641
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 8409
57.0%
Common 6348
43.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
동 661
 
7.9%
시 621
 
7.4%
인 619
 
7.4%
홀 619
 
7.4%
천 619
 
7.4%
구 619
 
7.4%
추 619
 
7.4%
미 619
 
7.4%
역 619
 
7.4%
광 619
 
7.4%
Other values (42) 2175
25.9%
Common
ValueCountFrequency (%)
2020
31.8%
- 641
 
10.1%
1 596
 
9.4%
2 511
 
8.0%
6 504
 
7.9%
5 338
 
5.3%
4 298
 
4.7%
8 277
 
4.4%
7 272
 
4.3%
3 258
 
4.1%
Other values (8) 633
 
10.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 8409
57.0%
ASCII 6341
43.0%
None 7
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
2020
31.9%
- 641
 
10.1%
1 596
 
9.4%
2 511
 
8.1%
6 504
 
7.9%
5 338
 
5.3%
4 298
 
4.7%
8 277
 
4.4%
7 272
 
4.3%
3 258
 
4.1%
Other values (7) 626
 
9.9%
Hangul
ValueCountFrequency (%)
동 661
 
7.9%
시 621
 
7.4%
인 619
 
7.4%
홀 619
 
7.4%
천 619
 
7.4%
구 619
 
7.4%
추 619
 
7.4%
미 619
 
7.4%
역 619
 
7.4%
광 619
 
7.4%
Other values (42) 2175
25.9%
None
ValueCountFrequency (%)
· 7
100.0%

증권번호
Text

Distinct606
Distinct (%)98.1%
Missing1
Missing (%)0.2%
Memory size5.0 KiB
2023-12-12T14:13:47.360070image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length47
Median length46
Mean length20.907767
Min length1

Characters and Unicode

Total characters12921
Distinct characters16
Distinct categories6 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique599 ?
Unique (%)96.9%

Sample

1st row310-023-200100001467-71
2nd row310-023-200100002078-82
3rd row310-023-200100002827-31
4th row310-023-200100003298-02
5th row310-023-200100003452-56
ValueCountFrequency (%)
100-000-2016 52
 
5.0%
100-000-2015 35
 
3.3%
100-000-2014 24
 
2.3%
100-000-2017 19
 
1.8%
0000 18
 
1.7%
100-000-2020 15
 
1.4%
100-000-2013 14
 
1.3%
100-000-2021 11
 
1.0%
100-000-2018 9
 
0.9%
100-000-2012 7
 
0.7%
Other values (777) 844
80.5%
2023-12-12T14:13:47.876919image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 4856
37.6%
2 1566
 
12.1%
1 1414
 
10.9%
- 1275
 
9.9%
3 966
 
7.5%
4 487
 
3.8%
432
 
3.3%
5 418
 
3.2%
6 396
 
3.1%
9 379
 
2.9%
Other values (6) 732
 
5.7%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 11191
86.6%
Dash Punctuation 1275
 
9.9%
Space Separator 432
 
3.3%
Math Symbol 12
 
0.1%
Other Letter 10
 
0.1%
Other Punctuation 1
 
< 0.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 4856
43.4%
2 1566
 
14.0%
1 1414
 
12.6%
3 966
 
8.6%
4 487
 
4.4%
5 418
 
3.7%
6 396
 
3.5%
9 379
 
3.4%
7 359
 
3.2%
8 350
 
3.1%
Other Letter
ValueCountFrequency (%)
인 5
50.0%
하 5
50.0%
Dash Punctuation
ValueCountFrequency (%)
- 1275
100.0%
Space Separator
ValueCountFrequency (%)
432
100.0%
Math Symbol
ValueCountFrequency (%)
~ 12
100.0%
Other Punctuation
ValueCountFrequency (%)
. 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 12911
99.9%
Hangul 10
 
0.1%

Most frequent character per script

Common
ValueCountFrequency (%)
0 4856
37.6%
2 1566
 
12.1%
1 1414
 
11.0%
- 1275
 
9.9%
3 966
 
7.5%
4 487
 
3.8%
432
 
3.3%
5 418
 
3.2%
6 396
 
3.1%
9 379
 
2.9%
Other values (4) 722
 
5.6%
Hangul
ValueCountFrequency (%)
인 5
50.0%
하 5
50.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 12911
99.9%
Hangul 10
 
0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 4856
37.6%
2 1566
 
12.1%
1 1414
 
11.0%
- 1275
 
9.9%
3 966
 
7.5%
4 487
 
3.8%
432
 
3.3%
5 418
 
3.2%
6 396
 
3.1%
9 379
 
2.9%
Other values (4) 722
 
5.6%
Hangul
ValueCountFrequency (%)
인 5
50.0%
하 5
50.0%

증권발급일
Date

Distinct489
Distinct (%)79.6%
Missing5
Missing (%)0.8%
Memory size5.0 KiB
Minimum1986-05-24 00:00:00
Maximum2023-01-19 00:00:00
2023-12-12T14:13:48.106715image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T14:13:48.326559image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

1년치 금액(예치금액의 0_3퍼센트)
Real number (ℝ)

MISSING 

Distinct93
Distinct (%)92.1%
Missing518
Missing (%)83.7%
Infinite0
Infinite (%)0.0%
Mean19048648
Minimum569260
Maximum1.7411994 × 109
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size5.6 KiB
2023-12-12T14:13:48.542239image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum569260
5-th percentile1009990
Q11402350
median1651690
Q31943840
95-th percentile2829200
Maximum1.7411994 × 109
Range1.7406301 × 109
Interquartile range (IQR)541490

Descriptive statistics

Standard deviation1.7307861 × 108
Coefficient of variation (CV)9.0861362
Kurtosis100.98893
Mean19048648
Median Absolute Deviation (MAD)273070
Skewness10.049061
Sum1.9239134 × 109
Variance2.9956205 × 1016
MonotonicityNot monotonic
2023-12-12T14:13:48.759421image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1902480 2
 
0.3%
1906060 2
 
0.3%
1476460 2
 
0.3%
1595410 2
 
0.3%
1009990 2
 
0.3%
1400010 2
 
0.3%
1431350 2
 
0.3%
1556860 2
 
0.3%
2039466 1
 
0.2%
1890610 1
 
0.2%
Other values (83) 83
 
13.4%
(Missing) 518
83.7%
ValueCountFrequency (%)
569260 1
0.2%
756320 1
0.2%
817940 1
0.2%
910570 1
0.2%
1009990 2
0.3%
1047930 1
0.2%
1140500 1
0.2%
1188360 1
0.2%
1195400 1
0.2%
1210590 1
0.2%
ValueCountFrequency (%)
1741199377 1
0.2%
13101667 1
0.2%
5420890 1
0.2%
2891690 1
0.2%
2833810 1
0.2%
2829200 1
0.2%
2620740 1
0.2%
2365390 1
0.2%
2102460 1
0.2%
2100590 1
0.2%

2년치 금액(예치금액의 0_45퍼센트)
Real number (ℝ)

HIGH CORRELATION  MISSING 

Distinct46
Distinct (%)97.9%
Missing572
Missing (%)92.4%
Infinite0
Infinite (%)0.0%
Mean3631571.7
Minimum1949160
Maximum10214260
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size5.6 KiB
2023-12-12T14:13:49.012983image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1949160
5-th percentile2308080
Q12620495
median3028940
Q33223535
95-th percentile7677368
Maximum10214260
Range8265100
Interquartile range (IQR)603040

Descriptive statistics

Standard deviation1844956.4
Coefficient of variation (CV)0.50803249
Kurtosis3.5729207
Mean3631571.7
Median Absolute Deviation (MAD)374990
Skewness2.0287555
Sum1.7068387 × 108
Variance3.4038643 × 1012
MonotonicityNot monotonic
2023-12-12T14:13:49.192957image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=46)
ValueCountFrequency (%)
2308080 2
 
0.3%
3031230 1
 
0.2%
8489530 1
 
0.2%
2636870 1
 
0.2%
2446570 1
 
0.2%
2464440 1
 
0.2%
3081480 1
 
0.2%
2390620 1
 
0.2%
3063620 1
 
0.2%
2407150 1
 
0.2%
Other values (36) 36
 
5.8%
(Missing) 572
92.4%
ValueCountFrequency (%)
1949160 1
0.2%
2045380 1
0.2%
2308080 2
0.3%
2324680 1
0.2%
2328820 1
0.2%
2390620 1
0.2%
2407150 1
0.2%
2446570 1
0.2%
2464440 1
0.2%
2493760 1
0.2%
ValueCountFrequency (%)
10214260 1
0.2%
8489530 1
0.2%
7970180 1
0.2%
6994140 1
0.2%
6743690 1
0.2%
6362970 1
0.2%
6327230 1
0.2%
5260530 1
0.2%
4786720 1
0.2%
4255780 1
0.2%

10년치 금액(예치금액의0_6퍼센트)
Real number (ℝ)

HIGH CORRELATION  MISSING 

Distinct91
Distinct (%)96.8%
Missing525
Missing (%)84.8%
Infinite0
Infinite (%)0.0%
Mean5039073.8
Minimum1242720
Maximum13702270
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size5.6 KiB
2023-12-12T14:13:49.402024image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1242720
5-th percentile2809505.5
Q13361797.5
median4037380
Q34319025
95-th percentile11351592
Maximum13702270
Range12459550
Interquartile range (IQR)957227.5

Descriptive statistics

Standard deviation2832399.5
Coefficient of variation (CV)0.56208732
Kurtosis1.6714026
Mean5039073.8
Median Absolute Deviation (MAD)638795
Skewness1.6342556
Sum4.7367293 × 108
Variance8.0224868 × 1012
MonotonicityNot monotonic
2023-12-12T14:13:49.603364image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
3119420 2
 
0.3%
3699870 2
 
0.3%
3077440 2
 
0.3%
4269050 1
 
0.2%
4145090 1
 
0.2%
4038210 1
 
0.2%
8991580 1
 
0.2%
3538600 1
 
0.2%
4037290 1
 
0.2%
4323120 1
 
0.2%
Other values (81) 81
 
13.1%
(Missing) 525
84.8%
ValueCountFrequency (%)
1242720 1
0.2%
1406260 1
0.2%
2340992 1
0.2%
2598880 1
0.2%
2727170 1
0.2%
2853840 1
0.2%
3050280 1
0.2%
3077440 2
0.3%
3097110 1
0.2%
3099580 1
0.2%
ValueCountFrequency (%)
13702270 1
0.2%
13619010 1
0.2%
12292380 1
0.2%
12161430 1
0.2%
11416390 1
0.2%
11316700 1
0.2%
11270700 1
0.2%
11169220 1
0.2%
11037200 1
0.2%
10626900 1
0.2%

수령일
Text

MISSING 

Distinct343
Distinct (%)86.8%
Missing224
Missing (%)36.2%
Memory size5.0 KiB
2023-12-12T14:13:49.941906image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length1024
Median length10
Mean length12.567089
Min length10

Characters and Unicode

Total characters4964
Distinct characters12
Distinct categories3 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique313 ?
Unique (%)79.2%

Sample

1st row2004-11-10
2nd row2006-02-16
3rd row2005-03-10
4th row2005-05-12
5th row2006-02-13
ValueCountFrequency (%)
2015-08-31 10
 
2.5%
2020-06-24 7
 
1.8%
2009-12-03 4
 
1.0%
2004-10-29 3
 
0.8%
2004-05-20 3
 
0.8%
2009-04-29 3
 
0.8%
2005-09-26 3
 
0.8%
2014-07-15 3
 
0.8%
2005-06-30 3
 
0.8%
2012-10-25 3
 
0.8%
Other values (332) 352
89.3%
2023-12-12T14:13:50.418318image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 1099
22.1%
1024
20.6%
- 788
15.9%
2 664
13.4%
1 571
11.5%
5 147
 
3.0%
4 146
 
2.9%
3 132
 
2.7%
6 112
 
2.3%
7 101
 
2.0%
Other values (2) 180
 
3.6%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 3152
63.5%
Space Separator 1024
 
20.6%
Dash Punctuation 788
 
15.9%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 1099
34.9%
2 664
21.1%
1 571
18.1%
5 147
 
4.7%
4 146
 
4.6%
3 132
 
4.2%
6 112
 
3.6%
7 101
 
3.2%
8 91
 
2.9%
9 89
 
2.8%
Space Separator
ValueCountFrequency (%)
1024
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 788
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 4964
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 1099
22.1%
1024
20.6%
- 788
15.9%
2 664
13.4%
1 571
11.5%
5 147
 
3.0%
4 146
 
2.9%
3 132
 
2.7%
6 112
 
2.3%
7 101
 
2.0%
Other values (2) 180
 
3.6%

Most occurring blocks

ValueCountFrequency (%)
ASCII 4964
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 1099
22.1%
1024
20.6%
- 788
15.9%
2 664
13.4%
1 571
11.5%
5 147
 
3.0%
4 146
 
2.9%
3 132
 
2.7%
6 112
 
2.3%
7 101
 
2.0%
Other values (2) 180
 
3.6%

위도
Real number (ℝ)

MISSING 

Distinct592
Distinct (%)97.7%
Missing13
Missing (%)2.1%
Infinite0
Infinite (%)0.0%
Mean37.453917
Minimum37.446093
Maximum37.465531
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size5.6 KiB
2023-12-12T14:13:50.623825image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum37.446093
5-th percentile37.448619
Q137.452155
median37.454192
Q337.455716
95-th percentile37.457833
Maximum37.465531
Range0.01943815
Interquartile range (IQR)0.0035611275

Descriptive statistics

Standard deviation0.0027576764
Coefficient of variation (CV)7.3628517 × 10-5
Kurtosis-0.0093670339
Mean37.453917
Median Absolute Deviation (MAD)0.0017763
Skewness-0.16947468
Sum22697.074
Variance7.604779 × 10-6
MonotonicityNot monotonic
2023-12-12T14:13:50.836739image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
37.451501 10
 
1.6%
37.45256175 2
 
0.3%
37.4572994 2
 
0.3%
37.4574068 2
 
0.3%
37.45481488 2
 
0.3%
37.45201495 2
 
0.3%
37.4478919 1
 
0.2%
37.4556069 1
 
0.2%
37.4540343 1
 
0.2%
37.45470455 1
 
0.2%
Other values (582) 582
94.0%
(Missing) 13
 
2.1%
ValueCountFrequency (%)
37.4460929 1
0.2%
37.44759398 1
0.2%
37.44764554 1
0.2%
37.44765686 1
0.2%
37.44774352 1
0.2%
37.4478919 1
0.2%
37.4479091 1
0.2%
37.44797 1
0.2%
37.44798503 1
0.2%
37.4480723 1
0.2%
ValueCountFrequency (%)
37.46553105 1
0.2%
37.4624391 1
0.2%
37.4598273 1
0.2%
37.4591933 1
0.2%
37.45909249 1
0.2%
37.4590397 1
0.2%
37.4590139 1
0.2%
37.45901218 1
0.2%
37.4588693 1
0.2%
37.45884513 1
0.2%

경도
Real number (ℝ)

MISSING 

Distinct592
Distinct (%)97.7%
Missing13
Missing (%)2.1%
Infinite0
Infinite (%)0.0%
Mean126.64707
Minimum126.63184
Maximum126.66738
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size5.6 KiB
2023-12-12T14:13:51.021580image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum126.63184
5-th percentile126.63441
Q1126.63767
median126.64125
Q3126.65912
95-th percentile126.66553
Maximum126.66738
Range0.0355408
Interquartile range (IQR)0.0214525

Descriptive statistics

Standard deviation0.011173813
Coefficient of variation (CV)8.8227963 × 10-5
Kurtosis-1.356176
Mean126.64707
Median Absolute Deviation (MAD)0.00597135
Skewness0.49443095
Sum76748.126
Variance0.0001248541
MonotonicityNot monotonic
2023-12-12T14:13:51.184813image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
126.647225 10
 
1.6%
126.6385472 2
 
0.3%
126.645864 2
 
0.3%
126.645615 2
 
0.3%
126.6557706 2
 
0.3%
126.6450629 2
 
0.3%
126.667121 1
 
0.2%
126.6586414 1
 
0.2%
126.638805 1
 
0.2%
126.6360885 1
 
0.2%
Other values (582) 582
94.0%
(Missing) 13
 
2.1%
ValueCountFrequency (%)
126.631837 1
0.2%
126.6326461 1
0.2%
126.632753 1
0.2%
126.632843 1
0.2%
126.632851 1
0.2%
126.632947 1
0.2%
126.633051 1
0.2%
126.633125 1
0.2%
126.6331908 1
0.2%
126.6333086 1
0.2%
ValueCountFrequency (%)
126.6673778 1
0.2%
126.66724 1
0.2%
126.667188 1
0.2%
126.667121 1
0.2%
126.6670522 1
0.2%
126.666996 1
0.2%
126.666861 1
0.2%
126.666617 1
0.2%
126.6665421 1
0.2%
126.6664918 1
0.2%

Interactions

2023-12-12T14:13:44.746125image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T14:13:41.324986image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T14:13:41.958881image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T14:13:42.655201image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T14:13:43.332850image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T14:13:44.010141image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T14:13:44.840774image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T14:13:41.426834image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T14:13:42.074934image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T14:13:42.749846image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T14:13:43.434827image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T14:13:44.176976image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T14:13:44.936367image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T14:13:41.520322image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T14:13:42.215847image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T14:13:42.851236image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T14:13:43.532312image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T14:13:44.298606image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T14:13:45.018241image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T14:13:41.597239image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T14:13:42.314513image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T14:13:42.965575image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T14:13:43.655178image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T14:13:44.410701image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T14:13:45.375511image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T14:13:41.683211image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T14:13:42.416166image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T14:13:43.101821image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T14:13:43.776949image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T14:13:44.514650image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T14:13:45.505672image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T14:13:41.837401image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T14:13:42.540908image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T14:13:43.222944image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T14:13:43.895115image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T14:13:44.630112image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-12T14:13:51.298491image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연번1년치 금액(예치금액의 0_3퍼센트)2년치 금액(예치금액의 0_45퍼센트)10년치 금액(예치금액의0_6퍼센트)위도경도
연번1.0000.000NaN0.2100.4060.537
1년치 금액(예치금액의 0_3퍼센트)0.0001.000NaNNaN0.0000.155
2년치 금액(예치금액의 0_45퍼센트)NaNNaN1.0000.9940.3730.000
10년치 금액(예치금액의0_6퍼센트)0.210NaN0.9941.0000.0000.487
위도0.4060.0000.3730.0001.0000.716
경도0.5370.1550.0000.4870.7161.000
2023-12-12T14:13:51.470654image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연번1년치 금액(예치금액의 0_3퍼센트)2년치 금액(예치금액의 0_45퍼센트)10년치 금액(예치금액의0_6퍼센트)위도경도
연번1.0000.361-0.1020.1250.146-0.220
1년치 금액(예치금액의 0_3퍼센트)0.3611.000NaNNaN-0.0610.098
2년치 금액(예치금액의 0_45퍼센트)-0.102NaN1.0001.000-0.118-0.029
10년치 금액(예치금액의0_6퍼센트)0.125NaN1.0001.000-0.033-0.082
위도0.146-0.061-0.118-0.0331.000-0.052
경도-0.2200.098-0.029-0.082-0.0521.000

Missing values

2023-12-12T14:13:45.663028image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-12T14:13:45.830496image/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.
2023-12-12T14:13:45.996017image/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 금액(예치금액의 0_3퍼센트)2년치 금액(예치금액의 0_45퍼센트)10년치 금액(예치금액의0_6퍼센트)수령일위도경도
01인천광역시 미추홀구 용현동 629-107310-023-200100001467-712001-01-30<NA><NA><NA><NA>37.45303126.635251
12인천광역시 미추홀구 용현동 617-100310-023-200100002078-822001-02-14<NA><NA><NA>2004-11-1037.451101126.63853
23인천광역시 미추홀구 용현동 629-73외1필지310-023-200100002827-312001-03-02<NA><NA><NA><NA>37.452669126.634449
34인천광역시 미추홀구 용현동 147-71외1필지310-023-200100003298-022001-03-06<NA><NA><NA>2006-02-1637.454393126.656287
45인천광역시 미추홀구 용현동 177-40외1필지310-023-200100003452-562001-03-12<NA><NA><NA>2005-03-1037.453188126.660192
56인천광역시 미추홀구 용현동 172-13310-023-200000002924-282001-03-20<NA><NA><NA>2005-05-1237.45372126.65952
67인천광역시 미추홀구 용현동 199-2310-023-200100004222-262001-03-29<NA><NA><NA>2006-02-1337.452195126.654949
78인천광역시 미추홀구 용현동 147-91외1필지310-023-200100005136-402001-04-20<NA><NA><NA>2001-09-1337.454698126.655958
89인천광역시 미추홀구 용현동 629-103310-023-200100005889-932001-05-04<NA><NA><NA>2006-02-1537.45326126.635431
910인천광역시 미추홀구 용현동 568-4310-023-200100006523-272001-05-11<NA><NA><NA>2003-10-2437.457798126.641674
연번지번주소증권번호증권발급일1년치 금액(예치금액의 0_3퍼센트)2년치 금액(예치금액의 0_45퍼센트)10년치 금액(예치금액의0_6퍼센트)수령일위도경도
609610인천광역시 미추홀구 용현동 684-143(8세대)100-000-2021 0470 45472021-11-05<NA>23080803077440<NA><NA><NA>
610611인천광역시 미추홀구 용현동 55 공동주택(단지형연립주택) 신축공사(22세대)100-000-2021 0512 45602021-12-02<NA>797018010626900<NA><NA><NA>
611612인천광역시 미추홀구 용현동 66-22 외 1필지(66-25)(8세대)100-000-2022 0039 22132022-01-26<NA>30244304032570<NA><NA><NA>
612613인천광역시 미추홀구 용현동 627-330 외 1필지(627-331) 공동주택(도시형 다세대주택) 신축공사(8세대)100-000-2022 0193 61422022-05-09<NA>30302704040350<NA><NA><NA>
613614인천광역시 미추홀구 용현동 127-12외 2필지 공동주택 신축공사2022 0000 00002022-07-04<NA>30310424041388<NA><NA><NA>
614615인천광역시 미추홀구 용현동 70-37 다세대주택 신축공사2022 0000 00002022-08-31<NA>29160193888023<NA><NA><NA>
615616인천광역시 미추홀구 용현동 118-23 외 1필지(12세대)100-000-2022 0360 98182022-08-22<NA>42557805674380<NA><NA><NA>
616617인천광역시 미추홀구 용현동 630-57 외 1필지(6세대)100-000-2022 0481 71922022-11-10<NA>24937603325010<NA><NA><NA>
617618인천광역시 미추홀구 용현동 628-48 공동주택(다세대주택)신축공사(8세대)100-000-2023 0029 31662023-01-19<NA>23246803099580<NA><NA><NA>
618619인천광역시 미추홀구 용현동 34-3 외 1필지(8세대)100-000-2023 0011 58722023-01-09<NA>30312304041640<NA><NA><NA>