Overview

Dataset statistics

Number of variables50
Number of observations10000
Missing cells122139
Missing cells (%)24.4%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory4.2 MiB
Average record size in memory441.0 B

Variable types

Numeric32
Text11
Categorical6
Unsupported1

Alerts

단지분류명 is highly imbalanced (82.8%)Imbalance
분양형태 is highly imbalanced (70.7%)Imbalance
관리방식 is highly imbalanced (84.9%)Imbalance
난방방식 is highly imbalanced (57.5%)Imbalance
도로명주소 has 867 (8.7%) missing valuesMissing
읍면동명 has 3345 (33.5%) missing valuesMissing
리명 has 9103 (91.0%) missing valuesMissing
충당금월부과금액 has 4933 (49.3%) missing valuesMissing
충당금액잔액 has 10000 (100.0%) missing valuesMissing
청소비용 has 4934 (49.3%) missing valuesMissing
경비원급여비용 has 4994 (49.9%) missing valuesMissing
난방공용비용 has 8278 (82.8%) missing valuesMissing
난방전용비용 has 8278 (82.8%) missing valuesMissing
수도공용비용 has 6296 (63.0%) missing valuesMissing
수도전용비용 has 6296 (63.0%) missing valuesMissing
전기공용비용 has 4935 (49.4%) missing valuesMissing
전기전용비용 has 4935 (49.4%) missing valuesMissing
건강보험요금 has 4939 (49.4%) missing valuesMissing
고용보험요금 has 4939 (49.4%) missing valuesMissing
국민연금금액 has 4939 (49.4%) missing valuesMissing
급여금액 has 4939 (49.4%) missing valuesMissing
기타급여금액 has 4939 (49.4%) missing valuesMissing
복지비용 has 4939 (49.4%) missing valuesMissing
산재보험요금 has 4939 (49.4%) missing valuesMissing
상여금액 has 4939 (49.4%) missing valuesMissing
퇴직금액 has 4939 (49.4%) missing valuesMissing
연면적 is highly skewed (γ1 = 45.94546654)Skewed
충당금액잔액 is an unsupported type, check if it needs cleaning or further analysisUnsupported
충당금월부과금액 has 664 (6.6%) zerosZeros
충당금월사용금액 has 5519 (55.2%) zerosZeros
135이상전용면적세대수 has 8624 (86.2%) zerosZeros
135이하전용면적세대수 has 6567 (65.7%) zerosZeros
60이하전용면적세대수 has 4420 (44.2%) zerosZeros
85이하전용면적세대수 has 3103 (31.0%) zerosZeros
난방공용비용 has 867 (8.7%) zerosZeros
난방전용비용 has 884 (8.8%) zerosZeros
수도공용비용 has 1386 (13.9%) zerosZeros
수도전용비용 has 179 (1.8%) zerosZeros
전기전용비용 has 428 (4.3%) zerosZeros
건강보험요금 has 188 (1.9%) zerosZeros
고용보험요금 has 202 (2.0%) zerosZeros
국민연금금액 has 297 (3.0%) zerosZeros
기타급여금액 has 153 (1.5%) zerosZeros
복지비용 has 273 (2.7%) zerosZeros
산재보험요금 has 194 (1.9%) zerosZeros
상여금액 has 4758 (47.6%) zerosZeros
퇴직금액 has 210 (2.1%) zerosZeros

Reproduction

Analysis started2024-05-03 18:53:51.840857
Analysis finished2024-05-03 18:53:58.800568
Duration6.96 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

발생년월
Real number (ℝ)

Distinct6
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean202325.39
Minimum202308
Maximum202401
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-05-03T18:53:58.954534image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum202308
5-th percentile202308
Q1202309
median202311
Q3202312
95-th percentile202401
Maximum202401
Range93
Interquartile range (IQR)3

Descriptive statistics

Standard deviation34.112007
Coefficient of variation (CV)0.00016859973
Kurtosis1.1151579
Mean202325.39
Median Absolute Deviation (MAD)1
Skewness1.7620789
Sum2.0232539 × 109
Variance1163.629
MonotonicityNot monotonic
2024-05-03T18:53:59.292082image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=6)
ValueCountFrequency (%)
202311 1722
17.2%
202401 1689
16.9%
202310 1675
16.8%
202309 1662
16.6%
202312 1656
16.6%
202308 1596
16.0%
ValueCountFrequency (%)
202308 1596
16.0%
202309 1662
16.6%
202310 1675
16.8%
202311 1722
17.2%
202312 1656
16.6%
202401 1689
16.9%
ValueCountFrequency (%)
202401 1689
16.9%
202312 1656
16.6%
202311 1722
17.2%
202310 1675
16.8%
202309 1662
16.6%
202308 1596
16.0%
Distinct4494
Distinct (%)45.1%
Missing26
Missing (%)0.3%
Memory size156.2 KiB
2024-05-03T18:53:59.800235image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length34
Median length22
Mean length8.9656106
Min length2

Characters and Unicode

Total characters89423
Distinct characters526
Distinct categories10 ?
Distinct scripts3 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1302 ?
Unique (%)13.1%

Sample

1st row양주현진에버빌1단지
2nd row금호1차
3rd row광주센트럴푸르지오
4th row광명두산위브트레지움
5th row김포전원마을월드2단지
ValueCountFrequency (%)
아파트 319
 
2.6%
e편한세상 72
 
0.6%
54
 
0.4%
2단지 45
 
0.4%
동탄2 45
 
0.4%
푸르지오 41
 
0.3%
lh 37
 
0.3%
동탄역 35
 
0.3%
힐스테이트 34
 
0.3%
1단지 23
 
0.2%
Other values (4776) 11641
94.3%
2024-05-03T18:54:00.787956image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
3424
 
3.8%
2879
 
3.2%
2876
 
3.2%
2665
 
3.0%
2602
 
2.9%
2502
 
2.8%
2220
 
2.5%
2035
 
2.3%
1591
 
1.8%
1454
 
1.6%
Other values (516) 65175
72.9%

Most occurring categories

ValueCountFrequency (%)
Other Letter 80111
89.6%
Decimal Number 4880
 
5.5%
Space Separator 2502
 
2.8%
Uppercase Letter 1246
 
1.4%
Lowercase Letter 310
 
0.3%
Close Punctuation 101
 
0.1%
Open Punctuation 101
 
0.1%
Dash Punctuation 98
 
0.1%
Other Punctuation 73
 
0.1%
Letter Number 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
3424
 
4.3%
2879
 
3.6%
2876
 
3.6%
2665
 
3.3%
2602
 
3.2%
2220
 
2.8%
2035
 
2.5%
1591
 
2.0%
1454
 
1.8%
1382
 
1.7%
Other values (460) 56983
71.1%
Uppercase Letter
ValueCountFrequency (%)
L 262
21.0%
H 243
19.5%
S 112
9.0%
C 104
 
8.3%
K 80
 
6.4%
I 46
 
3.7%
N 45
 
3.6%
G 41
 
3.3%
E 41
 
3.3%
F 36
 
2.9%
Other values (13) 236
18.9%
Lowercase Letter
ValueCountFrequency (%)
e 207
66.8%
c 21
 
6.8%
s 19
 
6.1%
h 13
 
4.2%
k 10
 
3.2%
l 9
 
2.9%
t 7
 
2.3%
j 4
 
1.3%
i 3
 
1.0%
d 3
 
1.0%
Other values (5) 14
 
4.5%
Decimal Number
ValueCountFrequency (%)
1 1432
29.3%
2 1339
27.4%
3 641
13.1%
5 357
 
7.3%
4 327
 
6.7%
6 242
 
5.0%
7 176
 
3.6%
0 130
 
2.7%
9 127
 
2.6%
8 109
 
2.2%
Other Punctuation
ValueCountFrequency (%)
, 49
67.1%
. 17
 
23.3%
& 7
 
9.6%
Space Separator
ValueCountFrequency (%)
2502
100.0%
Close Punctuation
ValueCountFrequency (%)
) 101
100.0%
Open Punctuation
ValueCountFrequency (%)
( 101
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 98
100.0%
Letter Number
ValueCountFrequency (%)
1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 80111
89.6%
Common 7755
 
8.7%
Latin 1557
 
1.7%

Most frequent character per script

Hangul
ValueCountFrequency (%)
3424
 
4.3%
2879
 
3.6%
2876
 
3.6%
2665
 
3.3%
2602
 
3.2%
2220
 
2.8%
2035
 
2.5%
1591
 
2.0%
1454
 
1.8%
1382
 
1.7%
Other values (460) 56983
71.1%
Latin
ValueCountFrequency (%)
L 262
16.8%
H 243
15.6%
e 207
13.3%
S 112
 
7.2%
C 104
 
6.7%
K 80
 
5.1%
I 46
 
3.0%
N 45
 
2.9%
G 41
 
2.6%
E 41
 
2.6%
Other values (29) 376
24.1%
Common
ValueCountFrequency (%)
2502
32.3%
1 1432
18.5%
2 1339
17.3%
3 641
 
8.3%
5 357
 
4.6%
4 327
 
4.2%
6 242
 
3.1%
7 176
 
2.3%
0 130
 
1.7%
9 127
 
1.6%
Other values (7) 482
 
6.2%

Most occurring blocks

ValueCountFrequency (%)
Hangul 80111
89.6%
ASCII 9311
 
10.4%
Number Forms 1
 
< 0.1%

Most frequent character per block

Hangul
ValueCountFrequency (%)
3424
 
4.3%
2879
 
3.6%
2876
 
3.6%
2665
 
3.3%
2602
 
3.2%
2220
 
2.8%
2035
 
2.5%
1591
 
2.0%
1454
 
1.8%
1382
 
1.7%
Other values (460) 56983
71.1%
ASCII
ValueCountFrequency (%)
2502
26.9%
1 1432
15.4%
2 1339
14.4%
3 641
 
6.9%
5 357
 
3.8%
4 327
 
3.5%
L 262
 
2.8%
H 243
 
2.6%
6 242
 
2.6%
e 207
 
2.2%
Other values (45) 1759
18.9%
Number Forms
ValueCountFrequency (%)
1
100.0%

단지분류명
Categorical

IMBALANCE 

Distinct7
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
아파트
9355 
주상복합
 
261
<NA>
 
134
도시형 생활주택(주상복합)
 
115
연립주택
 
101
Other values (2)
 
34

Length

Max length14
Median length3
Mean length3.2106
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
아파트 9355
93.5%
주상복합 261
 
2.6%
<NA> 134
 
1.3%
도시형 생활주택(주상복합) 115
 
1.1%
연립주택 101
 
1.0%
도시형 생활주택(아파트) 29
 
0.3%
도시형 생활주택(연립주택) 5
 
0.1%

Length

2024-05-03T18:54:01.197422image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-03T18:54:01.541856image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
아파트 9355
92.2%
주상복합 261
 
2.6%
도시형 149
 
1.5%
na 134
 
1.3%
생활주택(주상복합 115
 
1.1%
연립주택 101
 
1.0%
생활주택(아파트 29
 
0.3%
생활주택(연립주택 5
 
< 0.1%

단지전용면적합계
Real number (ℝ)

Distinct4505
Distinct (%)45.2%
Missing26
Missing (%)0.3%
Infinite0
Infinite (%)0.0%
Mean50819.107
Minimum2362.1424
Maximum462728.12
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-05-03T18:54:02.013320image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum2362.1424
5-th percentile12274.175
Q124803.907
median41855.765
Q364674.753
95-th percentile121649.84
Maximum462728.12
Range460365.98
Interquartile range (IQR)39870.846

Descriptive statistics

Standard deviation38875.424
Coefficient of variation (CV)0.76497654
Kurtosis9.9407942
Mean50819.107
Median Absolute Deviation (MAD)18929.536
Skewness2.4090865
Sum5.0686977 × 108
Variance1.5112986 × 109
MonotonicityNot monotonic
2024-05-03T18:54:02.383456image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
10759.5 7
 
0.1%
20662.17 6
 
0.1%
77846.9318 6
 
0.1%
22508.5476 6
 
0.1%
38689.75 6
 
0.1%
17596.8 6
 
0.1%
45543.64 6
 
0.1%
67606.025 6
 
0.1%
97915.52 6
 
0.1%
47660.22 6
 
0.1%
Other values (4495) 9913
99.1%
(Missing) 26
 
0.3%
ValueCountFrequency (%)
2362.1424 4
< 0.1%
2514.037 2
< 0.1%
2571.12 4
< 0.1%
2668.607 1
 
< 0.1%
2785.24 3
< 0.1%
2802.67 3
< 0.1%
2877.7997 1
 
< 0.1%
2912.09 1
 
< 0.1%
2954.12 2
< 0.1%
3007.32 2
< 0.1%
ValueCountFrequency (%)
462728.122 1
 
< 0.1%
365423.902 3
< 0.1%
359368.404 2
< 0.1%
317673.07 2
< 0.1%
314900.0415 1
 
< 0.1%
306846.684 1
 
< 0.1%
306296.22 3
< 0.1%
295055.36 3
< 0.1%
294076.9627 2
< 0.1%
287296.654 1
 
< 0.1%
Distinct4523
Distinct (%)45.2%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2024-05-03T18:54:03.074373image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length9
Median length9
Mean length9
Min length9

Characters and Unicode

Total characters90000
Distinct characters11
Distinct categories2 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1305 ?
Unique (%)13.1%

Sample

1st rowA48205009
2nd rowA47186010
3rd rowA10026301
4th rowA42374401
5th rowA41506009
ValueCountFrequency (%)
a48002003 6
 
0.1%
a41170309 6
 
0.1%
a44598804 6
 
0.1%
a10024992 6
 
0.1%
a41053001 6
 
0.1%
a10025955 6
 
0.1%
a46285003 6
 
0.1%
a10025645 6
 
0.1%
a42976007 6
 
0.1%
a48002014 6
 
0.1%
Other values (4513) 9940
99.4%
2024-05-03T18:54:03.893932image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 16605
18.4%
4 13033
14.5%
1 10866
12.1%
A 10000
11.1%
2 8963
10.0%
7 6810
7.6%
3 5949
 
6.6%
8 5206
 
5.8%
5 4751
 
5.3%
6 4679
 
5.2%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 80000
88.9%
Uppercase Letter 10000
 
11.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 16605
20.8%
4 13033
16.3%
1 10866
13.6%
2 8963
11.2%
7 6810
8.5%
3 5949
 
7.4%
8 5206
 
6.5%
5 4751
 
5.9%
6 4679
 
5.8%
9 3138
 
3.9%
Uppercase Letter
ValueCountFrequency (%)
A 10000
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 80000
88.9%
Latin 10000
 
11.1%

Most frequent character per script

Common
ValueCountFrequency (%)
0 16605
20.8%
4 13033
16.3%
1 10866
13.6%
2 8963
11.2%
7 6810
8.5%
3 5949
 
7.4%
8 5206
 
6.5%
5 4751
 
5.9%
6 4679
 
5.8%
9 3138
 
3.9%
Latin
ValueCountFrequency (%)
A 10000
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 90000
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 16605
18.4%
4 13033
14.5%
1 10866
12.1%
A 10000
11.1%
2 8963
10.0%
7 6810
7.6%
3 5949
 
6.6%
8 5206
 
5.8%
5 4751
 
5.3%
6 4679
 
5.2%

도로명주소
Text

MISSING 

Distinct4107
Distinct (%)45.0%
Missing867
Missing (%)8.7%
Memory size156.2 KiB
2024-05-03T18:54:04.497229image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length29
Median length26
Mean length18.432279
Min length13

Characters and Unicode

Total characters168342
Distinct characters351
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1177 ?
Unique (%)12.9%

Sample

1st row경기도 양주시 고덕로 160
2nd row경기도 구리시 장자대로 38
3rd row경기도 광주시 경충대로1461번길 43
4th row경기도 광명시 광덕산로 26
5th row경기도 김포시 전원로 44
ValueCountFrequency (%)
경기도 9133
 
22.7%
용인시 979
 
2.4%
고양시 778
 
1.9%
수원시 737
 
1.8%
화성시 683
 
1.7%
남양주시 595
 
1.5%
성남시 527
 
1.3%
평택시 507
 
1.3%
시흥시 470
 
1.2%
기흥구 421
 
1.0%
Other values (2904) 25325
63.1%
2024-05-03T18:54:05.576508image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
31022
18.4%
9715
 
5.8%
9646
 
5.7%
9422
 
5.6%
9245
 
5.5%
8719
 
5.2%
1 6717
 
4.0%
2 4338
 
2.6%
3923
 
2.3%
3 3351
 
2.0%
Other values (341) 72244
42.9%

Most occurring categories

ValueCountFrequency (%)
Other Letter 105410
62.6%
Space Separator 31022
 
18.4%
Decimal Number 30853
 
18.3%
Dash Punctuation 1057
 
0.6%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
9715
 
9.2%
9646
 
9.2%
9422
 
8.9%
9245
 
8.8%
8719
 
8.3%
3923
 
3.7%
3171
 
3.0%
2584
 
2.5%
2461
 
2.3%
1614
 
1.5%
Other values (329) 44910
42.6%
Decimal Number
ValueCountFrequency (%)
1 6717
21.8%
2 4338
14.1%
3 3351
10.9%
5 2765
9.0%
4 2590
 
8.4%
0 2535
 
8.2%
6 2429
 
7.9%
7 2383
 
7.7%
8 1962
 
6.4%
9 1783
 
5.8%
Space Separator
ValueCountFrequency (%)
31022
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 1057
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 105410
62.6%
Common 62932
37.4%

Most frequent character per script

Hangul
ValueCountFrequency (%)
9715
 
9.2%
9646
 
9.2%
9422
 
8.9%
9245
 
8.8%
8719
 
8.3%
3923
 
3.7%
3171
 
3.0%
2584
 
2.5%
2461
 
2.3%
1614
 
1.5%
Other values (329) 44910
42.6%
Common
ValueCountFrequency (%)
31022
49.3%
1 6717
 
10.7%
2 4338
 
6.9%
3 3351
 
5.3%
5 2765
 
4.4%
4 2590
 
4.1%
0 2535
 
4.0%
6 2429
 
3.9%
7 2383
 
3.8%
8 1962
 
3.1%
Other values (2) 2840
 
4.5%

Most occurring blocks

ValueCountFrequency (%)
Hangul 105410
62.6%
ASCII 62932
37.4%

Most frequent character per block

ASCII
ValueCountFrequency (%)
31022
49.3%
1 6717
 
10.7%
2 4338
 
6.9%
3 3351
 
5.3%
5 2765
 
4.4%
4 2590
 
4.1%
0 2535
 
4.0%
6 2429
 
3.9%
7 2383
 
3.8%
8 1962
 
3.1%
Other values (2) 2840
 
4.5%
Hangul
ValueCountFrequency (%)
9715
 
9.2%
9646
 
9.2%
9422
 
8.9%
9245
 
8.8%
8719
 
8.3%
3923
 
3.7%
3171
 
3.0%
2584
 
2.5%
2461
 
2.3%
1614
 
1.5%
Other values (329) 44910
42.6%
Distinct4524
Distinct (%)45.4%
Missing26
Missing (%)0.3%
Memory size156.2 KiB
2024-05-03T18:54:06.166451image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length54
Median length42
Mean length27.252356
Min length18

Characters and Unicode

Total characters271815
Distinct characters543
Distinct categories10 ?
Distinct scripts3 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1316 ?
Unique (%)13.2%

Sample

1st row경기도 양주시 덕계동 855 양주현진에버빌1단지
2nd row경기도 구리시 교문동 820 금호1차
3rd row경기도 광주시 쌍령동 503 광주센트럴푸르지오
4th row경기도 광명시 하안동 863 광명두산위브트레지움
5th row경기도 김포시 운양동 1435 김포전원마을월드2단지
ValueCountFrequency (%)
경기도 9974
 
18.7%
화성시 756
 
1.4%
남양주시 607
 
1.1%
평택시 519
 
1.0%
시흥시 496
 
0.9%
의정부시 441
 
0.8%
용인기흥구 425
 
0.8%
용인수지구 415
 
0.8%
김포시 401
 
0.8%
성남분당구 374
 
0.7%
Other values (8045) 38986
73.0%
2024-05-03T18:54:07.001659image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
43742
 
16.1%
10930
 
4.0%
10590
 
3.9%
10587
 
3.9%
10228
 
3.8%
1 7976
 
2.9%
7615
 
2.8%
2 4890
 
1.8%
4628
 
1.7%
4084
 
1.5%
Other values (533) 156545
57.6%

Most occurring categories

ValueCountFrequency (%)
Other Letter 184153
67.7%
Space Separator 43742
 
16.1%
Decimal Number 39082
 
14.4%
Dash Punctuation 3006
 
1.1%
Uppercase Letter 1246
 
0.5%
Lowercase Letter 310
 
0.1%
Close Punctuation 101
 
< 0.1%
Open Punctuation 101
 
< 0.1%
Other Punctuation 73
 
< 0.1%
Letter Number 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
10930
 
5.9%
10590
 
5.8%
10587
 
5.7%
10228
 
5.6%
7615
 
4.1%
4628
 
2.5%
4084
 
2.2%
3585
 
1.9%
2950
 
1.6%
2926
 
1.6%
Other values (477) 116030
63.0%
Uppercase Letter
ValueCountFrequency (%)
L 262
21.0%
H 243
19.5%
S 112
9.0%
C 104
 
8.3%
K 80
 
6.4%
I 46
 
3.7%
N 45
 
3.6%
E 41
 
3.3%
G 41
 
3.3%
F 36
 
2.9%
Other values (13) 236
18.9%
Lowercase Letter
ValueCountFrequency (%)
e 207
66.8%
c 21
 
6.8%
s 19
 
6.1%
h 13
 
4.2%
k 10
 
3.2%
l 9
 
2.9%
t 7
 
2.3%
j 4
 
1.3%
i 3
 
1.0%
a 3
 
1.0%
Other values (5) 14
 
4.5%
Decimal Number
ValueCountFrequency (%)
1 7976
20.4%
2 4890
12.5%
5 3738
9.6%
3 3581
9.2%
6 3562
9.1%
7 3251
8.3%
4 3195
8.2%
8 3132
 
8.0%
0 3014
 
7.7%
9 2743
 
7.0%
Other Punctuation
ValueCountFrequency (%)
, 49
67.1%
. 17
 
23.3%
& 7
 
9.6%
Space Separator
ValueCountFrequency (%)
43742
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 3006
100.0%
Close Punctuation
ValueCountFrequency (%)
) 101
100.0%
Open Punctuation
ValueCountFrequency (%)
( 101
100.0%
Letter Number
ValueCountFrequency (%)
1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 184153
67.7%
Common 86105
31.7%
Latin 1557
 
0.6%

Most frequent character per script

Hangul
ValueCountFrequency (%)
10930
 
5.9%
10590
 
5.8%
10587
 
5.7%
10228
 
5.6%
7615
 
4.1%
4628
 
2.5%
4084
 
2.2%
3585
 
1.9%
2950
 
1.6%
2926
 
1.6%
Other values (477) 116030
63.0%
Latin
ValueCountFrequency (%)
L 262
16.8%
H 243
15.6%
e 207
13.3%
S 112
 
7.2%
C 104
 
6.7%
K 80
 
5.1%
I 46
 
3.0%
N 45
 
2.9%
E 41
 
2.6%
G 41
 
2.6%
Other values (29) 376
24.1%
Common
ValueCountFrequency (%)
43742
50.8%
1 7976
 
9.3%
2 4890
 
5.7%
5 3738
 
4.3%
3 3581
 
4.2%
6 3562
 
4.1%
7 3251
 
3.8%
4 3195
 
3.7%
8 3132
 
3.6%
0 3014
 
3.5%
Other values (7) 6024
 
7.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 184153
67.7%
ASCII 87661
32.3%
Number Forms 1
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
43742
49.9%
1 7976
 
9.1%
2 4890
 
5.6%
5 3738
 
4.3%
3 3581
 
4.1%
6 3562
 
4.1%
7 3251
 
3.7%
4 3195
 
3.6%
8 3132
 
3.6%
0 3014
 
3.4%
Other values (45) 7580
 
8.6%
Hangul
ValueCountFrequency (%)
10930
 
5.9%
10590
 
5.8%
10587
 
5.7%
10228
 
5.6%
7615
 
4.1%
4628
 
2.5%
4084
 
2.2%
3585
 
1.9%
2950
 
1.6%
2926
 
1.6%
Other values (477) 116030
63.0%
Number Forms
ValueCountFrequency (%)
1
100.0%

법정동코드
Real number (ℝ)

Distinct555
Distinct (%)5.6%
Missing26
Missing (%)0.3%
Infinite0
Infinite (%)0.0%
Mean4.1358064 × 109
Minimum4.1111129 × 109
Maximum4.18304 × 109
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-05-03T18:54:07.415280image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum4.1111129 × 109
5-th percentile4.1115141 × 109
Q14.1194105 × 109
median4.1360256 × 109
Q34.1480102 × 109
95-th percentile4.1610259 × 109
Maximum4.18304 × 109
Range71927124
Interquartile range (IQR)28599675

Descriptive statistics

Standard deviation17077203
Coefficient of variation (CV)0.0041291108
Kurtosis-0.98674366
Mean4.1358064 × 109
Median Absolute Deviation (MAD)14013622
Skewness0.21022688
Sum4.1250533 × 1013
Variance2.9163085 × 1014
MonotonicityNot monotonic
2024-05-03T18:54:07.869029image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
4139013200 130
 
1.3%
4146510200 111
 
1.1%
4128710100 101
 
1.0%
4136011200 100
 
1.0%
4146510700 100
 
1.0%
4119210900 97
 
1.0%
4119210800 97
 
1.0%
4117310400 96
 
1.0%
4115010200 92
 
0.9%
4128112800 89
 
0.9%
Other values (545) 8961
89.6%
ValueCountFrequency (%)
4111112900 3
 
< 0.1%
4111113000 69
0.7%
4111113100 3
 
< 0.1%
4111113200 25
 
0.2%
4111113300 17
 
0.2%
4111113400 2
 
< 0.1%
4111113500 13
 
0.1%
4111113600 12
 
0.1%
4111113700 5
 
0.1%
4111312600 23
 
0.2%
ValueCountFrequency (%)
4183040024 2
 
< 0.1%
4183033021 1
 
< 0.1%
4183031021 5
 
0.1%
4183025032 5
 
0.1%
4183025026 5
 
0.1%
4183025025 3
 
< 0.1%
4183025021 18
0.2%
4182032521 12
0.1%
4182031022 1
 
< 0.1%
4182025022 6
 
0.1%

복도유형
Categorical

Distinct5
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
계단식
7158 
복도식
1395 
혼합식
1356 
타워형
 
65
<NA>
 
26

Length

Max length4
Median length3
Mean length3.0026
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
계단식 7158
71.6%
복도식 1395
 
14.0%
혼합식 1356
 
13.6%
타워형 65
 
0.7%
<NA> 26
 
0.3%

Length

2024-05-03T18:54:08.260919image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-03T18:54:08.589025image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
계단식 7158
71.6%
복도식 1395
 
14.0%
혼합식 1356
 
13.6%
타워형 65
 
0.7%
na 26
 
0.3%

분양형태
Categorical

IMBALANCE 

Distinct5
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
분양
8690 
임대
1029 
혼합
 
237
<NA>
 
26
사택 및 관사 등
 
18

Length

Max length9
Median length2
Mean length2.0178
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
분양 8690
86.9%
임대 1029
 
10.3%
혼합 237
 
2.4%
<NA> 26
 
0.3%
사택 및 관사 등 18
 
0.2%

Length

2024-05-03T18:54:09.117704image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-03T18:54:09.467419image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
분양 8690
86.4%
임대 1029
 
10.2%
혼합 237
 
2.4%
na 26
 
0.3%
사택 18
 
0.2%
18
 
0.2%
관사 18
 
0.2%
18
 
0.2%

사용승인일
Real number (ℝ)

Distinct3108
Distinct (%)31.2%
Missing26
Missing (%)0.3%
Infinite0
Infinite (%)0.0%
Mean20061511
Minimum19781109
Maximum20240115
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-05-03T18:54:09.868491image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum19781109
5-th percentile19921009
Q119980717
median20051109
Q320151030
95-th percentile20211102
Maximum20240115
Range459006
Interquartile range (IQR)170312.75

Descriptive statistics

Standard deviation97197.467
Coefficient of variation (CV)0.0048449723
Kurtosis-1.0608727
Mean20061511
Median Absolute Deviation (MAD)80207
Skewness0.065779309
Sum2.0009351 × 1011
Variance9.4473476 × 109
MonotonicityNot monotonic
2024-05-03T18:54:10.384095image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
20161031 19
 
0.2%
20180627 18
 
0.2%
19941028 18
 
0.2%
19960228 18
 
0.2%
20060227 18
 
0.2%
20040630 17
 
0.2%
19991029 17
 
0.2%
20030627 16
 
0.2%
20190628 15
 
0.1%
20221229 13
 
0.1%
Other values (3098) 9805
98.0%
(Missing) 26
 
0.3%
ValueCountFrequency (%)
19781109 2
 
< 0.1%
19790515 4
< 0.1%
19790530 3
< 0.1%
19790920 2
 
< 0.1%
19800123 1
 
< 0.1%
19800429 1
 
< 0.1%
19821116 3
< 0.1%
19821220 2
 
< 0.1%
19830724 3
< 0.1%
19830808 5
0.1%
ValueCountFrequency (%)
20240115 1
< 0.1%
20240102 1
< 0.1%
20231220 1
< 0.1%
20231219 1
< 0.1%
20231213 1
< 0.1%
20231211 1
< 0.1%
20231208 1
< 0.1%
20231130 1
< 0.1%
20231129 2
< 0.1%
20231127 1
< 0.1%

세대수
Real number (ℝ)

Distinct1334
Distinct (%)13.4%
Missing26
Missing (%)0.3%
Infinite0
Infinite (%)0.0%
Mean662.74614
Minimum104
Maximum5282
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-05-03T18:54:10.882499image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum104
5-th percentile186
Q1332
median539
Q3848
95-th percentile1568
Maximum5282
Range5178
Interquartile range (IQR)516

Descriptive statistics

Standard deviation470.27298
Coefficient of variation (CV)0.70958237
Kurtosis8.0521577
Mean662.74614
Median Absolute Deviation (MAD)241
Skewness2.1659796
Sum6610230
Variance221156.67
MonotonicityNot monotonic
2024-05-03T18:54:11.379763image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
299 96
 
1.0%
168 52
 
0.5%
498 51
 
0.5%
298 51
 
0.5%
420 50
 
0.5%
180 46
 
0.5%
330 42
 
0.4%
390 37
 
0.4%
200 37
 
0.4%
600 36
 
0.4%
Other values (1324) 9476
94.8%
ValueCountFrequency (%)
104 3
 
< 0.1%
114 1
 
< 0.1%
120 3
 
< 0.1%
124 1
 
< 0.1%
140 3
 
< 0.1%
144 3
 
< 0.1%
148 1
 
< 0.1%
150 24
0.2%
151 3
 
< 0.1%
152 22
0.2%
ValueCountFrequency (%)
5282 1
 
< 0.1%
4250 2
< 0.1%
4089 3
< 0.1%
4086 3
< 0.1%
3850 3
< 0.1%
3806 3
< 0.1%
3728 1
 
< 0.1%
3724 1
 
< 0.1%
3603 1
 
< 0.1%
3498 1
 
< 0.1%
Distinct1828
Distinct (%)18.3%
Missing26
Missing (%)0.3%
Memory size156.2 KiB
2024-05-03T18:54:12.136612image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length60
Median length48
Mean length6.1433728
Min length1

Characters and Unicode

Total characters61274
Distinct characters348
Distinct categories11 ?
Distinct scripts4 ?
Distinct blocks4 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique388 ?
Unique (%)3.9%

Sample

1st row(주)현진
2nd row금호
3rd row대우건설
4th row두산건설
5th row월드건설(주)
ValueCountFrequency (%)
대우건설 203
 
1.9%
현대건설 194
 
1.8%
대한주택공사 169
 
1.6%
현대산업개발 156
 
1.5%
gs건설 149
 
1.4%
주)대우건설 100
 
0.9%
금호건설 93
 
0.9%
현대산업개발(주 90
 
0.8%
롯데건설 88
 
0.8%
대림산업(주 85
 
0.8%
Other values (1721) 9282
87.5%
2024-05-03T18:54:13.434514image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
6674
 
10.9%
6063
 
9.9%
5343
 
8.7%
) 4256
 
6.9%
( 4210
 
6.9%
1879
 
3.1%
1468
 
2.4%
1325
 
2.2%
1152
 
1.9%
981
 
1.6%
Other values (338) 27923
45.6%

Most occurring categories

ValueCountFrequency (%)
Other Letter 49867
81.4%
Close Punctuation 4256
 
6.9%
Open Punctuation 4210
 
6.9%
Uppercase Letter 1184
 
1.9%
Other Punctuation 758
 
1.2%
Space Separator 667
 
1.1%
Lowercase Letter 188
 
0.3%
Decimal Number 125
 
0.2%
Dash Punctuation 12
 
< 0.1%
Other Symbol 6
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
6674
 
13.4%
6063
 
12.2%
5343
 
10.7%
1879
 
3.8%
1468
 
2.9%
1325
 
2.7%
1152
 
2.3%
981
 
2.0%
981
 
2.0%
913
 
1.8%
Other values (285) 23088
46.3%
Uppercase Letter
ValueCountFrequency (%)
G 283
23.9%
S 255
21.5%
L 196
16.6%
H 99
 
8.4%
K 86
 
7.3%
C 83
 
7.0%
I 34
 
2.9%
D 31
 
2.6%
E 28
 
2.4%
T 19
 
1.6%
Other values (11) 70
 
5.9%
Lowercase Letter
ValueCountFrequency (%)
c 51
27.1%
k 44
23.4%
s 34
18.1%
g 16
 
8.5%
l 13
 
6.9%
h 11
 
5.9%
n 4
 
2.1%
j 4
 
2.1%
e 3
 
1.6%
d 2
 
1.1%
Other values (3) 6
 
3.2%
Decimal Number
ValueCountFrequency (%)
1 42
33.6%
2 36
28.8%
0 22
17.6%
3 10
 
8.0%
7 6
 
4.8%
5 5
 
4.0%
9 3
 
2.4%
4 1
 
0.8%
Other Punctuation
ValueCountFrequency (%)
, 580
76.5%
. 92
 
12.1%
/ 52
 
6.9%
& 27
 
3.6%
: 7
 
0.9%
Close Punctuation
ValueCountFrequency (%)
) 4256
100.0%
Open Punctuation
ValueCountFrequency (%)
( 4210
100.0%
Space Separator
ValueCountFrequency (%)
667
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 12
100.0%
Other Symbol
ValueCountFrequency (%)
6
100.0%
Math Symbol
ValueCountFrequency (%)
+ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 49872
81.4%
Common 10029
 
16.4%
Latin 1372
 
2.2%
Han 1
 
< 0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
6674
 
13.4%
6063
 
12.2%
5343
 
10.7%
1879
 
3.8%
1468
 
2.9%
1325
 
2.7%
1152
 
2.3%
981
 
2.0%
981
 
2.0%
913
 
1.8%
Other values (285) 23093
46.3%
Latin
ValueCountFrequency (%)
G 283
20.6%
S 255
18.6%
L 196
14.3%
H 99
 
7.2%
K 86
 
6.3%
C 83
 
6.0%
c 51
 
3.7%
k 44
 
3.2%
I 34
 
2.5%
s 34
 
2.5%
Other values (24) 207
15.1%
Common
ValueCountFrequency (%)
) 4256
42.4%
( 4210
42.0%
667
 
6.7%
, 580
 
5.8%
. 92
 
0.9%
/ 52
 
0.5%
1 42
 
0.4%
2 36
 
0.4%
& 27
 
0.3%
0 22
 
0.2%
Other values (8) 45
 
0.4%
Han
ValueCountFrequency (%)
1
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 49866
81.4%
ASCII 11401
 
18.6%
None 6
 
< 0.1%
CJK 1
 
< 0.1%

Most frequent character per block

Hangul
ValueCountFrequency (%)
6674
 
13.4%
6063
 
12.2%
5343
 
10.7%
1879
 
3.8%
1468
 
2.9%
1325
 
2.7%
1152
 
2.3%
981
 
2.0%
981
 
2.0%
913
 
1.8%
Other values (284) 23087
46.3%
ASCII
ValueCountFrequency (%)
) 4256
37.3%
( 4210
36.9%
667
 
5.9%
, 580
 
5.1%
G 283
 
2.5%
S 255
 
2.2%
L 196
 
1.7%
H 99
 
0.9%
. 92
 
0.8%
K 86
 
0.8%
Other values (42) 677
 
5.9%
None
ValueCountFrequency (%)
6
100.0%
CJK
ValueCountFrequency (%)
1
100.0%

시군구명
Categorical

Distinct45
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
<NA>
3345 
화성시
528 
남양주시
 
404
평택시
 
342
시흥시
 
325
Other values (40)
5056 

Length

Max length6
Median length5
Mean length4.0276
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row양주시
2nd row<NA>
3rd row광주시
4th row광명시
5th row<NA>

Common Values

ValueCountFrequency (%)
<NA> 3345
33.5%
화성시 528
 
5.3%
남양주시 404
 
4.0%
평택시 342
 
3.4%
시흥시 325
 
3.2%
용인기흥구 293
 
2.9%
의정부시 279
 
2.8%
용인수지구 276
 
2.8%
김포시 270
 
2.7%
성남분당구 255
 
2.5%
Other values (35) 3683
36.8%

Length

2024-05-03T18:54:14.180212image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
na 3345
33.5%
화성시 528
 
5.3%
남양주시 404
 
4.0%
평택시 342
 
3.4%
시흥시 325
 
3.2%
용인기흥구 293
 
2.9%
의정부시 279
 
2.8%
용인수지구 276
 
2.8%
김포시 270
 
2.7%
성남분당구 255
 
2.5%
Other values (35) 3683
36.8%

읍면동명
Text

MISSING 

Distinct434
Distinct (%)6.5%
Missing3345
Missing (%)33.5%
Memory size156.2 KiB
2024-05-03T18:54:14.989670image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length5
Median length3
Mean length2.9767092
Min length2

Characters and Unicode

Total characters19810
Distinct characters217
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

Unique32 ?
Unique (%)0.5%

Sample

1st row덕계동
2nd row쌍령동
3rd row하안동
4th row초월읍
5th row역북동
ValueCountFrequency (%)
중동 98
 
1.5%
정자동 86
 
1.3%
정왕동 83
 
1.2%
봉담읍 73
 
1.1%
죽전동 71
 
1.1%
다산동 70
 
1.1%
상동 70
 
1.1%
일산동 65
 
1.0%
상현동 64
 
1.0%
호계동 62
 
0.9%
Other values (424) 5913
88.9%
2024-05-03T18:54:16.687085image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
5964
30.1%
805
 
4.1%
508
 
2.6%
426
 
2.2%
288
 
1.5%
267
 
1.3%
259
 
1.3%
245
 
1.2%
228
 
1.2%
204
 
1.0%
Other values (207) 10616
53.6%

Most occurring categories

ValueCountFrequency (%)
Other Letter 19808
> 99.9%
Decimal Number 2
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
5964
30.1%
805
 
4.1%
508
 
2.6%
426
 
2.2%
288
 
1.5%
267
 
1.3%
259
 
1.3%
245
 
1.2%
228
 
1.2%
204
 
1.0%
Other values (206) 10614
53.6%
Decimal Number
ValueCountFrequency (%)
2 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 19808
> 99.9%
Common 2
 
< 0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
5964
30.1%
805
 
4.1%
508
 
2.6%
426
 
2.2%
288
 
1.5%
267
 
1.3%
259
 
1.3%
245
 
1.2%
228
 
1.2%
204
 
1.0%
Other values (206) 10614
53.6%
Common
ValueCountFrequency (%)
2 2
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 19808
> 99.9%
ASCII 2
 
< 0.1%

Most frequent character per block

Hangul
ValueCountFrequency (%)
5964
30.1%
805
 
4.1%
508
 
2.6%
426
 
2.2%
288
 
1.5%
267
 
1.3%
259
 
1.3%
245
 
1.2%
228
 
1.2%
204
 
1.0%
Other values (206) 10614
53.6%
ASCII
ValueCountFrequency (%)
2 2
100.0%

리명
Text

MISSING 

Distinct152
Distinct (%)16.9%
Missing9103
Missing (%)91.0%
Memory size156.2 KiB
2024-05-03T18:54:17.478358image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length4
Median length3
Mean length3.0345596
Min length2

Characters and Unicode

Total characters2722
Distinct characters132
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

Unique44 ?
Unique (%)4.9%

Sample

1st row쌍동리
2nd row마정리
3rd row봉일천리
4th row상리
5th row송화리
ValueCountFrequency (%)
남양리 27
 
3.0%
퇴계원리 24
 
2.7%
덕소리 24
 
2.7%
오남리 23
 
2.6%
도곡리 22
 
2.5%
수영리 20
 
2.2%
행정리 20
 
2.2%
신곡리 20
 
2.2%
상리 19
 
2.1%
현화리 19
 
2.1%
Other values (142) 679
75.7%
2024-05-03T18:54:18.495985image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
897
33.0%
100
 
3.7%
82
 
3.0%
68
 
2.5%
59
 
2.2%
55
 
2.0%
50
 
1.8%
47
 
1.7%
46
 
1.7%
46
 
1.7%
Other values (122) 1272
46.7%

Most occurring categories

ValueCountFrequency (%)
Other Letter 2722
100.0%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
897
33.0%
100
 
3.7%
82
 
3.0%
68
 
2.5%
59
 
2.2%
55
 
2.0%
50
 
1.8%
47
 
1.7%
46
 
1.7%
46
 
1.7%
Other values (122) 1272
46.7%

Most occurring scripts

ValueCountFrequency (%)
Hangul 2722
100.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
897
33.0%
100
 
3.7%
82
 
3.0%
68
 
2.5%
59
 
2.2%
55
 
2.0%
50
 
1.8%
47
 
1.7%
46
 
1.7%
46
 
1.7%
Other values (122) 1272
46.7%

Most occurring blocks

ValueCountFrequency (%)
Hangul 2722
100.0%

Most frequent character per block

Hangul
ValueCountFrequency (%)
897
33.0%
100
 
3.7%
82
 
3.0%
68
 
2.5%
59
 
2.2%
55
 
2.0%
50
 
1.8%
47
 
1.7%
46
 
1.7%
46
 
1.7%
Other values (122) 1272
46.7%
Distinct2457
Distinct (%)24.6%
Missing26
Missing (%)0.3%
Memory size156.2 KiB
2024-05-03T18:54:19.093975image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length32
Median length28
Mean length7.1698416
Min length1

Characters and Unicode

Total characters71512
Distinct characters491
Distinct categories10 ?
Distinct scripts3 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique569 ?
Unique (%)5.7%

Sample

1st row(주)ks건설
2nd row군인공제회
3rd row쌍령피에프브이(주)
4th row하안주공 본2단지 재건축조합
5th row월드건설(주)
ValueCountFrequency (%)
한국토지주택공사 647
 
5.9%
lh 331
 
3.0%
대한주택공사 282
 
2.6%
lh공사 108
 
1.0%
주식회사 97
 
0.9%
현대산업개발 88
 
0.8%
한국토지신탁 79
 
0.7%
현대건설 74
 
0.7%
61
 
0.6%
현대산업개발(주 53
 
0.5%
Other values (2500) 9143
83.4%
2024-05-03T18:54:20.293553image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
6299
 
8.8%
4009
 
5.6%
) 3781
 
5.3%
( 3751
 
5.2%
3268
 
4.6%
2053
 
2.9%
2024
 
2.8%
1906
 
2.7%
1857
 
2.6%
1407
 
2.0%
Other values (481) 41157
57.6%

Most occurring categories

ValueCountFrequency (%)
Other Letter 59849
83.7%
Close Punctuation 3783
 
5.3%
Open Punctuation 3753
 
5.2%
Uppercase Letter 1645
 
2.3%
Space Separator 1025
 
1.4%
Other Punctuation 669
 
0.9%
Decimal Number 530
 
0.7%
Lowercase Letter 229
 
0.3%
Dash Punctuation 27
 
< 0.1%
Other Symbol 2
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
6299
 
10.5%
4009
 
6.7%
3268
 
5.5%
2053
 
3.4%
2024
 
3.4%
1906
 
3.2%
1857
 
3.1%
1407
 
2.4%
1402
 
2.3%
1332
 
2.2%
Other values (413) 34292
57.3%
Uppercase Letter
ValueCountFrequency (%)
H 536
32.6%
L 527
32.0%
S 76
 
4.6%
G 75
 
4.6%
C 67
 
4.1%
N 55
 
3.3%
F 53
 
3.2%
D 50
 
3.0%
K 44
 
2.7%
M 30
 
1.8%
Other values (13) 132
 
8.0%
Lowercase Letter
ValueCountFrequency (%)
l 50
21.8%
h 48
21.0%
k 26
11.4%
s 17
 
7.4%
b 13
 
5.7%
e 13
 
5.7%
c 11
 
4.8%
d 8
 
3.5%
p 7
 
3.1%
o 7
 
3.1%
Other values (10) 29
12.7%
Decimal Number
ValueCountFrequency (%)
1 185
34.9%
2 126
23.8%
3 66
 
12.5%
4 34
 
6.4%
6 32
 
6.0%
8 23
 
4.3%
0 22
 
4.2%
5 21
 
4.0%
9 12
 
2.3%
7 9
 
1.7%
Other Punctuation
ValueCountFrequency (%)
, 466
69.7%
. 102
 
15.2%
/ 55
 
8.2%
& 29
 
4.3%
* 8
 
1.2%
? 4
 
0.6%
' 3
 
0.4%
; 2
 
0.3%
Close Punctuation
ValueCountFrequency (%)
) 3781
99.9%
] 2
 
0.1%
Open Punctuation
ValueCountFrequency (%)
( 3751
99.9%
[ 2
 
0.1%
Space Separator
ValueCountFrequency (%)
1025
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 27
100.0%
Other Symbol
ValueCountFrequency (%)
2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 59851
83.7%
Common 9787
 
13.7%
Latin 1874
 
2.6%

Most frequent character per script

Hangul
ValueCountFrequency (%)
6299
 
10.5%
4009
 
6.7%
3268
 
5.5%
2053
 
3.4%
2024
 
3.4%
1906
 
3.2%
1857
 
3.1%
1407
 
2.4%
1402
 
2.3%
1332
 
2.2%
Other values (414) 34294
57.3%
Latin
ValueCountFrequency (%)
H 536
28.6%
L 527
28.1%
S 76
 
4.1%
G 75
 
4.0%
C 67
 
3.6%
N 55
 
2.9%
F 53
 
2.8%
D 50
 
2.7%
l 50
 
2.7%
h 48
 
2.6%
Other values (33) 337
18.0%
Common
ValueCountFrequency (%)
) 3781
38.6%
( 3751
38.3%
1025
 
10.5%
, 466
 
4.8%
1 185
 
1.9%
2 126
 
1.3%
. 102
 
1.0%
3 66
 
0.7%
/ 55
 
0.6%
4 34
 
0.3%
Other values (14) 196
 
2.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 59849
83.7%
ASCII 11661
 
16.3%
None 2
 
< 0.1%

Most frequent character per block

Hangul
ValueCountFrequency (%)
6299
 
10.5%
4009
 
6.7%
3268
 
5.5%
2053
 
3.4%
2024
 
3.4%
1906
 
3.2%
1857
 
3.1%
1407
 
2.4%
1402
 
2.3%
1332
 
2.2%
Other values (413) 34292
57.3%
ASCII
ValueCountFrequency (%)
) 3781
32.4%
( 3751
32.2%
1025
 
8.8%
H 536
 
4.6%
L 527
 
4.5%
, 466
 
4.0%
1 185
 
1.6%
2 126
 
1.1%
. 102
 
0.9%
S 76
 
0.7%
Other values (57) 1086
 
9.3%
None
ValueCountFrequency (%)
2
100.0%

연면적
Real number (ℝ)

SKEWED 

Distinct4514
Distinct (%)45.3%
Missing26
Missing (%)0.3%
Infinite0
Infinite (%)0.0%
Mean758458.78
Minimum4928
Maximum1.237596 × 109
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-05-03T18:54:20.688771image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum4928
5-th percentile20023.975
Q140531.07
median68899.34
Q3109887.04
95-th percentile215876.3
Maximum1.237596 × 109
Range1.2375911 × 109
Interquartile range (IQR)69355.97

Descriptive statistics

Standard deviation25708563
Coefficient of variation (CV)33.895794
Kurtosis2174.2569
Mean758458.78
Median Absolute Deviation (MAD)32115.278
Skewness45.945467
Sum7.5648679 × 109
Variance6.6093019 × 1014
MonotonicityNot monotonic
2024-05-03T18:54:21.224450image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
110940.465 6
 
0.1%
36138.37 6
 
0.1%
65003.417 6
 
0.1%
172254.688 6
 
0.1%
28993.0 6
 
0.1%
66989.0 6
 
0.1%
145827.6125 6
 
0.1%
81721.9671 6
 
0.1%
42564.83 6
 
0.1%
28752.19 6
 
0.1%
Other values (4504) 9914
99.1%
(Missing) 26
 
0.3%
ValueCountFrequency (%)
4928.0 1
 
< 0.1%
4947.92 4
< 0.1%
4990.8 4
< 0.1%
5383.3546 2
< 0.1%
5656.813 2
< 0.1%
5772.58 2
< 0.1%
5971.0653 4
< 0.1%
6021.15 3
< 0.1%
6038.34 2
< 0.1%
6346.925 1
 
< 0.1%
ValueCountFrequency (%)
1237596000.0 4
< 0.1%
584686914.0 1
 
< 0.1%
166167204.0 3
< 0.1%
85273774.0 3
< 0.1%
75674541.0 2
< 0.1%
59518900.0 1
 
< 0.1%
49489124.0 1
 
< 0.1%
46116713.0 1
 
< 0.1%
45030888.0 2
< 0.1%
18991884.0 1
 
< 0.1%

충당금월부과금액
Real number (ℝ)

MISSING  ZEROS 

Distinct3239
Distinct (%)63.9%
Missing4933
Missing (%)49.3%
Infinite0
Infinite (%)0.0%
Mean13437366
Minimum0
Maximum1.3656695 × 108
Zeros664
Zeros (%)6.6%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-05-03T18:54:21.676543image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q14529205
median9975280
Q318129925
95-th percentile39739743
Maximum1.3656695 × 108
Range1.3656695 × 108
Interquartile range (IQR)13600720

Descriptive statistics

Standard deviation13879320
Coefficient of variation (CV)1.0328899
Kurtosis11.311138
Mean13437366
Median Absolute Deviation (MAD)6494720
Skewness2.5464496
Sum6.8087133 × 1010
Variance1.9263553 × 1014
MonotonicityNot monotonic
2024-05-03T18:54:22.270035image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 664
 
6.6%
8731460 4
 
< 0.1%
23400000 4
 
< 0.1%
10800000 4
 
< 0.1%
7897560 3
 
< 0.1%
51055860 3
 
< 0.1%
2400000 3
 
< 0.1%
4005000 3
 
< 0.1%
6929460 3
 
< 0.1%
14466690 3
 
< 0.1%
Other values (3229) 4373
43.7%
(Missing) 4933
49.3%
ValueCountFrequency (%)
0 664
6.6%
308390 1
 
< 0.1%
353320 2
 
< 0.1%
378070 2
 
< 0.1%
381350 2
 
< 0.1%
428400 1
 
< 0.1%
564360 2
 
< 0.1%
620110 1
 
< 0.1%
661190 2
 
< 0.1%
662800 1
 
< 0.1%
ValueCountFrequency (%)
136566950 3
< 0.1%
129225681 1
 
< 0.1%
119713280 1
 
< 0.1%
113399480 1
 
< 0.1%
111831740 1
 
< 0.1%
107355626 1
 
< 0.1%
99266050 2
< 0.1%
97894050 2
< 0.1%
97563520 1
 
< 0.1%
96253890 1
 
< 0.1%

충당금월사용금액
Real number (ℝ)

ZEROS 

Distinct3358
Distinct (%)33.6%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean14277655
Minimum-29921400
Maximum1.66077 × 109
Zeros5519
Zeros (%)55.2%
Negative4
Negative (%)< 0.1%
Memory size166.0 KiB
2024-05-03T18:54:22.925225image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum-29921400
5-th percentile0
Q10
median0
Q33669750
95-th percentile87345500
Maximum1.66077 × 109
Range1.6906914 × 109
Interquartile range (IQR)3669750

Descriptive statistics

Standard deviation53795480
Coefficient of variation (CV)3.7678094
Kurtosis141.67257
Mean14277655
Median Absolute Deviation (MAD)0
Skewness8.7230657
Sum1.4277655 × 1011
Variance2.8939537 × 1015
MonotonicityNot monotonic
2024-05-03T18:54:23.435546image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 5519
55.2%
660000 24
 
0.2%
1650000 22
 
0.2%
1100000 22
 
0.2%
550000 20
 
0.2%
330000 20
 
0.2%
440000 19
 
0.2%
770000 19
 
0.2%
1320000 19
 
0.2%
5500000 16
 
0.2%
Other values (3348) 4300
43.0%
ValueCountFrequency (%)
-29921400 1
 
< 0.1%
-25201000 1
 
< 0.1%
-15290000 1
 
< 0.1%
-1430000 1
 
< 0.1%
0 5519
55.2%
1 1
 
< 0.1%
40 1
 
< 0.1%
80 1
 
< 0.1%
400 1
 
< 0.1%
1000 1
 
< 0.1%
ValueCountFrequency (%)
1660770000 1
< 0.1%
945721700 1
< 0.1%
885527500 1
< 0.1%
843339000 1
< 0.1%
742631670 1
< 0.1%
734206000 1
< 0.1%
704626127 1
< 0.1%
700436000 1
< 0.1%
602662000 1
< 0.1%
576708000 1
< 0.1%

동수
Real number (ℝ)

Distinct47
Distinct (%)0.5%
Missing26
Missing (%)0.3%
Infinite0
Infinite (%)0.0%
Mean8.3647483
Minimum1
Maximum58
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-05-03T18:54:23.881492image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q15
median7
Q311
95-th percentile19
Maximum58
Range57
Interquartile range (IQR)6

Descriptive statistics

Standard deviation5.8117209
Coefficient of variation (CV)0.6947873
Kurtosis6.3569881
Mean8.3647483
Median Absolute Deviation (MAD)3
Skewness1.8633177
Sum83430
Variance33.7761
MonotonicityNot monotonic
2024-05-03T18:54:24.345052image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=47)
ValueCountFrequency (%)
6 961
 
9.6%
5 921
 
9.2%
8 873
 
8.7%
7 831
 
8.3%
4 730
 
7.3%
9 638
 
6.4%
3 638
 
6.4%
10 616
 
6.2%
2 567
 
5.7%
1 544
 
5.4%
Other values (37) 2655
26.6%
ValueCountFrequency (%)
1 544
5.4%
2 567
5.7%
3 638
6.4%
4 730
7.3%
5 921
9.2%
6 961
9.6%
7 831
8.3%
8 873
8.7%
9 638
6.4%
10 616
6.2%
ValueCountFrequency (%)
58 1
 
< 0.1%
52 1
 
< 0.1%
50 2
 
< 0.1%
49 1
 
< 0.1%
48 4
< 0.1%
44 3
 
< 0.1%
43 3
 
< 0.1%
41 2
 
< 0.1%
39 8
0.1%
38 8
0.1%

호수
Real number (ℝ)

Distinct1336
Distinct (%)13.4%
Missing26
Missing (%)0.3%
Infinite0
Infinite (%)0.0%
Mean662.75807
Minimum104
Maximum5282
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-05-03T18:54:24.833567image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum104
5-th percentile186
Q1332
median539.5
Q3847
95-th percentile1568
Maximum5282
Range5178
Interquartile range (IQR)515

Descriptive statistics

Standard deviation470.36976
Coefficient of variation (CV)0.70971563
Kurtosis8.0581594
Mean662.75807
Median Absolute Deviation (MAD)241.5
Skewness2.1675752
Sum6610349
Variance221247.71
MonotonicityNot monotonic
2024-05-03T18:54:25.523758image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
299 96
 
1.0%
498 51
 
0.5%
298 51
 
0.5%
420 50
 
0.5%
168 48
 
0.5%
180 46
 
0.5%
330 42
 
0.4%
390 37
 
0.4%
200 37
 
0.4%
600 36
 
0.4%
Other values (1326) 9480
94.8%
ValueCountFrequency (%)
104 3
 
< 0.1%
114 1
 
< 0.1%
120 3
 
< 0.1%
124 1
 
< 0.1%
140 3
 
< 0.1%
144 3
 
< 0.1%
148 1
 
< 0.1%
150 24
0.2%
151 3
 
< 0.1%
152 22
0.2%
ValueCountFrequency (%)
5282 1
 
< 0.1%
4250 2
< 0.1%
4089 3
< 0.1%
4086 3
< 0.1%
3850 3
< 0.1%
3806 3
< 0.1%
3728 1
 
< 0.1%
3724 1
 
< 0.1%
3603 1
 
< 0.1%
3498 1
 
< 0.1%
Distinct2382
Distinct (%)23.9%
Missing26
Missing (%)0.3%
Memory size156.2 KiB
2024-05-03T18:54:26.304191image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length84
Median length70
Mean length10.830158
Min length1

Characters and Unicode

Total characters108020
Distinct characters479
Distinct categories11 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique661 ?
Unique (%)6.6%

Sample

1st row
2nd row
3rd row
4th row광명두산위브트레지움.apti.co.kr
5th row전원마을월드2단지.ma-um.co.kr
ValueCountFrequency (%)
없음 89
 
1.6%
www.kohom.co.kr 47
 
0.8%
www.kohom.or.kr 37
 
0.7%
v2admin.aptner.com 15
 
0.3%
apti.co.kr 13
 
0.2%
link.zigbang.com 12
 
0.2%
kohom.or.kr 11
 
0.2%
없슴 11
 
0.2%
www.aptner.com 10
 
0.2%
movill.net 9
 
0.2%
Other values (2379) 5379
95.5%
2024-05-03T18:54:27.514711image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
. 14428
 
13.4%
o 6379
 
5.9%
a 6226
 
5.8%
m 5789
 
5.4%
c 5580
 
5.2%
r 5379
 
5.0%
k 4610
 
4.3%
4455
 
4.1%
t 3872
 
3.6%
p 3131
 
2.9%
Other values (469) 48171
44.6%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 59073
54.7%
Other Letter 22212
 
20.6%
Other Punctuation 16316
 
15.1%
Space Separator 4455
 
4.1%
Decimal Number 3495
 
3.2%
Dash Punctuation 2085
 
1.9%
Uppercase Letter 307
 
0.3%
Connector Punctuation 29
 
< 0.1%
Math Symbol 18
 
< 0.1%
Open Punctuation 15
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
1034
 
4.7%
828
 
3.7%
741
 
3.3%
712
 
3.2%
582
 
2.6%
482
 
2.2%
426
 
1.9%
400
 
1.8%
390
 
1.8%
390
 
1.8%
Other values (395) 16227
73.1%
Lowercase Letter
ValueCountFrequency (%)
o 6379
10.8%
a 6226
10.5%
m 5789
9.8%
c 5580
9.4%
r 5379
9.1%
k 4610
 
7.8%
t 3872
 
6.6%
p 3131
 
5.3%
i 2705
 
4.6%
u 2565
 
4.3%
Other values (16) 12837
21.7%
Uppercase Letter
ValueCountFrequency (%)
H 94
30.6%
S 21
 
6.8%
T 20
 
6.5%
W 17
 
5.5%
A 14
 
4.6%
K 13
 
4.2%
C 12
 
3.9%
N 12
 
3.9%
I 11
 
3.6%
U 10
 
3.3%
Other values (14) 83
27.0%
Decimal Number
ValueCountFrequency (%)
1 841
24.1%
2 798
22.8%
3 435
12.4%
4 294
 
8.4%
5 278
 
8.0%
7 184
 
5.3%
6 181
 
5.2%
8 169
 
4.8%
9 160
 
4.6%
0 155
 
4.4%
Other Punctuation
ValueCountFrequency (%)
. 14428
88.4%
/ 1585
 
9.7%
: 257
 
1.6%
, 24
 
0.1%
? 15
 
0.1%
& 7
 
< 0.1%
Open Punctuation
ValueCountFrequency (%)
( 12
80.0%
[ 3
 
20.0%
Close Punctuation
ValueCountFrequency (%)
) 12
80.0%
] 3
 
20.0%
Space Separator
ValueCountFrequency (%)
4455
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 2085
100.0%
Connector Punctuation
ValueCountFrequency (%)
_ 29
100.0%
Math Symbol
ValueCountFrequency (%)
= 18
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 59380
55.0%
Common 26428
24.5%
Hangul 22212
 
20.6%

Most frequent character per script

Hangul
ValueCountFrequency (%)
1034
 
4.7%
828
 
3.7%
741
 
3.3%
712
 
3.2%
582
 
2.6%
482
 
2.2%
426
 
1.9%
400
 
1.8%
390
 
1.8%
390
 
1.8%
Other values (395) 16227
73.1%
Latin
ValueCountFrequency (%)
o 6379
10.7%
a 6226
10.5%
m 5789
9.7%
c 5580
9.4%
r 5379
9.1%
k 4610
 
7.8%
t 3872
 
6.5%
p 3131
 
5.3%
i 2705
 
4.6%
u 2565
 
4.3%
Other values (40) 13144
22.1%
Common
ValueCountFrequency (%)
. 14428
54.6%
4455
 
16.9%
- 2085
 
7.9%
/ 1585
 
6.0%
1 841
 
3.2%
2 798
 
3.0%
3 435
 
1.6%
4 294
 
1.1%
5 278
 
1.1%
: 257
 
1.0%
Other values (14) 972
 
3.7%

Most occurring blocks

ValueCountFrequency (%)
ASCII 85808
79.4%
Hangul 22212
 
20.6%

Most frequent character per block

ASCII
ValueCountFrequency (%)
. 14428
16.8%
o 6379
 
7.4%
a 6226
 
7.3%
m 5789
 
6.7%
c 5580
 
6.5%
r 5379
 
6.3%
k 4610
 
5.4%
4455
 
5.2%
t 3872
 
4.5%
p 3131
 
3.6%
Other values (64) 25959
30.3%
Hangul
ValueCountFrequency (%)
1034
 
4.7%
828
 
3.7%
741
 
3.3%
712
 
3.2%
582
 
2.6%
482
 
2.2%
426
 
1.9%
400
 
1.8%
390
 
1.8%
390
 
1.8%
Other values (395) 16227
73.1%

135이상전용면적세대수
Real number (ℝ)

ZEROS 

Distinct236
Distinct (%)2.4%
Missing26
Missing (%)0.3%
Infinite0
Infinite (%)0.0%
Mean17.248947
Minimum0
Maximum1164
Zeros8624
Zeros (%)86.2%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-05-03T18:54:28.069018image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile109
Maximum1164
Range1164
Interquartile range (IQR)0

Descriptive statistics

Standard deviation69.443604
Coefficient of variation (CV)4.0259619
Kurtosis59.515023
Mean17.248947
Median Absolute Deviation (MAD)0
Skewness6.6789689
Sum172041
Variance4822.4142
MonotonicityNot monotonic
2024-05-03T18:54:28.618594image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 8624
86.2%
2 45
 
0.4%
4 37
 
0.4%
76 33
 
0.3%
60 30
 
0.3%
30 30
 
0.3%
80 28
 
0.3%
6 28
 
0.3%
72 27
 
0.3%
5 26
 
0.3%
Other values (226) 1066
 
10.7%
(Missing) 26
 
0.3%
ValueCountFrequency (%)
0 8624
86.2%
1 12
 
0.1%
2 45
 
0.4%
3 13
 
0.1%
4 37
 
0.4%
5 26
 
0.3%
6 28
 
0.3%
7 1
 
< 0.1%
8 18
 
0.2%
9 1
 
< 0.1%
ValueCountFrequency (%)
1164 1
 
< 0.1%
924 1
 
< 0.1%
889 5
0.1%
884 3
< 0.1%
800 4
< 0.1%
760 3
< 0.1%
741 2
 
< 0.1%
692 2
 
< 0.1%
650 2
 
< 0.1%
644 2
 
< 0.1%

135이하전용면적세대수
Real number (ℝ)

ZEROS 

Distinct598
Distinct (%)6.0%
Missing26
Missing (%)0.3%
Infinite0
Infinite (%)0.0%
Mean92.018749
Minimum0
Maximum2021
Zeros6567
Zeros (%)65.7%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-05-03T18:54:29.182230image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q391
95-th percentile493
Maximum2021
Range2021
Interquartile range (IQR)91

Descriptive statistics

Standard deviation195.39912
Coefficient of variation (CV)2.1234708
Kurtosis14.169787
Mean92.018749
Median Absolute Deviation (MAD)0
Skewness3.2252969
Sum917795
Variance38180.817
MonotonicityNot monotonic
2024-05-03T18:54:29.811214image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 6567
65.7%
60 78
 
0.8%
40 55
 
0.5%
80 31
 
0.3%
48 31
 
0.3%
30 30
 
0.3%
240 29
 
0.3%
120 28
 
0.3%
72 27
 
0.3%
150 25
 
0.2%
Other values (588) 3073
30.7%
(Missing) 26
 
0.3%
ValueCountFrequency (%)
0 6567
65.7%
2 4
 
< 0.1%
3 5
 
0.1%
4 10
 
0.1%
5 5
 
0.1%
6 4
 
< 0.1%
7 1
 
< 0.1%
8 4
 
< 0.1%
9 7
 
0.1%
10 8
 
0.1%
ValueCountFrequency (%)
2021 2
< 0.1%
1928 1
 
< 0.1%
1878 3
< 0.1%
1654 3
< 0.1%
1616 1
 
< 0.1%
1568 2
< 0.1%
1458 1
 
< 0.1%
1406 2
< 0.1%
1401 2
< 0.1%
1290 3
< 0.1%

60이하전용면적세대수
Real number (ℝ)

ZEROS 

Distinct955
Distinct (%)9.6%
Missing26
Missing (%)0.3%
Infinite0
Infinite (%)0.0%
Mean248.65119
Minimum0
Maximum3227
Zeros4420
Zeros (%)44.2%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-05-03T18:54:30.295107image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median84
Q3332
95-th percentile1070.35
Maximum3227
Range3227
Interquartile range (IQR)332

Descriptive statistics

Standard deviation388.0326
Coefficient of variation (CV)1.5605499
Kurtosis6.9919007
Mean248.65119
Median Absolute Deviation (MAD)84
Skewness2.3806921
Sum2480047
Variance150569.3
MonotonicityNot monotonic
2024-05-03T18:54:30.893948image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 4420
44.2%
180 55
 
0.5%
299 49
 
0.5%
60 46
 
0.5%
120 45
 
0.4%
240 45
 
0.4%
210 43
 
0.4%
90 41
 
0.4%
300 39
 
0.4%
140 39
 
0.4%
Other values (945) 5152
51.5%
ValueCountFrequency (%)
0 4420
44.2%
1 2
 
< 0.1%
3 1
 
< 0.1%
7 2
 
< 0.1%
8 4
 
< 0.1%
11 3
 
< 0.1%
12 1
 
< 0.1%
14 3
 
< 0.1%
17 3
 
< 0.1%
18 5
 
0.1%
ValueCountFrequency (%)
3227 1
 
< 0.1%
3129 1
 
< 0.1%
2742 2
 
< 0.1%
2682 3
< 0.1%
2615 3
< 0.1%
2568 5
0.1%
2510 2
 
< 0.1%
2489 3
< 0.1%
2416 1
 
< 0.1%
2342 3
< 0.1%

85이하전용면적세대수
Real number (ℝ)

ZEROS 

Distinct1023
Distinct (%)10.3%
Missing26
Missing (%)0.3%
Infinite0
Infinite (%)0.0%
Mean304.82725
Minimum0
Maximum3425
Zeros3103
Zeros (%)31.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-05-03T18:54:31.323749image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median205.5
Q3460
95-th percentile1023
Maximum3425
Range3425
Interquartile range (IQR)460

Descriptive statistics

Standard deviation359.4772
Coefficient of variation (CV)1.1792817
Kurtosis6.4589524
Mean304.82725
Median Absolute Deviation (MAD)205.5
Skewness1.984023
Sum3040347
Variance129223.86
MonotonicityNot monotonic
2024-05-03T18:54:31.891424image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 3103
31.0%
240 55
 
0.5%
180 54
 
0.5%
120 48
 
0.5%
150 44
 
0.4%
320 41
 
0.4%
360 38
 
0.4%
200 37
 
0.4%
72 37
 
0.4%
156 36
 
0.4%
Other values (1013) 6481
64.8%
ValueCountFrequency (%)
0 3103
31.0%
1 6
 
0.1%
2 4
 
< 0.1%
3 4
 
< 0.1%
4 3
 
< 0.1%
5 7
 
0.1%
6 3
 
< 0.1%
7 2
 
< 0.1%
8 7
 
0.1%
10 5
 
0.1%
ValueCountFrequency (%)
3425 3
< 0.1%
3374 1
 
< 0.1%
2988 1
 
< 0.1%
2820 3
< 0.1%
2454 1
 
< 0.1%
2429 1
 
< 0.1%
2324 1
 
< 0.1%
2303 3
< 0.1%
2280 1
 
< 0.1%
2240 2
< 0.1%

관리방식
Categorical

IMBALANCE 

Distinct8
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
위탁관리
9244 
자치관리
 
658
자치관리(직영)
 
28
<NA>
 
26
위탁관리(직영+위탁)
 
18
Other values (3)
 
26

Length

Max length11
Median length4
Mean length4.0316
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
위탁관리 9244
92.4%
자치관리 658
 
6.6%
자치관리(직영) 28
 
0.3%
<NA> 26
 
0.3%
위탁관리(직영+위탁) 18
 
0.2%
위탁관리(총액관리제) 10
 
0.1%
관리방식미정 10
 
0.1%
기타 6
 
0.1%

Length

2024-05-03T18:54:32.542071image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-03T18:54:32.880833image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
위탁관리 9244
92.4%
자치관리 658
 
6.6%
자치관리(직영 28
 
0.3%
na 26
 
0.3%
위탁관리(직영+위탁 18
 
0.2%
위탁관리(총액관리제 10
 
0.1%
관리방식미정 10
 
0.1%
기타 6
 
0.1%

관리금액부과면적
Real number (ℝ)

Distinct4514
Distinct (%)45.3%
Missing26
Missing (%)0.3%
Infinite0
Infinite (%)0.0%
Mean67663.123
Minimum1490.688
Maximum596167.02
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-05-03T18:54:33.490484image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1490.688
5-th percentile16036.569
Q132770.575
median56010.549
Q386559.201
95-th percentile161839.47
Maximum596167.02
Range594676.33
Interquartile range (IQR)53788.626

Descriptive statistics

Standard deviation50863.112
Coefficient of variation (CV)0.75171097
Kurtosis9.1509294
Mean67663.123
Median Absolute Deviation (MAD)25692.202
Skewness2.2987842
Sum6.7487199 × 108
Variance2.5870561 × 109
MonotonicityNot monotonic
2024-05-03T18:54:34.233464image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
27259.4938 6
 
0.1%
100639.2002 6
 
0.1%
119358.6372 6
 
0.1%
60340.82 6
 
0.1%
22611.574 6
 
0.1%
37935.18 6
 
0.1%
18264.08 6
 
0.1%
81721.9671 6
 
0.1%
87702.7985 6
 
0.1%
29035.93 6
 
0.1%
Other values (4504) 9914
99.1%
(Missing) 26
 
0.3%
ValueCountFrequency (%)
1490.688 1
 
< 0.1%
2383.122 3
< 0.1%
2514.036 2
 
< 0.1%
3947.143 2
 
< 0.1%
4024.02 2
 
< 0.1%
4151.43 4
< 0.1%
4293.554 5
0.1%
4370.48 3
< 0.1%
4569.9264 1
 
< 0.1%
4928.4495 3
< 0.1%
ValueCountFrequency (%)
596167.02 1
 
< 0.1%
456004.944 3
< 0.1%
441159.193 2
< 0.1%
438974.1666 1
 
< 0.1%
428956.1468 2
< 0.1%
416710.386 1
 
< 0.1%
398391.9616 3
< 0.1%
392903.12 3
< 0.1%
381671.94 1
 
< 0.1%
368911.08 2
< 0.1%
Distinct4507
Distinct (%)45.2%
Missing26
Missing (%)0.3%
Memory size156.2 KiB
2024-05-03T18:54:35.122955image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length12
Median length10
Mean length10.004913
Min length1

Characters and Unicode

Total characters99789
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

Unique1304 ?
Unique (%)13.1%

Sample

1st row0318599631
2nd row0315567332
3rd row0317658133
4th row028983338
5th row0319980531
ValueCountFrequency (%)
0317340972 6
 
0.1%
0318789087 6
 
0.1%
0326534021 6
 
0.1%
0318978994 6
 
0.1%
0313128440 6
 
0.1%
0326510029 6
 
0.1%
0319141312 6
 
0.1%
0312227757 6
 
0.1%
0319626331 6
 
0.1%
024498891 6
 
0.1%
Other values (4496) 9903
99.4%
2024-05-03T18:54:36.531272image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
3 17168
17.2%
0 16219
16.3%
1 16122
16.2%
2 8654
8.7%
7 7382
7.4%
8 7074
7.1%
6 7068
7.1%
5 6994
7.0%
9 6768
 
6.8%
4 6197
 
6.2%
Other values (2) 143
 
0.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 99646
99.9%
Dash Punctuation 132
 
0.1%
Space Separator 11
 
< 0.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
3 17168
17.2%
0 16219
16.3%
1 16122
16.2%
2 8654
8.7%
7 7382
7.4%
8 7074
7.1%
6 7068
7.1%
5 6994
7.0%
9 6768
 
6.8%
4 6197
 
6.2%
Dash Punctuation
ValueCountFrequency (%)
- 132
100.0%
Space Separator
ValueCountFrequency (%)
11
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 99789
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
3 17168
17.2%
0 16219
16.3%
1 16122
16.2%
2 8654
8.7%
7 7382
7.4%
8 7074
7.1%
6 7068
7.1%
5 6994
7.0%
9 6768
 
6.8%
4 6197
 
6.2%
Other values (2) 143
 
0.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 99789
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
3 17168
17.2%
0 16219
16.3%
1 16122
16.2%
2 8654
8.7%
7 7382
7.4%
8 7074
7.1%
6 7068
7.1%
5 6994
7.0%
9 6768
 
6.8%
4 6197
 
6.2%
Other values (2) 143
 
0.1%
Distinct4413
Distinct (%)44.2%
Missing26
Missing (%)0.3%
Memory size156.2 KiB
2024-05-03T18:54:37.538201image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length11
Median length10
Mean length9.8129136
Min length1

Characters and Unicode

Total characters97874
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

Unique1274 ?
Unique (%)12.8%

Sample

1st row0318599632
2nd row0315567333
3rd row03181338135
4th row028984448
5th row0319980532
ValueCountFrequency (%)
0319626321 6
 
0.1%
0313128443 6
 
0.1%
0312257757 6
 
0.1%
0319117608 6
 
0.1%
0326149301 6
 
0.1%
0318273495 6
 
0.1%
0318983006 6
 
0.1%
0318162133 6
 
0.1%
024498892 6
 
0.1%
0317340974 6
 
0.1%
Other values (4402) 9706
99.4%
2024-05-03T18:54:38.958555image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
3 17030
17.4%
0 15270
15.6%
1 15198
15.5%
2 8444
8.6%
8 7281
7.4%
6 7199
7.4%
7 7103
7.3%
9 6933
7.1%
5 6827
7.0%
4 6381
 
6.5%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 97666
99.8%
Space Separator 208
 
0.2%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
3 17030
17.4%
0 15270
15.6%
1 15198
15.6%
2 8444
8.6%
8 7281
7.5%
6 7199
7.4%
7 7103
7.3%
9 6933
7.1%
5 6827
7.0%
4 6381
 
6.5%
Space Separator
ValueCountFrequency (%)
208
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 97874
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
3 17030
17.4%
0 15270
15.6%
1 15198
15.5%
2 8444
8.6%
8 7281
7.4%
6 7199
7.4%
7 7103
7.3%
9 6933
7.1%
5 6827
7.0%
4 6381
 
6.5%

Most occurring blocks

ValueCountFrequency (%)
ASCII 97874
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
3 17030
17.4%
0 15270
15.6%
1 15198
15.5%
2 8444
8.6%
8 7281
7.4%
6 7199
7.4%
7 7103
7.3%
9 6933
7.1%
5 6827
7.0%
4 6381
 
6.5%

난방방식
Categorical

IMBALANCE 

Distinct6
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
지역난방
5015 
개별난방
4868 
중앙난방
 
67
<NA>
 
26
개별난방+기타
 
21

Length

Max length7
Median length4
Mean length4.0057
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
지역난방 5015
50.1%
개별난방 4868
48.7%
중앙난방 67
 
0.7%
<NA> 26
 
0.3%
개별난방+기타 21
 
0.2%
기타 3
 
< 0.1%

Length

2024-05-03T18:54:39.628315image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-03T18:54:39.975908image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
지역난방 5015
50.1%
개별난방 4868
48.7%
중앙난방 67
 
0.7%
na 26
 
0.3%
개별난방+기타 21
 
0.2%
기타 3
 
< 0.1%

충당금액잔액
Unsupported

MISSING  REJECTED  UNSUPPORTED 

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

청소비용
Real number (ℝ)

MISSING 

Distinct4778
Distinct (%)94.3%
Missing4934
Missing (%)49.3%
Infinite0
Infinite (%)0.0%
Mean12338051
Minimum0
Maximum1.0748614 × 108
Zeros22
Zeros (%)0.2%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-05-03T18:54:40.444716image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile2111222.5
Q15622885
median9544825
Q315825700
95-th percentile31238618
Maximum1.0748614 × 108
Range1.0748614 × 108
Interquartile range (IQR)10202815

Descriptive statistics

Standard deviation10417127
Coefficient of variation (CV)0.84430892
Kurtosis11.701818
Mean12338051
Median Absolute Deviation (MAD)4709070
Skewness2.6119987
Sum6.2504569 × 1010
Variance1.0851653 × 1014
MonotonicityNot monotonic
2024-05-03T18:54:41.060521image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 22
 
0.2%
14363380 3
 
< 0.1%
3819920 3
 
< 0.1%
1500000 3
 
< 0.1%
1020000 3
 
< 0.1%
13356050 2
 
< 0.1%
14404540 2
 
< 0.1%
18308540 2
 
< 0.1%
5819610 2
 
< 0.1%
8998920 2
 
< 0.1%
Other values (4768) 5022
50.2%
(Missing) 4934
49.3%
ValueCountFrequency (%)
0 22
0.2%
26050 1
 
< 0.1%
29600 1
 
< 0.1%
66100 1
 
< 0.1%
100500 1
 
< 0.1%
128465 1
 
< 0.1%
144410 1
 
< 0.1%
149160 1
 
< 0.1%
159995 1
 
< 0.1%
170000 1
 
< 0.1%
ValueCountFrequency (%)
107486140 1
< 0.1%
99547500 1
< 0.1%
99070750 1
< 0.1%
97192580 1
< 0.1%
94569950 1
< 0.1%
87199646 1
< 0.1%
86513680 1
< 0.1%
85030880 1
< 0.1%
84321310 1
< 0.1%
81088407 1
< 0.1%

경비원급여비용
Real number (ℝ)

MISSING 

Distinct4618
Distinct (%)92.2%
Missing4994
Missing (%)49.9%
Infinite0
Infinite (%)0.0%
Mean18387849
Minimum-827341
Maximum2.7088501 × 108
Zeros92
Zeros (%)0.9%
Negative1
Negative (%)< 0.1%
Memory size166.0 KiB
2024-05-03T18:54:41.528089image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum-827341
5-th percentile4975261.2
Q19562823.2
median14399374
Q322902521
95-th percentile43772416
Maximum2.7088501 × 108
Range2.7171235 × 108
Interquartile range (IQR)13339698

Descriptive statistics

Standard deviation15585452
Coefficient of variation (CV)0.84759515
Kurtosis38.547125
Mean18387849
Median Absolute Deviation (MAD)6516884
Skewness4.1800914
Sum9.2049573 × 1010
Variance2.4290631 × 1014
MonotonicityNot monotonic
2024-05-03T18:54:42.029846image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 92
 
0.9%
3540000 3
 
< 0.1%
12292000 3
 
< 0.1%
1888840 3
 
< 0.1%
13325340 2
 
< 0.1%
16751410 2
 
< 0.1%
13445850 2
 
< 0.1%
11447860 2
 
< 0.1%
22125170 2
 
< 0.1%
5794590 2
 
< 0.1%
Other values (4608) 4893
48.9%
(Missing) 4994
49.9%
ValueCountFrequency (%)
-827341 1
 
< 0.1%
0 92
0.9%
308000 1
 
< 0.1%
1789510 1
 
< 0.1%
1836550 1
 
< 0.1%
1888840 3
 
< 0.1%
2196445 2
 
< 0.1%
2240720 1
 
< 0.1%
2342945 1
 
< 0.1%
2393310 1
 
< 0.1%
ValueCountFrequency (%)
270885010 1
< 0.1%
268700630 1
< 0.1%
150934980 1
< 0.1%
149285446 1
< 0.1%
148877452 1
< 0.1%
141428352 1
< 0.1%
140858390 1
< 0.1%
138696216 1
< 0.1%
135052142 1
< 0.1%
129641350 1
< 0.1%

난방공용비용
Real number (ℝ)

MISSING  ZEROS 

Distinct856
Distinct (%)49.7%
Missing8278
Missing (%)82.8%
Infinite0
Infinite (%)0.0%
Mean4912343.2
Minimum-22538910
Maximum1.6446936 × 108
Zeros867
Zeros (%)8.7%
Negative20
Negative (%)0.2%
Memory size166.0 KiB
2024-05-03T18:54:43.160073image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum-22538910
5-th percentile0
Q10
median0
Q35272372.5
95-th percentile22194610
Maximum1.6446936 × 108
Range1.8700827 × 108
Interquartile range (IQR)5272372.5

Descriptive statistics

Standard deviation12123700
Coefficient of variation (CV)2.4680075
Kurtosis50.862529
Mean4912343.2
Median Absolute Deviation (MAD)0
Skewness5.9495137
Sum8.459055 × 109
Variance1.4698409 × 1014
MonotonicityNot monotonic
2024-05-03T18:54:44.501534image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 867
 
8.7%
6262250 1
 
< 0.1%
6748690 1
 
< 0.1%
20105250 1
 
< 0.1%
1727150 1
 
< 0.1%
4095260 1
 
< 0.1%
10811080 1
 
< 0.1%
2719510 1
 
< 0.1%
1883130 1
 
< 0.1%
6254230 1
 
< 0.1%
Other values (846) 846
 
8.5%
(Missing) 8278
82.8%
ValueCountFrequency (%)
-22538910 1
< 0.1%
-12536770 1
< 0.1%
-9899000 1
< 0.1%
-8954000 1
< 0.1%
-7602680 1
< 0.1%
-7252320 1
< 0.1%
-6075740 1
< 0.1%
-5724470 1
< 0.1%
-4294500 1
< 0.1%
-4242930 1
< 0.1%
ValueCountFrequency (%)
164469359 1
< 0.1%
147891590 1
< 0.1%
128328229 1
< 0.1%
118278970 1
< 0.1%
106152270 1
< 0.1%
93667620 1
< 0.1%
86653630 1
< 0.1%
84645160 1
< 0.1%
84520670 1
< 0.1%
76683520 1
< 0.1%

난방전용비용
Real number (ℝ)

MISSING  ZEROS 

Distinct839
Distinct (%)48.7%
Missing8278
Missing (%)82.8%
Infinite0
Infinite (%)0.0%
Mean17549319
Minimum0
Maximum1.7955291 × 108
Zeros884
Zeros (%)8.8%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-05-03T18:54:45.471644image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q328977175
95-th percentile63662901
Maximum1.7955291 × 108
Range1.7955291 × 108
Interquartile range (IQR)28977175

Descriptive statistics

Standard deviation25490648
Coefficient of variation (CV)1.4525149
Kurtosis7.356453
Mean17549319
Median Absolute Deviation (MAD)0
Skewness2.2295549
Sum3.0219928 × 1010
Variance6.4977314 × 1014
MonotonicityNot monotonic
2024-05-03T18:54:46.322613image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 884
 
8.8%
13519690 1
 
< 0.1%
39153220 1
 
< 0.1%
6717200 1
 
< 0.1%
103278110 1
 
< 0.1%
24709290 1
 
< 0.1%
71915910 1
 
< 0.1%
55592950 1
 
< 0.1%
103055040 1
 
< 0.1%
41214730 1
 
< 0.1%
Other values (829) 829
 
8.3%
(Missing) 8278
82.8%
ValueCountFrequency (%)
0 884
8.8%
89890 1
 
< 0.1%
171660 1
 
< 0.1%
343600 1
 
< 0.1%
498550 1
 
< 0.1%
654240 1
 
< 0.1%
1983830 1
 
< 0.1%
2107790 1
 
< 0.1%
2113200 1
 
< 0.1%
2687010 1
 
< 0.1%
ValueCountFrequency (%)
179552910 1
< 0.1%
176622840 1
< 0.1%
171034910 1
< 0.1%
168691840 1
< 0.1%
167884200 1
< 0.1%
167388430 1
< 0.1%
163432000 1
< 0.1%
161005810 1
< 0.1%
151541410 1
< 0.1%
135210810 1
< 0.1%

수도공용비용
Real number (ℝ)

MISSING  ZEROS 

Distinct2011
Distinct (%)54.3%
Missing6296
Missing (%)63.0%
Infinite0
Infinite (%)0.0%
Mean619344.83
Minimum-16425660
Maximum57858860
Zeros1386
Zeros (%)13.9%
Negative827
Negative (%)8.3%
Memory size166.0 KiB
2024-05-03T18:54:47.892313image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum-16425660
5-th percentile-513876
Q10
median0
Q3152017.5
95-th percentile3123451
Maximum57858860
Range74284520
Interquartile range (IQR)152017.5

Descriptive statistics

Standard deviation3244914
Coefficient of variation (CV)5.2392687
Kurtosis93.951183
Mean619344.83
Median Absolute Deviation (MAD)1240
Skewness8.1184303
Sum2.2940532 × 109
Variance1.0529467 × 1013
MonotonicityNot monotonic
2024-05-03T18:54:49.406958image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 1386
 
13.9%
-10 15
 
0.1%
-40 11
 
0.1%
10 9
 
0.1%
-350 8
 
0.1%
-20 8
 
0.1%
-210 7
 
0.1%
-140 7
 
0.1%
-90 7
 
0.1%
-400 7
 
0.1%
Other values (2001) 2239
 
22.4%
(Missing) 6296
63.0%
ValueCountFrequency (%)
-16425660 1
< 0.1%
-8412470 1
< 0.1%
-6037500 1
< 0.1%
-5692270 1
< 0.1%
-4960080 1
< 0.1%
-4652110 1
< 0.1%
-4512790 1
< 0.1%
-4382290 1
< 0.1%
-4337730 1
< 0.1%
-4198720 1
< 0.1%
ValueCountFrequency (%)
57858860 1
< 0.1%
56153790 1
< 0.1%
45272800 1
< 0.1%
42904490 1
< 0.1%
38571810 1
< 0.1%
34419680 1
< 0.1%
32369000 1
< 0.1%
31485500 1
< 0.1%
28464660 1
< 0.1%
27161620 1
< 0.1%

수도전용비용
Real number (ℝ)

MISSING  ZEROS 

Distinct3518
Distinct (%)95.0%
Missing6296
Missing (%)63.0%
Infinite0
Infinite (%)0.0%
Mean11842239
Minimum0
Maximum99117750
Zeros179
Zeros (%)1.8%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-05-03T18:54:50.519021image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile838336.5
Q15653192.5
median9936170
Q315891872
95-th percentile29144719
Maximum99117750
Range99117750
Interquartile range (IQR)10238679

Descriptive statistics

Standard deviation9071141.1
Coefficient of variation (CV)0.76599884
Kurtosis6.9525026
Mean11842239
Median Absolute Deviation (MAD)4874700
Skewness1.8602778
Sum4.3863652 × 1010
Variance8.22856 × 1013
MonotonicityNot monotonic
2024-05-03T18:54:51.168307image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 179
 
1.8%
7271690 2
 
< 0.1%
3738010 2
 
< 0.1%
6995580 2
 
< 0.1%
4256470 2
 
< 0.1%
3764450 2
 
< 0.1%
3920410 2
 
< 0.1%
4599900 2
 
< 0.1%
4878550 2
 
< 0.1%
11017300 1
 
< 0.1%
Other values (3508) 3508
35.1%
(Missing) 6296
63.0%
ValueCountFrequency (%)
0 179
1.8%
672340 1
 
< 0.1%
693390 1
 
< 0.1%
727070 1
 
< 0.1%
737940 1
 
< 0.1%
784000 1
 
< 0.1%
824230 1
 
< 0.1%
832950 1
 
< 0.1%
868860 1
 
< 0.1%
903900 1
 
< 0.1%
ValueCountFrequency (%)
99117750 1
< 0.1%
82541520 1
< 0.1%
77845530 1
< 0.1%
72395080 1
< 0.1%
64591460 1
< 0.1%
60848710 1
< 0.1%
58269190 1
< 0.1%
56775180 1
< 0.1%
55693160 1
< 0.1%
53546700 1
< 0.1%

전기공용비용
Real number (ℝ)

MISSING 

Distinct5036
Distinct (%)99.4%
Missing4935
Missing (%)49.4%
Infinite0
Infinite (%)0.0%
Mean11431068
Minimum-30768600
Maximum2.6838828 × 108
Zeros27
Zeros (%)0.3%
Negative48
Negative (%)0.5%
Memory size166.0 KiB
2024-05-03T18:54:51.840459image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum-30768600
5-th percentile1099022.4
Q13464340
median7137560
Q314195460
95-th percentile34587300
Maximum2.6838828 × 108
Range2.9915688 × 108
Interquartile range (IQR)10731120

Descriptive statistics

Standard deviation14586151
Coefficient of variation (CV)1.2760095
Kurtosis62.249479
Mean11431068
Median Absolute Deviation (MAD)4438870
Skewness5.5881656
Sum5.7898359 × 1010
Variance2.127558 × 1014
MonotonicityNot monotonic
2024-05-03T18:54:52.556039image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 27
 
0.3%
7089220 2
 
< 0.1%
322322 2
 
< 0.1%
151800 2
 
< 0.1%
7547007 1
 
< 0.1%
17677580 1
 
< 0.1%
10169810 1
 
< 0.1%
4160650 1
 
< 0.1%
2566699 1
 
< 0.1%
3823810 1
 
< 0.1%
Other values (5026) 5026
50.3%
(Missing) 4935
49.4%
ValueCountFrequency (%)
-30768600 1
< 0.1%
-5956912 1
< 0.1%
-5862489 1
< 0.1%
-5791420 1
< 0.1%
-5598140 1
< 0.1%
-4814650 1
< 0.1%
-4694840 1
< 0.1%
-4044453 1
< 0.1%
-4022517 1
< 0.1%
-3417430 1
< 0.1%
ValueCountFrequency (%)
268388285 1
< 0.1%
251209667 1
< 0.1%
226990213 1
< 0.1%
205929860 1
< 0.1%
203179603 1
< 0.1%
125781135 1
< 0.1%
123714780 1
< 0.1%
121640330 1
< 0.1%
109518690 1
< 0.1%
104228682 1
< 0.1%

전기전용비용
Real number (ℝ)

MISSING  ZEROS 

Distinct4632
Distinct (%)91.5%
Missing4935
Missing (%)49.4%
Infinite0
Infinite (%)0.0%
Mean29496358
Minimum0
Maximum2.2932022 × 108
Zeros428
Zeros (%)4.3%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-05-03T18:54:53.052049image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q113203530
median24210480
Q338648580
95-th percentile75270956
Maximum2.2932022 × 108
Range2.2932022 × 108
Interquartile range (IQR)25445050

Descriptive statistics

Standard deviation25453693
Coefficient of variation (CV)0.86294361
Kurtosis9.5081864
Mean29496358
Median Absolute Deviation (MAD)12163230
Skewness2.2995199
Sum1.4939905 × 1011
Variance6.478905 × 1014
MonotonicityNot monotonic
2024-05-03T18:54:53.545065image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 428
 
4.3%
10354810 2
 
< 0.1%
39748750 2
 
< 0.1%
17075500 2
 
< 0.1%
74968060 2
 
< 0.1%
6696710 2
 
< 0.1%
40641060 2
 
< 0.1%
78990200 1
 
< 0.1%
4454500 1
 
< 0.1%
50626170 1
 
< 0.1%
Other values (4622) 4622
46.2%
(Missing) 4935
49.4%
ValueCountFrequency (%)
0 428
4.3%
810 1
 
< 0.1%
33800 1
 
< 0.1%
47500 1
 
< 0.1%
55900 1
 
< 0.1%
94300 1
 
< 0.1%
117300 1
 
< 0.1%
347430 1
 
< 0.1%
357500 1
 
< 0.1%
420060 1
 
< 0.1%
ValueCountFrequency (%)
229320220 1
< 0.1%
224559980 1
< 0.1%
221820040 1
< 0.1%
212967490 1
< 0.1%
212182330 1
< 0.1%
203472370 1
< 0.1%
199370260 1
< 0.1%
197706760 1
< 0.1%
197198000 1
< 0.1%
196363900 1
< 0.1%

건강보험요금
Real number (ℝ)

MISSING  ZEROS 

Distinct4414
Distinct (%)87.2%
Missing4939
Missing (%)49.4%
Infinite0
Infinite (%)0.0%
Mean779223.64
Minimum-5797000
Maximum4600200
Zeros188
Zeros (%)1.9%
Negative1
Negative (%)< 0.1%
Memory size166.0 KiB
2024-05-03T18:54:54.361515image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum-5797000
5-th percentile160140
Q1500760
median716840
Q3993140
95-th percentile1538310
Maximum4600200
Range10397200
Interquartile range (IQR)492380

Descriptive statistics

Standard deviation463825.69
Coefficient of variation (CV)0.59524078
Kurtosis14.219098
Mean779223.64
Median Absolute Deviation (MAD)237170
Skewness0.98941296
Sum3.9436508 × 109
Variance2.1513427 × 1011
MonotonicityNot monotonic
2024-05-03T18:54:54.871189image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 188
 
1.9%
656140 4
 
< 0.1%
665690 4
 
< 0.1%
417650 3
 
< 0.1%
525930 3
 
< 0.1%
208730 3
 
< 0.1%
266710 3
 
< 0.1%
409610 3
 
< 0.1%
242920 3
 
< 0.1%
648590 3
 
< 0.1%
Other values (4404) 4844
48.4%
(Missing) 4939
49.4%
ValueCountFrequency (%)
-5797000 1
 
< 0.1%
0 188
1.9%
41980 1
 
< 0.1%
48382 2
 
< 0.1%
54897 2
 
< 0.1%
83970 1
 
< 0.1%
88260 1
 
< 0.1%
90457 2
 
< 0.1%
91970 1
 
< 0.1%
94760 1
 
< 0.1%
ValueCountFrequency (%)
4600200 2
< 0.1%
4188020 1
< 0.1%
3832480 1
< 0.1%
3812910 1
< 0.1%
3759270 1
< 0.1%
3753650 1
< 0.1%
3530320 1
< 0.1%
3424200 1
< 0.1%
3403290 1
< 0.1%
3314630 1
< 0.1%

고용보험요금
Real number (ℝ)

MISSING  ZEROS 

Distinct4132
Distinct (%)81.6%
Missing4939
Missing (%)49.4%
Infinite0
Infinite (%)0.0%
Mean216622.48
Minimum-372260
Maximum1642780
Zeros202
Zeros (%)2.0%
Negative1
Negative (%)< 0.1%
Memory size166.0 KiB
2024-05-03T18:54:55.356803image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum-372260
5-th percentile30190
Q1131740
median196480
Q3277370
95-th percentile449940
Maximum1642780
Range2015040
Interquartile range (IQR)145630

Descriptive statistics

Standard deviation138608.32
Coefficient of variation (CV)0.6398612
Kurtosis8.9658342
Mean216622.48
Median Absolute Deviation (MAD)72830
Skewness1.8417776
Sum1.0963264 × 109
Variance1.9212267 × 1010
MonotonicityNot monotonic
2024-05-03T18:54:56.242660image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 202
 
2.0%
181430 5
 
0.1%
178540 5
 
0.1%
209140 4
 
< 0.1%
270740 4
 
< 0.1%
323770 4
 
< 0.1%
138390 4
 
< 0.1%
183280 4
 
< 0.1%
380100 4
 
< 0.1%
268900 4
 
< 0.1%
Other values (4122) 4821
48.2%
(Missing) 4939
49.4%
ValueCountFrequency (%)
-372260 1
 
< 0.1%
0 202
2.0%
2250 1
 
< 0.1%
6000 1
 
< 0.1%
7820 2
 
< 0.1%
8590 1
 
< 0.1%
9450 1
 
< 0.1%
10320 1
 
< 0.1%
10770 1
 
< 0.1%
11950 1
 
< 0.1%
ValueCountFrequency (%)
1642780 1
< 0.1%
1367550 1
< 0.1%
1316450 1
< 0.1%
1288180 1
< 0.1%
1282368 1
< 0.1%
1159510 1
< 0.1%
1146080 1
< 0.1%
1109420 1
< 0.1%
1043240 1
< 0.1%
1025840 1
< 0.1%

국민연금금액
Real number (ℝ)

MISSING  ZEROS 

Distinct3674
Distinct (%)72.6%
Missing4939
Missing (%)49.4%
Infinite0
Infinite (%)0.0%
Mean526158.53
Minimum-65730
Maximum4228670
Zeros297
Zeros (%)3.0%
Negative1
Negative (%)< 0.1%
Memory size166.0 KiB
2024-05-03T18:54:56.813591image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum-65730
5-th percentile0
Q1244050
median443250
Q3723760
95-th percentile1241510
Maximum4228670
Range4294400
Interquartile range (IQR)479710

Descriptive statistics

Standard deviation403327.76
Coefficient of variation (CV)0.76655178
Kurtosis4.8520951
Mean526158.53
Median Absolute Deviation (MAD)234090
Skewness1.5272632
Sum2.6628883 × 109
Variance1.6267328 × 1011
MonotonicityNot monotonic
2024-05-03T18:54:57.487807image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 297
 
3.0%
533650 6
 
0.1%
400400 5
 
0.1%
101860 5
 
0.1%
109840 5
 
0.1%
260410 4
 
< 0.1%
252580 4
 
< 0.1%
121300 4
 
< 0.1%
152900 4
 
< 0.1%
87250 4
 
< 0.1%
Other values (3664) 4723
47.2%
(Missing) 4939
49.4%
ValueCountFrequency (%)
-65730 1
 
< 0.1%
0 297
3.0%
280 1
 
< 0.1%
10950 1
 
< 0.1%
17670 2
 
< 0.1%
18200 2
 
< 0.1%
18380 2
 
< 0.1%
18440 3
 
< 0.1%
18800 2
 
< 0.1%
18850 1
 
< 0.1%
ValueCountFrequency (%)
4228670 1
< 0.1%
3113700 2
< 0.1%
2950520 1
< 0.1%
2868490 1
< 0.1%
2848680 1
< 0.1%
2733000 1
< 0.1%
2625170 1
< 0.1%
2551080 1
< 0.1%
2529730 1
< 0.1%
2523450 1
< 0.1%

급여금액
Real number (ℝ)

MISSING 

Distinct4565
Distinct (%)90.2%
Missing4939
Missing (%)49.4%
Infinite0
Infinite (%)0.0%
Mean17621159
Minimum0
Maximum1.0197384 × 108
Zeros17
Zeros (%)0.2%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-05-03T18:54:57.978884image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile5258250
Q111250350
median16047380
Q321711420
95-th percentile33868920
Maximum1.0197384 × 108
Range1.0197384 × 108
Interquartile range (IQR)10461070

Descriptive statistics

Standard deviation9696336.2
Coefficient of variation (CV)0.55026667
Kurtosis8.4546047
Mean17621159
Median Absolute Deviation (MAD)5162330
Skewness1.9740403
Sum8.9180684 × 1010
Variance9.4018937 × 1013
MonotonicityNot monotonic
2024-05-03T18:54:58.540108image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 17
 
0.2%
2800000 7
 
0.1%
5100000 4
 
< 0.1%
3000000 4
 
< 0.1%
10580870 3
 
< 0.1%
24499780 3
 
< 0.1%
5250000 3
 
< 0.1%
14570000 3
 
< 0.1%
4840000 3
 
< 0.1%
14510000 3
 
< 0.1%
Other values (4555) 5011
50.1%
(Missing) 4939
49.4%
ValueCountFrequency (%)
0 17
0.2%
1660310 1
 
< 0.1%
1880540 1
 
< 0.1%
1975000 1
 
< 0.1%
2010580 1
 
< 0.1%
2067397 1
 
< 0.1%
2080000 1
 
< 0.1%
2200000 2
 
< 0.1%
2225740 2
 
< 0.1%
2250000 2
 
< 0.1%
ValueCountFrequency (%)
101973840 1
< 0.1%
101928500 1
< 0.1%
90880520 1
< 0.1%
88031530 1
< 0.1%
84571850 1
< 0.1%
83078560 1
< 0.1%
79373916 1
< 0.1%
78725640 1
< 0.1%
78500000 1
< 0.1%
77787547 1
< 0.1%

기타급여금액
Real number (ℝ)

MISSING  ZEROS 

Distinct4583
Distinct (%)90.6%
Missing4939
Missing (%)49.4%
Infinite0
Infinite (%)0.0%
Mean3067436.8
Minimum-12598550
Maximum23035130
Zeros153
Zeros (%)1.5%
Negative3
Negative (%)< 0.1%
Memory size166.0 KiB
2024-05-03T18:54:59.067152image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum-12598550
5-th percentile353560
Q11869860
median2833940
Q33968370
95-th percentile6364250
Maximum23035130
Range35633680
Interquartile range (IQR)2098510

Descriptive statistics

Standard deviation1934411.5
Coefficient of variation (CV)0.63062799
Kurtosis7.6354294
Mean3067436.8
Median Absolute Deviation (MAD)1034370
Skewness1.5099681
Sum1.5524298 × 1010
Variance3.741948 × 1012
MonotonicityNot monotonic
2024-05-03T18:54:59.692655image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 153
 
1.5%
200000 19
 
0.2%
300000 8
 
0.1%
850000 6
 
0.1%
1200000 5
 
0.1%
500000 4
 
< 0.1%
800000 4
 
< 0.1%
100000 4
 
< 0.1%
400000 4
 
< 0.1%
729120 3
 
< 0.1%
Other values (4573) 4851
48.5%
(Missing) 4939
49.4%
ValueCountFrequency (%)
-12598550 1
 
< 0.1%
-997160 1
 
< 0.1%
-730420 1
 
< 0.1%
0 153
1.5%
29580 1
 
< 0.1%
36070 2
 
< 0.1%
50000 3
 
< 0.1%
54540 1
 
< 0.1%
75100 1
 
< 0.1%
87550 1
 
< 0.1%
ValueCountFrequency (%)
23035130 1
< 0.1%
18406090 1
< 0.1%
15800839 1
< 0.1%
14936230 1
< 0.1%
14815790 1
< 0.1%
14780950 1
< 0.1%
14776350 1
< 0.1%
13860100 1
< 0.1%
13828070 1
< 0.1%
13697280 1
< 0.1%

복지비용
Real number (ℝ)

MISSING  ZEROS 

Distinct3608
Distinct (%)71.3%
Missing4939
Missing (%)49.4%
Infinite0
Infinite (%)0.0%
Mean954945.89
Minimum-2994860
Maximum8180420
Zeros273
Zeros (%)2.7%
Negative4
Negative (%)< 0.1%
Memory size166.0 KiB
2024-05-03T18:55:00.268081image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum-2994860
5-th percentile0
Q1400000
median789900
Q31296890
95-th percentile2430260
Maximum8180420
Range11175280
Interquartile range (IQR)896890

Descriptive statistics

Standard deviation842934.29
Coefficient of variation (CV)0.88270372
Kurtosis9.2254981
Mean954945.89
Median Absolute Deviation (MAD)425060
Skewness2.2301196
Sum4.8329812 × 109
Variance7.1053822 × 1011
MonotonicityNot monotonic
2024-05-03T18:55:00.812531image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 273
 
2.7%
400000 99
 
1.0%
600000 86
 
0.9%
200000 63
 
0.6%
500000 55
 
0.5%
800000 54
 
0.5%
300000 52
 
0.5%
1000000 49
 
0.5%
700000 41
 
0.4%
1200000 39
 
0.4%
Other values (3598) 4250
42.5%
(Missing) 4939
49.4%
ValueCountFrequency (%)
-2994860 1
 
< 0.1%
-805640 1
 
< 0.1%
-294330 1
 
< 0.1%
-6820 1
 
< 0.1%
0 273
2.7%
3820 1
 
< 0.1%
4667 4
 
< 0.1%
5880 1
 
< 0.1%
10000 1
 
< 0.1%
12500 1
 
< 0.1%
ValueCountFrequency (%)
8180420 1
< 0.1%
7083940 1
< 0.1%
7034843 1
< 0.1%
6902010 1
< 0.1%
6897450 1
< 0.1%
6799700 1
< 0.1%
6636620 1
< 0.1%
6553180 1
< 0.1%
6507500 1
< 0.1%
6492213 1
< 0.1%

산재보험요금
Real number (ℝ)

MISSING  ZEROS 

Distinct4188
Distinct (%)82.8%
Missing4939
Missing (%)49.4%
Infinite0
Infinite (%)0.0%
Mean188761.69
Minimum-219267
Maximum1173670
Zeros194
Zeros (%)1.9%
Negative4
Negative (%)< 0.1%
Memory size166.0 KiB
2024-05-03T18:55:01.326456image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum-219267
5-th percentile39650
Q1118340
median172210
Q3238350
95-th percentile385670
Maximum1173670
Range1392937
Interquartile range (IQR)120010

Descriptive statistics

Standard deviation114445.06
Coefficient of variation (CV)0.60629388
Kurtosis7.5118492
Mean188761.69
Median Absolute Deviation (MAD)58590
Skewness1.7414601
Sum9.5532293 × 108
Variance1.3097672 × 1010
MonotonicityNot monotonic
2024-05-03T18:55:01.820471image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 194
 
1.9%
151880 5
 
0.1%
225990 4
 
< 0.1%
149350 4
 
< 0.1%
159350 4
 
< 0.1%
163050 3
 
< 0.1%
143250 3
 
< 0.1%
321740 3
 
< 0.1%
194190 3
 
< 0.1%
105000 3
 
< 0.1%
Other values (4178) 4835
48.4%
(Missing) 4939
49.4%
ValueCountFrequency (%)
-219267 1
 
< 0.1%
-192407 1
 
< 0.1%
-175640 1
 
< 0.1%
-40658 1
 
< 0.1%
0 194
1.9%
920 1
 
< 0.1%
4540 1
 
< 0.1%
19910 1
 
< 0.1%
20840 1
 
< 0.1%
22750 1
 
< 0.1%
ValueCountFrequency (%)
1173670 1
< 0.1%
1109650 2
< 0.1%
1095170 1
< 0.1%
1035770 1
< 0.1%
910710 1
< 0.1%
879210 1
< 0.1%
870920 1
< 0.1%
838920 1
< 0.1%
826250 1
< 0.1%
807750 1
< 0.1%

상여금액
Real number (ℝ)

MISSING  ZEROS 

Distinct262
Distinct (%)5.2%
Missing4939
Missing (%)49.4%
Infinite0
Infinite (%)0.0%
Mean86438.005
Minimum-662910
Maximum16144000
Zeros4758
Zeros (%)47.6%
Negative2
Negative (%)< 0.1%
Memory size166.0 KiB
2024-05-03T18:55:02.331573image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum-662910
5-th percentile0
Q10
median0
Q30
95-th percentile313130
Maximum16144000
Range16806910
Interquartile range (IQR)0

Descriptive statistics

Standard deviation552167.41
Coefficient of variation (CV)6.3880166
Kurtosis284.28413
Mean86438.005
Median Absolute Deviation (MAD)0
Skewness13.617688
Sum4.3746274 × 108
Variance3.0488885 × 1011
MonotonicityNot monotonic
2024-05-03T18:55:02.913094image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 4758
47.6%
100000 6
 
0.1%
282000 3
 
< 0.1%
1488660 3
 
< 0.1%
644966 2
 
< 0.1%
1100660 2
 
< 0.1%
700000 2
 
< 0.1%
409160 2
 
< 0.1%
300000 2
 
< 0.1%
685820 2
 
< 0.1%
Other values (252) 279
 
2.8%
(Missing) 4939
49.4%
ValueCountFrequency (%)
-662910 1
 
< 0.1%
-79284 1
 
< 0.1%
0 4758
47.6%
30000 1
 
< 0.1%
41490 1
 
< 0.1%
58680 1
 
< 0.1%
61670 2
 
< 0.1%
66500 1
 
< 0.1%
80780 1
 
< 0.1%
95000 2
 
< 0.1%
ValueCountFrequency (%)
16144000 1
< 0.1%
14429920 1
< 0.1%
9589420 1
< 0.1%
8684940 1
< 0.1%
6951098 1
< 0.1%
5268221 1
< 0.1%
5206275 1
< 0.1%
5150650 1
< 0.1%
5114945 1
< 0.1%
5014150 1
< 0.1%

퇴직금액
Real number (ℝ)

MISSING  ZEROS 

Distinct3979
Distinct (%)78.6%
Missing4939
Missing (%)49.4%
Infinite0
Infinite (%)0.0%
Mean1851921.6
Minimum-1790000
Maximum28467140
Zeros210
Zeros (%)2.1%
Negative2
Negative (%)< 0.1%
Memory size166.0 KiB
2024-05-03T18:55:03.371184image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum-1790000
5-th percentile252000
Q11124898
median1684732
Q32394150
95-th percentile3813934
Maximum28467140
Range30257140
Interquartile range (IQR)1269252

Descriptive statistics

Standard deviation1201727.7
Coefficient of variation (CV)0.64890854
Kurtosis52.12568
Mean1851921.6
Median Absolute Deviation (MAD)616872
Skewness3.4747439
Sum9.372575 × 109
Variance1.4441495 × 1012
MonotonicityNot monotonic
2024-05-03T18:55:03.872756image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 210
 
2.1%
1500000 21
 
0.2%
1000000 19
 
0.2%
1400000 16
 
0.2%
1300000 15
 
0.1%
1200000 15
 
0.1%
2500000 12
 
0.1%
2000000 12
 
0.1%
1800000 11
 
0.1%
500000 10
 
0.1%
Other values (3969) 4720
47.2%
(Missing) 4939
49.4%
ValueCountFrequency (%)
-1790000 1
 
< 0.1%
-358020 1
 
< 0.1%
0 210
2.1%
22595 1
 
< 0.1%
66000 1
 
< 0.1%
68190 1
 
< 0.1%
92450 1
 
< 0.1%
96640 1
 
< 0.1%
98580 1
 
< 0.1%
100000 1
 
< 0.1%
ValueCountFrequency (%)
28467140 1
< 0.1%
12312060 1
< 0.1%
11383770 1
< 0.1%
10453500 1
< 0.1%
9966670 1
< 0.1%
8232800 2
< 0.1%
8123290 1
< 0.1%
8016320 1
< 0.1%
7875700 1
< 0.1%
7854180 1
< 0.1%

Sample

발생년월단지명단지분류명단지전용면적합계단지코드도로명주소법정동주소법정동코드복도유형분양형태사용승인일세대수시공사명시군구명읍면동명리명시행사명연면적충당금월부과금액충당금월사용금액동수호수홈페이지주소135이상전용면적세대수135이하전용면적세대수60이하전용면적세대수85이하전용면적세대수관리방식관리금액부과면적관리사무소전화번호관리사무소팩스번호난방방식충당금액잔액청소비용경비원급여비용난방공용비용난방전용비용수도공용비용수도전용비용전기공용비용전기전용비용건강보험요금고용보험요금국민연금금액급여금액기타급여금액복지비용산재보험요금상여금액퇴직금액
20158202309양주현진에버빌1단지아파트37708.966A48205009경기도 양주시 고덕로 160경기도 양주시 덕계동 855 양주현진에버빌1단지4163011600계단식분양20070627418(주)현진양주시덕계동<NA>(주)ks건설59996.089<NA>084180550363위탁관리51782.203185996310318599632개별난방<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
2338202401금호1차아파트38666.64A47186010경기도 구리시 장자대로 38경기도 구리시 교문동 820 금호1차4131010400계단식분양20010831704금호<NA><NA><NA>군인공제회72201.692041600007704007040위탁관리57037.70503155673320315567333개별난방<NA>1232865018196010<NA><NA>-8665701353477010306690264214709826602683501000600200129004885890120031021465002600370
11863202311광주센트럴푸르지오아파트108314.2533A10026301경기도 광주시 경충대로1461번길 43경기도 광주시 쌍령동 503 광주센트럴푸르지오4161010200계단식분양201804271425대우건설광주시쌍령동<NA>쌍령피에프브이(주)205578.61431100764090200001814250001425위탁관리144210.9071031765813303181338135개별난방<NA>362716772400978600<NA><NA>12221697873268001494000429340101338033812690642914085967035838001960000
19911202309광명두산위브트레지움아파트114002.4164A42374401경기도 광명시 광덕산로 26경기도 광명시 하안동 863 광명두산위브트레지움4121010300계단식분양200911021248두산건설광명시하안동<NA>하안주공 본2단지 재건축조합216026.52<NA>091248광명두산위브트레지움.apti.co.kr106336250556위탁관리154180.9984028983338028984448개별난방<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
9112202312김포전원마을월드2단지아파트48096.4A41506009경기도 김포시 전원로 44경기도 김포시 운양동 1435 김포전원마을월드2단지4157010300계단식분양20000407442월드건설(주)<NA><NA><NA>월드건설(주)78100.6011671984010006442전원마을월드2단지.ma-um.co.kr6813668170위탁관리48096.403199805310319980532개별난방<NA>880655012844670<NA><NA>010065590481303022812260763952207628436785144897953981261156225817174002892761
11539202311동광모닝스카이아파트33354.657A46478806경기도 광주시 경충대로1127번길 15경기도 광주시 초월읍 쌍동리 392 동광모닝스카이4161025322계단식분양20050729378동광건설(주)광주시초월읍쌍동리용곡(주)43758.6863252601844946405378동광모닝스카이.ma-um.co.kr0600318위탁관리43487.2803176394380317639439개별난방<NA>56140001686622000<NA><NA>37678901930081041725012343022687078900004479040110625010301001017740
16725202310역북신원아침도시아파트아파트29250.7048A10025716경기도 용인시 처인구 낙은로 11경기도 용인처인구 역북동 795 역북신원아침도시아파트4146110200계단식분양20190201452신원종합건설용인처인구역북동<NA>용인2구역 주택재건축정비사업조합59966.2059<NA>2310005452ybswmorning.com00282170위탁관리59768.37803132302950313230296개별난방<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
19668202309비산삼성래미안아파트아파트365423.902A43105004경기도 안양시 동안구 관악대로 121경기도 안양동안구 비산동 425 비산삼성래미안아파트4117310100계단식분양200312243806삼성물산(주)건설부문안양동안구비산동<NA>비산주공2단지재건축주택조합642232.404<NA>271887000443806비산삼성래미안.apti.co.kr3049285742000위탁관리456004.94403146822000314689060지역난방<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
126202401무지개마을건영6단지아파트27647.16A46393404경기도 성남시 분당구 구미로 115경기도 성남분당구 구미동 225 무지개마을건영6단지4113511400계단식분양19950831208건영<NA><NA><NA>건영41004.0361005256013937000042086014800위탁관리33507.92403171748470317183436지역난방<NA>365948612274672<NA><NA>0340033074035908637140614090171350111100130510201928680100000013485001755150
16305202310한강신도시푸르지오아파트48646.6785A41574414경기도 김포시 김포한강11로 179경기도 김포시 운양동 1407-5 한강신도시푸르지오4157010300계단식분양20130614812대우건설김포시운양동<NA>아이랜드건설101211.899<NA>011812008120위탁관리66284.53103198698260319861197지역난방<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
발생년월단지명단지분류명단지전용면적합계단지코드도로명주소법정동주소법정동코드복도유형분양형태사용승인일세대수시공사명시군구명읍면동명리명시행사명연면적충당금월부과금액충당금월사용금액동수호수홈페이지주소135이상전용면적세대수135이하전용면적세대수60이하전용면적세대수85이하전용면적세대수관리방식관리금액부과면적관리사무소전화번호관리사무소팩스번호난방방식충당금액잔액청소비용경비원급여비용난방공용비용난방전용비용수도공용비용수도전용비용전기공용비용전기전용비용건강보험요금고용보험요금국민연금금액급여금액기타급여금액복지비용산재보험요금상여금액퇴직금액
6996202312합정주공4단지아파트27833.99A45076305경기도 평택시 평택3로 11경기도 평택시 합정동 829 합정주공4단지4122011700계단식분양19921110684대한주택공사<NA><NA><NA>대한주택공사34992.9387960604979800013684합정주공4단지.ma-um.co.kr006840위탁관리34494.10803165154160316535571개별난방<NA>795334012765720<NA><NA>-30000083678401115460049175014113028138011086800184779020000011779001233600
22495202309오남금호어울림아파트55198.8A47281523경기도 남양주시 진건오남로 472경기도 남양주시 오남읍 오남리 464 오남금호어울림4136026223계단식분양20060302711금호건설남양주시오남읍오남리(주)청록산업92581.0<NA>014711오남금호어울림.ma-um.co.kr00186525위탁관리55194.903157557830315755784개별난방<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
104202401분당시범삼성한신아파트아파트194255.61A46377208경기도 성남시 분당구 중앙공원로 53경기도 성남분당구 서현동 87 분당시범삼성한신아파트4113510500계단식분양199109301781삼성종합건설(주). 한신공영(주)<NA><NA><NA>삼성종합건설(주). 한신공영(주)238034.175040280011709500331781분당시범삼성한신.apti.co.kr249464210858위탁관리238032.17403170199090317021745지역난방<NA>31743410124447173<NA><NA>1378700278502003474225011022503018312134773001025668400387124451634587126042047504300281
3406202401유승아파트11022.45A46786302경기도 이천시 경충대로 2227-1경기도 이천시 부발읍 신하리 487-9 유승4150025328계단식분양20010807153유승종합건설<NA><NA><NA>대한주택보증17410.741054858002153유승.ma-um.co.kr007974위탁관리15062.97303163527920316382792개별난방<NA>16371405944962<NA><NA>0379623012963509228930208890609501287004750000729120498070487600570000
10080202311시화요진아파트43223.44A42978310경기도 시흥시 중심상가로 77경기도 시흥시 정왕동 1850 시화요진4139013200계단식분양19970909580요진산업시흥시정왕동<NA>요진산업63639.6418954800187000022580요진.ma-um.co.kr00240340위탁관리56250.003149978360315037886개별난방<NA>96930901684714600<NA><NA>490568823473120829170237020536660175825902804680110774019164001700000
7010202312오목천상송마을주공아파트52166.12A44176609경기도 수원시 권선구 오목천로 15경기도 수원권선구 오목천동 946 오목천상송마을주공4111312900복도식임대200510311185세양건설<NA><NA><NA>대한주택공사84216.417001311850011850위탁관리70456.202303122766890312276690개별난방<NA>1226982027607170<NA><NA>335550151431906269729345415801030220295950638370226090004348810024703002421780
17759202310양주옥정신도시1차대방노블랜드더시그니처아파트134007.6743A10024462경기도 양주시 회천남로 54경기도 양주시 옥정동 968 양주옥정신도시1차대방노블랜드더시그니처4163011400계단식분양202101141483주)대방건설양주시옥정동<NA>대방하우징(주)238889.1557<NA>63360000131483035401129위탁관리169870.040703185712100318571211지역난방<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
23560202309신한2차아파트25767.885A46786806경기도 이천시 경충대로 2216-33경기도 이천시 부발읍 신하리 362-3 신한2차4150025328계단식분양19980828349(주)신한건설이천시부발읍신하리(주)신한건설39768.401<NA>164340003349신한2차.ma-um.co.kr00155194위탁관리31195.10803163575310316358531개별난방<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
20546202309분당청솔마을주공6단지아파트39375.0A46372312경기도 성남시 분당구 미금로 246경기도 성남분당구 금곡동 126 분당청솔마을주공6단지4113511100복도식임대199408191250한국토지주택공사성남분당구금곡동<NA>한국토지주택공사57317.98<NA>0912500012500위탁관리57127.603171310380317145661지역난방<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
2974202401부천범박힐스테이트3단지아파트85823.54A42280404<NA>경기도 부천시소사구 범박동 155-1 부천범박힐스테이트3단지4119410300계단식분양200406251012기양건설산업(주)<NA><NA><NA>기양건설산업(주)144722.892550373050600000111012www.bh3town.or.kr01830829위탁관리113134.4203234109800323514228개별난방<NA>1996238034389900<NA><NA>0215038601073465060420270117465033163070020026665240352129087677026626003411080