Overview

Dataset statistics

Number of variables29
Number of observations46
Missing cells1
Missing cells (%)0.1%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory11.7 KiB
Average record size in memory259.9 B

Variable types

Categorical1
Text3
Numeric25

Dataset

Description인천광역시 부평구 개인서비스 요금입니다. 구분,품목명,규격 및 단위,전월평균,금월평균,차액,전월대비상승율,부평1동,부평2동,부평3동,부평4동,부평5동,부평6동,산곡1동,산곡2동,산곡3동,산곡4동,청천1동,청천2동,갈산1동,갈산2동,삼산1동,삼산2동,부개1동,부개2동,부개3동,일신동,십정1동,십정2동 기타서비스(21종),세탁료,신사복상하드라이크리닝(다림질 포함)
URLhttps://www.data.go.kr/data/15051638/fileData.do

Alerts

품목명 has 1 (2.2%) missing valuesMissing
전월평균 has unique valuesUnique
금월평균 has unique valuesUnique
차액 has 19 (41.3%) zerosZeros
부평2동 has 4 (8.7%) zerosZeros
부평3동 has 6 (13.0%) zerosZeros
부평4동 has 5 (10.9%) zerosZeros
부평5동 has 4 (8.7%) zerosZeros
부평6동 has 5 (10.9%) zerosZeros
산곡1동 has 15 (32.6%) zerosZeros
산곡2동 has 4 (8.7%) zerosZeros
산곡3동 has 11 (23.9%) zerosZeros
산곡4동 has 5 (10.9%) zerosZeros
청천1동 has 8 (17.4%) zerosZeros
청천2동 has 3 (6.5%) zerosZeros
갈산1동 has 8 (17.4%) zerosZeros
갈산2동 has 6 (13.0%) zerosZeros
삼산1동 has 5 (10.9%) zerosZeros
삼산2동 has 3 (6.5%) zerosZeros
부개1동 has 7 (15.2%) zerosZeros
부개2동 has 10 (21.7%) zerosZeros
부개3동 has 9 (19.6%) zerosZeros
일신동 has 12 (26.1%) zerosZeros
십정1동 has 9 (19.6%) zerosZeros
십정2동 has 9 (19.6%) zerosZeros

Reproduction

Analysis started2023-12-12 17:19:01.828367
Analysis finished2023-12-12 17:19:02.231420
Duration0.4 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

구분
Categorical

Distinct2
Distinct (%)4.3%
Missing0
Missing (%)0.0%
Memory size500.0 B
외식비(24종)
24 
기타서비스(21종)
22 

Length

Max length10
Median length8
Mean length8.9565217
Min length8

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row기타서비스(21종)
2nd row기타서비스(21종)
3rd row기타서비스(21종)
4th row기타서비스(21종)
5th row기타서비스(21종)

Common Values

ValueCountFrequency (%)
외식비(24종) 24
52.2%
기타서비스(21종) 22
47.8%

Length

2023-12-13T02:19:02.324438image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T02:19:02.464522image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
외식비(24종 24
52.2%
기타서비스(21종 22
47.8%

품목명
Text

MISSING 

Distinct42
Distinct (%)93.3%
Missing1
Missing (%)2.2%
Memory size500.0 B
2023-12-13T02:19:02.719936image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length20
Median length16
Mean length7.8
Min length3

Characters and Unicode

Total characters351
Distinct characters106
Distinct categories6 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique40 ?
Unique (%)88.9%

Sample

1st row세탁료
2nd row의복수선료
3rd row공동주택관리비(아파트,개별부과금제외)
4th row택배이용료
5th row볼링장이용료
ValueCountFrequency (%)
식 6
 
6.8%
탕 4
 
4.5%
이용료 3
 
3.4%
미용료 3
 
3.4%
삼 2
 
2.3%
김 2
 
2.3%
반 2
 
2.3%
자 2
 
2.3%
육 2
 
2.3%
밥 2
 
2.3%
Other values (54) 60
68.2%
2023-12-13T02:19:03.195993image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
135
38.5%
료 20
 
5.7%
용 12
 
3.4%
) 9
 
2.6%
이 9
 
2.6%
( 9
 
2.6%
외 7
 
2.0%
장 6
 
1.7%
식 6
 
1.7%
개 4
 
1.1%
Other values (96) 134
38.2%

Most occurring categories

ValueCountFrequency (%)
Other Letter 195
55.6%
Space Separator 135
38.5%
Close Punctuation 9
 
2.6%
Open Punctuation 9
 
2.6%
Uppercase Letter 2
 
0.6%
Other Punctuation 1
 
0.3%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
료 20
 
10.3%
용 12
 
6.2%
이 9
 
4.6%
외 7
 
3.6%
장 6
 
3.1%
식 6
 
3.1%
개 4
 
2.1%
탕 4
 
2.1%
비 4
 
2.1%
방 3
 
1.5%
Other values (90) 120
61.5%
Uppercase Letter
ValueCountFrequency (%)
C 1
50.0%
P 1
50.0%
Space Separator
ValueCountFrequency (%)
135
100.0%
Close Punctuation
ValueCountFrequency (%)
) 9
100.0%
Open Punctuation
ValueCountFrequency (%)
( 9
100.0%
Other Punctuation
ValueCountFrequency (%)
, 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 195
55.6%
Common 154
43.9%
Latin 2
 
0.6%

Most frequent character per script

Hangul
ValueCountFrequency (%)
료 20
 
10.3%
용 12
 
6.2%
이 9
 
4.6%
외 7
 
3.6%
장 6
 
3.1%
식 6
 
3.1%
개 4
 
2.1%
탕 4
 
2.1%
비 4
 
2.1%
방 3
 
1.5%
Other values (90) 120
61.5%
Common
ValueCountFrequency (%)
135
87.7%
) 9
 
5.8%
( 9
 
5.8%
, 1
 
0.6%
Latin
ValueCountFrequency (%)
C 1
50.0%
P 1
50.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 195
55.6%
ASCII 156
44.4%

Most frequent character per block

ASCII
ValueCountFrequency (%)
135
86.5%
) 9
 
5.8%
( 9
 
5.8%
, 1
 
0.6%
C 1
 
0.6%
P 1
 
0.6%
Hangul
ValueCountFrequency (%)
료 20
 
10.3%
용 12
 
6.2%
이 9
 
4.6%
외 7
 
3.6%
장 6
 
3.1%
식 6
 
3.1%
개 4
 
2.1%
탕 4
 
2.1%
비 4
 
2.1%
방 3
 
1.5%
Other values (90) 120
61.5%

규격 및 단위
Text

Distinct38
Distinct (%)82.6%
Missing0
Missing (%)0.0%
Memory size500.0 B
2023-12-13T02:19:03.503539image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length43
Median length19
Mean length11.73913
Min length3

Characters and Unicode

Total characters540
Distinct characters153
Distinct categories9 ?
Distinct scripts3 ?
Distinct blocks4 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique36 ?
Unique (%)78.3%

Sample

1st row신사복상하드라이크리닝(다림질 포함)
2nd row신사복 하의길이 수선(바지밑단줄임)
3rd row고층 약82.65㎡
4th row고층 약105.79㎡
5th row크기:중형(가로+세로+높이=140cm)무게:20kg이하, 타지역(특수지역제외)
ValueCountFrequency (%)
1인분(보통 12
 
13.3%
200g 4
 
4.4%
포함 4
 
4.4%
1인분 3
 
3.3%
홀 3
 
3.3%
1시간 2
 
2.2%
고층 2
 
2.2%
성인 2
 
2.2%
일반인 2
 
2.2%
평일 2
 
2.2%
Other values (54) 54
60.0%
2023-12-13T02:19:03.973712image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
44
 
8.1%
1 27
 
5.0%
인 26
 
4.8%
( 24
 
4.4%
) 24
 
4.4%
, 18
 
3.3%
분 16
 
3.0%
0 14
 
2.6%
보 13
 
2.4%
통 13
 
2.4%
Other values (143) 321
59.4%

Most occurring categories

ValueCountFrequency (%)
Other Letter 354
65.6%
Decimal Number 56
 
10.4%
Space Separator 44
 
8.1%
Open Punctuation 24
 
4.4%
Close Punctuation 24
 
4.4%
Other Punctuation 22
 
4.1%
Lowercase Letter 10
 
1.9%
Math Symbol 4
 
0.7%
Other Symbol 2
 
0.4%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
인 26
 
7.3%
분 16
 
4.5%
보 13
 
3.7%
통 13
 
3.7%
일 12
 
3.4%
성 12
 
3.4%
반 12
 
3.4%
기 11
 
3.1%
이 7
 
2.0%
지 7
 
2.0%
Other values (119) 225
63.6%
Decimal Number
ValueCountFrequency (%)
1 27
48.2%
0 14
25.0%
2 6
 
10.7%
5 2
 
3.6%
4 2
 
3.6%
9 1
 
1.8%
7 1
 
1.8%
6 1
 
1.8%
8 1
 
1.8%
3 1
 
1.8%
Lowercase Letter
ValueCountFrequency (%)
g 5
50.0%
c 2
 
20.0%
m 2
 
20.0%
k 1
 
10.0%
Other Punctuation
ValueCountFrequency (%)
, 18
81.8%
. 2
 
9.1%
: 2
 
9.1%
Math Symbol
ValueCountFrequency (%)
+ 2
50.0%
= 1
25.0%
× 1
25.0%
Space Separator
ValueCountFrequency (%)
44
100.0%
Open Punctuation
ValueCountFrequency (%)
( 24
100.0%
Close Punctuation
ValueCountFrequency (%)
) 24
100.0%
Other Symbol
ValueCountFrequency (%)
㎡ 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 354
65.6%
Common 176
32.6%
Latin 10
 
1.9%

Most frequent character per script

Hangul
ValueCountFrequency (%)
인 26
 
7.3%
분 16
 
4.5%
보 13
 
3.7%
통 13
 
3.7%
일 12
 
3.4%
성 12
 
3.4%
반 12
 
3.4%
기 11
 
3.1%
이 7
 
2.0%
지 7
 
2.0%
Other values (119) 225
63.6%
Common
ValueCountFrequency (%)
44
25.0%
1 27
15.3%
( 24
13.6%
) 24
13.6%
, 18
10.2%
0 14
 
8.0%
2 6
 
3.4%
. 2
 
1.1%
5 2
 
1.1%
㎡ 2
 
1.1%
Other values (10) 13
 
7.4%
Latin
ValueCountFrequency (%)
g 5
50.0%
c 2
 
20.0%
m 2
 
20.0%
k 1
 
10.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 354
65.6%
ASCII 183
33.9%
CJK Compat 2
 
0.4%
None 1
 
0.2%

Most frequent character per block

ASCII
ValueCountFrequency (%)
44
24.0%
1 27
14.8%
( 24
13.1%
) 24
13.1%
, 18
9.8%
0 14
 
7.7%
2 6
 
3.3%
g 5
 
2.7%
. 2
 
1.1%
5 2
 
1.1%
Other values (12) 17
 
9.3%
Hangul
ValueCountFrequency (%)
인 26
 
7.3%
분 16
 
4.5%
보 13
 
3.7%
통 13
 
3.7%
일 12
 
3.4%
성 12
 
3.4%
반 12
 
3.4%
기 11
 
3.1%
이 7
 
2.0%
지 7
 
2.0%
Other values (119) 225
63.6%
CJK Compat
ValueCountFrequency (%)
㎡ 2
100.0%
None
ValueCountFrequency (%)
× 1
100.0%

전월평균
Real number (ℝ)

UNIQUE 

Distinct46
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean21230.652
Minimum672
Maximum167778
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size546.0 B
2023-12-13T02:19:04.162768image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum672
5-th percentile2794
Q16668.25
median10622.5
Q317665.25
95-th percentile91617.5
Maximum167778
Range167106
Interquartile range (IQR)10997

Descriptive statistics

Standard deviation33428.879
Coefficient of variation (CV)1.5745573
Kurtosis11.160203
Mean21230.652
Median Absolute Deviation (MAD)4305.5
Skewness3.3163332
Sum976610
Variance1.1174899 × 109
MonotonicityNot monotonic
2023-12-13T02:19:04.346366image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=46)
ValueCountFrequency (%)
7239 1
 
2.2%
6867 1
 
2.2%
14019 1
 
2.2%
7930 1
 
2.2%
6909 1
 
2.2%
6602 1
 
2.2%
13281 1
 
2.2%
28898 1
 
2.2%
13750 1
 
2.2%
14684 1
 
2.2%
Other values (36) 36
78.3%
ValueCountFrequency (%)
672 1
2.2%
1271 1
2.2%
2752 1
2.2%
2920 1
2.2%
3718 1
2.2%
4398 1
2.2%
4500 1
2.2%
4906 1
2.2%
5669 1
2.2%
6509 1
2.2%
ValueCountFrequency (%)
167778 1
2.2%
138187 1
2.2%
107879 1
2.2%
42833 1
2.2%
42682 1
2.2%
38432 1
2.2%
33375 1
2.2%
29159 1
2.2%
28898 1
2.2%
21167 1
2.2%

금월평균
Real number (ℝ)

UNIQUE 

Distinct46
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean21242.261
Minimum672
Maximum167778
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size546.0 B
2023-12-13T02:19:04.515078image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum672
5-th percentile2793
Q16737
median10645
Q317804.5
95-th percentile91423.25
Maximum167778
Range167106
Interquartile range (IQR)11067.5

Descriptive statistics

Standard deviation33350.487
Coefficient of variation (CV)1.5700065
Kurtosis11.187189
Mean21242.261
Median Absolute Deviation (MAD)4301
Skewness3.3178061
Sum977144
Variance1.112255 × 109
MonotonicityNot monotonic
2023-12-13T02:19:04.708632image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=46)
ValueCountFrequency (%)
7257 1
 
2.2%
6938 1
 
2.2%
14043 1
 
2.2%
7964 1
 
2.2%
6977 1
 
2.2%
6670 1
 
2.2%
13316 1
 
2.2%
28875 1
 
2.2%
13945 1
 
2.2%
14684 1
 
2.2%
Other values (36) 36
78.3%
ValueCountFrequency (%)
672 1
2.2%
1329 1
2.2%
2752 1
2.2%
2916 1
2.2%
3695 1
2.2%
4420 1
2.2%
4500 1
2.2%
4906 1
2.2%
5776 1
2.2%
6509 1
2.2%
ValueCountFrequency (%)
167778 1
2.2%
137499 1
2.2%
107620 1
2.2%
42833 1
2.2%
42682 1
2.2%
38432 1
2.2%
33375 1
2.2%
29159 1
2.2%
28875 1
2.2%
21190 1
2.2%

차액
Real number (ℝ)

ZEROS 

Distinct21
Distinct (%)45.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean11.608696
Minimum-688
Maximum195
Zeros19
Zeros (%)41.3%
Negative6
Negative (%)13.0%
Memory size546.0 B
2023-12-13T02:19:04.915390image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum-688
5-th percentile-23.75
Q10
median0
Q355.5
95-th percentile139.75
Maximum195
Range883
Interquartile range (IQR)55.5

Descriptive statistics

Standard deviation124.9189
Coefficient of variation (CV)10.760804
Kurtosis22.594546
Mean11.608696
Median Absolute Deviation (MAD)23
Skewness-4.1116773
Sum534
Variance15604.732
MonotonicityNot monotonic
2023-12-13T02:19:05.078217image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=21)
ValueCountFrequency (%)
0 19
41.3%
68 3
 
6.5%
24 2
 
4.3%
45 2
 
4.3%
71 2
 
4.3%
23 2
 
4.3%
34 2
 
4.3%
195 1
 
2.2%
-5 1
 
2.2%
-23 1
 
2.2%
Other values (11) 11
23.9%
ValueCountFrequency (%)
-688 1
 
2.2%
-259 1
 
2.2%
-24 1
 
2.2%
-23 1
 
2.2%
-9 1
 
2.2%
-5 1
 
2.2%
0 19
41.3%
18 1
 
2.2%
23 2
 
4.3%
24 2
 
4.3%
ValueCountFrequency (%)
195 1
 
2.2%
167 1
 
2.2%
140 1
 
2.2%
139 1
 
2.2%
119 1
 
2.2%
107 1
 
2.2%
71 2
4.3%
68 3
6.5%
59 1
 
2.2%
45 2
4.3%

전월대비상승율
Text

Distinct26
Distinct (%)56.5%
Missing0
Missing (%)0.0%
Memory size500.0 B
2023-12-13T02:19:05.267174image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length6
Median length5
Mean length5.1304348
Min length5

Characters and Unicode

Total characters236
Distinct characters13
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

Unique23 ?
Unique (%)50.0%

Sample

1st row0.25%
2nd row0.51%
3rd row-0.24%
4th row-0.50%
5th row0.00%
ValueCountFrequency (%)
0.00 19
41.3%
0.88 2
 
4.3%
1.02 2
 
4.3%
0.08 1
 
2.2%
0.25 1
 
2.2%
0.26 1
 
2.2%
0.62 1
 
2.2%
0.06 1
 
2.2%
1.17 1
 
2.2%
0.28 1
 
2.2%
Other values (16) 16
34.8%
2023-12-13T02:19:05.569210image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 84
35.6%
. 46
19.5%
% 46
19.5%
1 13
 
5.5%
2 9
 
3.8%
8 9
 
3.8%
4 6
 
2.5%
- 6
 
2.5%
5 5
 
2.1%
6 5
 
2.1%
Other values (3) 7
 
3.0%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 138
58.5%
Other Punctuation 92
39.0%
Dash Punctuation 6
 
2.5%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 84
60.9%
1 13
 
9.4%
2 9
 
6.5%
8 9
 
6.5%
4 6
 
4.3%
5 5
 
3.6%
6 5
 
3.6%
3 3
 
2.2%
7 3
 
2.2%
9 1
 
0.7%
Other Punctuation
ValueCountFrequency (%)
. 46
50.0%
% 46
50.0%
Dash Punctuation
ValueCountFrequency (%)
- 6
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 236
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 84
35.6%
. 46
19.5%
% 46
19.5%
1 13
 
5.5%
2 9
 
3.8%
8 9
 
3.8%
4 6
 
2.5%
- 6
 
2.5%
5 5
 
2.1%
6 5
 
2.1%
Other values (3) 7
 
3.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 236
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 84
35.6%
. 46
19.5%
% 46
19.5%
1 13
 
5.5%
2 9
 
3.8%
8 9
 
3.8%
4 6
 
2.5%
- 6
 
2.5%
5 5
 
2.1%
6 5
 
2.1%
Other values (3) 7
 
3.0%

부평1동
Real number (ℝ)

Distinct39
Distinct (%)84.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean29051.087
Minimum1000
Maximum260000
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size546.0 B
2023-12-13T02:19:05.717702image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1000
5-th percentile3000
Q16812.5
median12750
Q320875
95-th percentile138750
Maximum260000
Range259000
Interquartile range (IQR)14062.5

Descriptive statistics

Standard deviation51007.303
Coefficient of variation (CV)1.7557795
Kurtosis11.635127
Mean29051.087
Median Absolute Deviation (MAD)6125
Skewness3.3629606
Sum1336350
Variance2.6017449 × 109
MonotonicityNot monotonic
2023-12-13T02:19:05.902507image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=39)
ValueCountFrequency (%)
6750 3
 
6.5%
8500 2
 
4.3%
18500 2
 
4.3%
19000 2
 
4.3%
8000 2
 
4.3%
3000 2
 
4.3%
3450 1
 
2.2%
15500 1
 
2.2%
28200 1
 
2.2%
3250 1
 
2.2%
Other values (29) 29
63.0%
ValueCountFrequency (%)
1000 1
 
2.2%
1250 1
 
2.2%
3000 2
4.3%
3250 1
 
2.2%
3450 1
 
2.2%
4500 1
 
2.2%
5000 1
 
2.2%
5800 1
 
2.2%
6750 3
6.5%
7000 1
 
2.2%
ValueCountFrequency (%)
260000 1
2.2%
197500 1
2.2%
160000 1
2.2%
75000 1
2.2%
62000 1
2.2%
57000 1
2.2%
52000 1
2.2%
33000 1
2.2%
32500 1
2.2%
28200 1
2.2%

부평2동
Real number (ℝ)

ZEROS 

Distinct39
Distinct (%)84.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean18618.478
Minimum0
Maximum250000
Zeros4
Zeros (%)8.7%
Negative0
Negative (%)0.0%
Memory size546.0 B
2023-12-13T02:19:06.069055image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q15550
median10000
Q317750
95-th percentile46000
Maximum250000
Range250000
Interquartile range (IQR)12200

Descriptive statistics

Standard deviation37107.018
Coefficient of variation (CV)1.993021
Kurtosis35.247446
Mean18618.478
Median Absolute Deviation (MAD)6075
Skewness5.6518603
Sum856450
Variance1.3769308 × 109
MonotonicityNot monotonic
2023-12-13T02:19:06.278723image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=39)
ValueCountFrequency (%)
0 4
 
8.7%
9000 2
 
4.3%
10000 2
 
4.3%
14000 2
 
4.3%
17000 2
 
4.3%
7000 1
 
2.2%
18000 1
 
2.2%
22600 1
 
2.2%
19000 1
 
2.2%
18500 1
 
2.2%
Other values (29) 29
63.0%
ValueCountFrequency (%)
0 4
8.7%
1200 1
 
2.2%
1500 1
 
2.2%
2500 1
 
2.2%
3500 1
 
2.2%
3850 1
 
2.2%
4500 1
 
2.2%
5000 1
 
2.2%
5500 1
 
2.2%
5700 1
 
2.2%
ValueCountFrequency (%)
250000 1
2.2%
60000 1
2.2%
48000 1
2.2%
40000 1
2.2%
37000 1
2.2%
30000 1
2.2%
25000 1
2.2%
22600 1
2.2%
20000 1
2.2%
19000 1
2.2%

부평3동
Real number (ℝ)

ZEROS 

Distinct34
Distinct (%)73.9%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean15357.239
Minimum0
Maximum131338
Zeros6
Zeros (%)13.0%
Negative0
Negative (%)0.0%
Memory size546.0 B
2023-12-13T02:19:06.457608image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q14062.5
median9000
Q314875
95-th percentile36875
Maximum131338
Range131338
Interquartile range (IQR)10812.5

Descriptive statistics

Standard deviation23783.32
Coefficient of variation (CV)1.5486716
Kurtosis14.955096
Mean15357.239
Median Absolute Deviation (MAD)5375
Skewness3.6513709
Sum706433
Variance5.6564632 × 108
MonotonicityNot monotonic
2023-12-13T02:19:06.631950image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=34)
ValueCountFrequency (%)
0 6
 
13.0%
12500 3
 
6.5%
8000 2
 
4.3%
30000 2
 
4.3%
6000 2
 
4.3%
9000 2
 
4.3%
12000 2
 
4.3%
9500 1
 
2.2%
1250 1
 
2.2%
3150 1
 
2.2%
Other values (24) 24
52.2%
ValueCountFrequency (%)
0 6
13.0%
1000 1
 
2.2%
1250 1
 
2.2%
2500 1
 
2.2%
3150 1
 
2.2%
3750 1
 
2.2%
4000 1
 
2.2%
4250 1
 
2.2%
4700 1
 
2.2%
5000 1
 
2.2%
ValueCountFrequency (%)
131338 1
2.2%
98045 1
2.2%
37500 1
2.2%
35000 1
2.2%
34500 1
2.2%
30000 2
4.3%
22000 1
2.2%
20000 1
2.2%
17500 1
2.2%
16000 1
2.2%

부평4동
Real number (ℝ)

ZEROS 

Distinct34
Distinct (%)73.9%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean14193.174
Minimum0
Maximum92800
Zeros5
Zeros (%)10.9%
Negative0
Negative (%)0.0%
Memory size546.0 B
2023-12-13T02:19:06.803208image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q14800
median9000
Q314750
95-th percentile48750
Maximum92800
Range92800
Interquartile range (IQR)9950

Descriptive statistics

Standard deviation18199.713
Coefficient of variation (CV)1.2822863
Kurtosis8.9932253
Mean14193.174
Median Absolute Deviation (MAD)4750
Skewness2.8368655
Sum652886
Variance3.3122955 × 108
MonotonicityNot monotonic
2023-12-13T02:19:06.982221image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=34)
ValueCountFrequency (%)
0 5
 
10.9%
9000 3
 
6.5%
10000 2
 
4.3%
6500 2
 
4.3%
13000 2
 
4.3%
1000 2
 
4.3%
7700 2
 
4.3%
8500 2
 
4.3%
13450 1
 
2.2%
7000 1
 
2.2%
Other values (24) 24
52.2%
ValueCountFrequency (%)
0 5
10.9%
1000 2
 
4.3%
3000 1
 
2.2%
3100 1
 
2.2%
4000 1
 
2.2%
4500 1
 
2.2%
4750 1
 
2.2%
4950 1
 
2.2%
5000 1
 
2.2%
6000 1
 
2.2%
ValueCountFrequency (%)
92800 1
2.2%
72500 1
2.2%
50000 1
2.2%
45000 1
2.2%
30000 1
2.2%
25222 1
2.2%
23500 1
2.2%
20000 1
2.2%
17900 1
2.2%
17709 1
2.2%

부평5동
Real number (ℝ)

ZEROS 

Distinct35
Distinct (%)76.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean17847.457
Minimum0
Maximum112000
Zeros4
Zeros (%)8.7%
Negative0
Negative (%)0.0%
Memory size546.0 B
2023-12-13T02:19:07.561738image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q15112.5
median9725
Q320725
95-th percentile58000
Maximum112000
Range112000
Interquartile range (IQR)15612.5

Descriptive statistics

Standard deviation22743.933
Coefficient of variation (CV)1.2743515
Kurtosis7.6107374
Mean17847.457
Median Absolute Deviation (MAD)6100
Skewness2.6084213
Sum820983
Variance5.1728651 × 108
MonotonicityNot monotonic
2023-12-13T02:19:07.687154image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=35)
ValueCountFrequency (%)
7000 4
 
8.7%
0 4
 
8.7%
6500 3
 
6.5%
58000 2
 
4.3%
15500 2
 
4.3%
15000 2
 
4.3%
28950 1
 
2.2%
5150 1
 
2.2%
19200 1
 
2.2%
3500 1
 
2.2%
Other values (25) 25
54.3%
ValueCountFrequency (%)
0 4
8.7%
500 1
 
2.2%
1000 1
 
2.2%
2650 1
 
2.2%
3500 1
 
2.2%
3750 1
 
2.2%
4500 1
 
2.2%
5000 1
 
2.2%
5100 1
 
2.2%
5150 1
 
2.2%
ValueCountFrequency (%)
112000 1
2.2%
91000 1
2.2%
58000 2
4.3%
45000 1
2.2%
34500 1
2.2%
30000 1
2.2%
28950 1
2.2%
25000 1
2.2%
23500 1
2.2%
23333 1
2.2%

부평6동
Real number (ℝ)

ZEROS 

Distinct33
Distinct (%)71.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean17356.413
Minimum0
Maximum145000
Zeros5
Zeros (%)10.9%
Negative0
Negative (%)0.0%
Memory size546.0 B
2023-12-13T02:19:07.818826image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q16000
median9000
Q314971.25
95-th percentile46875
Maximum145000
Range145000
Interquartile range (IQR)8971.25

Descriptive statistics

Standard deviation27723.923
Coefficient of variation (CV)1.5973302
Kurtosis13.477751
Mean17356.413
Median Absolute Deviation (MAD)5125
Skewness3.5353709
Sum798395
Variance7.6861589 × 108
MonotonicityNot monotonic
2023-12-13T02:19:07.950253image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=33)
ValueCountFrequency (%)
0 5
 
10.9%
9000 3
 
6.5%
14000 3
 
6.5%
10500 2
 
4.3%
7500 2
 
4.3%
6000 2
 
4.3%
7000 2
 
4.3%
10000 2
 
4.3%
8000 1
 
2.2%
16760 1
 
2.2%
Other values (23) 23
50.0%
ValueCountFrequency (%)
0 5
10.9%
500 1
 
2.2%
2350 1
 
2.2%
2700 1
 
2.2%
3250 1
 
2.2%
3750 1
 
2.2%
4500 1
 
2.2%
6000 2
 
4.3%
7000 2
 
4.3%
7500 2
 
4.3%
ValueCountFrequency (%)
145000 1
2.2%
122000 1
2.2%
47000 1
2.2%
46500 1
2.2%
40000 1
2.2%
37500 1
2.2%
35000 1
2.2%
24000 1
2.2%
16760 1
2.2%
16250 1
2.2%

산곡1동
Real number (ℝ)

ZEROS 

Distinct27
Distinct (%)58.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean13366.087
Minimum0
Maximum159440
Zeros15
Zeros (%)32.6%
Negative0
Negative (%)0.0%
Memory size546.0 B
2023-12-13T02:19:08.082744image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median6000
Q313725
95-th percentile38750
Maximum159440
Range159440
Interquartile range (IQR)13725

Descriptive statistics

Standard deviation29080.11
Coefficient of variation (CV)2.1756637
Kurtosis17.649329
Mean13366.087
Median Absolute Deviation (MAD)6000
Skewness4.0893109
Sum614840
Variance8.4565281 × 108
MonotonicityNot monotonic
2023-12-13T02:19:08.193419image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=27)
ValueCountFrequency (%)
0 15
32.6%
7500 2
 
4.3%
17000 2
 
4.3%
6000 2
 
4.3%
4000 2
 
4.3%
14000 2
 
4.3%
6500 1
 
2.2%
1500 1
 
2.2%
2250 1
 
2.2%
3500 1
 
2.2%
Other values (17) 17
37.0%
ValueCountFrequency (%)
0 15
32.6%
1500 1
 
2.2%
2250 1
 
2.2%
3500 1
 
2.2%
4000 2
 
4.3%
4300 1
 
2.2%
5750 1
 
2.2%
6000 2
 
4.3%
6250 1
 
2.2%
6500 1
 
2.2%
ValueCountFrequency (%)
159440 1
2.2%
120310 1
2.2%
40000 1
2.2%
35000 1
2.2%
30000 1
2.2%
18660 1
2.2%
17000 2
4.3%
15000 1
2.2%
14780 1
2.2%
14000 2
4.3%

산곡2동
Real number (ℝ)

ZEROS 

Distinct31
Distinct (%)67.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean16903.043
Minimum0
Maximum160000
Zeros4
Zeros (%)8.7%
Negative0
Negative (%)0.0%
Memory size546.0 B
2023-12-13T02:19:08.318225image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q16000
median7750
Q314587.5
95-th percentile75000
Maximum160000
Range160000
Interquartile range (IQR)8587.5

Descriptive statistics

Standard deviation29026.757
Coefficient of variation (CV)1.7172503
Kurtosis14.321708
Mean16903.043
Median Absolute Deviation (MAD)4250
Skewness3.6157687
Sum777540
Variance8.4255263 × 108
MonotonicityNot monotonic
2023-12-13T02:19:08.420334image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=31)
ValueCountFrequency (%)
7000 4
 
8.7%
0 4
 
8.7%
10000 2
 
4.3%
3800 2
 
4.3%
6000 2
 
4.3%
16000 2
 
4.3%
6500 2
 
4.3%
8000 2
 
4.3%
12000 2
 
4.3%
45000 2
 
4.3%
Other values (21) 22
47.8%
ValueCountFrequency (%)
0 4
8.7%
500 1
 
2.2%
1200 1
 
2.2%
2900 1
 
2.2%
3200 1
 
2.2%
3800 2
4.3%
4000 1
 
2.2%
6000 2
4.3%
6500 2
4.3%
7000 4
8.7%
ValueCountFrequency (%)
160000 1
2.2%
99840 1
2.2%
85000 1
2.2%
45000 2
4.3%
26000 1
2.2%
20000 1
2.2%
17000 1
2.2%
16000 2
4.3%
15000 1
2.2%
14950 1
2.2%

산곡3동
Real number (ℝ)

ZEROS 

Distinct26
Distinct (%)56.5%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean14537.609
Minimum0
Maximum142500
Zeros11
Zeros (%)23.9%
Negative0
Negative (%)0.0%
Memory size546.0 B
2023-12-13T02:19:08.522618image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q11375
median6500
Q314250
95-th percentile35000
Maximum142500
Range142500
Interquartile range (IQR)12875

Descriptive statistics

Standard deviation26980.378
Coefficient of variation (CV)1.8559021
Kurtosis15.618481
Mean14537.609
Median Absolute Deviation (MAD)6500
Skewness3.8376538
Sum668730
Variance7.2794082 × 108
MonotonicityNot monotonic
2023-12-13T02:19:08.622440image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=26)
ValueCountFrequency (%)
0 11
23.9%
6500 4
 
8.7%
12000 3
 
6.5%
7000 3
 
6.5%
2500 2
 
4.3%
35000 2
 
4.3%
6000 2
 
4.3%
142500 1
 
2.2%
26666 1
 
2.2%
3500 1
 
2.2%
Other values (16) 16
34.8%
ValueCountFrequency (%)
0 11
23.9%
1000 1
 
2.2%
2500 2
 
4.3%
3500 1
 
2.2%
4000 1
 
2.2%
4700 1
 
2.2%
6000 2
 
4.3%
6250 1
 
2.2%
6500 4
 
8.7%
7000 3
 
6.5%
ValueCountFrequency (%)
142500 1
2.2%
120000 1
2.2%
35000 2
4.3%
30000 1
2.2%
26666 1
2.2%
24950 1
2.2%
24000 1
2.2%
17500 1
2.2%
16000 1
2.2%
15000 1
2.2%

산곡4동
Real number (ℝ)

ZEROS 

Distinct33
Distinct (%)71.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean19214.13
Minimum0
Maximum150000
Zeros5
Zeros (%)10.9%
Negative0
Negative (%)0.0%
Memory size546.0 B
2023-12-13T02:19:08.726967image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q15300
median8925
Q315375
95-th percentile86498.75
Maximum150000
Range150000
Interquartile range (IQR)10075

Descriptive statistics

Standard deviation31812.587
Coefficient of variation (CV)1.6556871
Kurtosis10.355488
Mean19214.13
Median Absolute Deviation (MAD)5250
Skewness3.2172247
Sum883850
Variance1.0120407 × 109
MonotonicityNot monotonic
2023-12-13T02:19:08.835997image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=33)
ValueCountFrequency (%)
0 5
 
10.9%
7000 4
 
8.7%
12500 3
 
6.5%
15000 2
 
4.3%
9000 2
 
4.3%
7450 2
 
4.3%
3500 2
 
4.3%
16700 1
 
2.2%
8450 1
 
2.2%
4900 1
 
2.2%
Other values (23) 23
50.0%
ValueCountFrequency (%)
0 5
10.9%
1000 1
 
2.2%
3000 1
 
2.2%
3500 2
 
4.3%
4000 1
 
2.2%
4500 1
 
2.2%
4900 1
 
2.2%
6500 1
 
2.2%
7000 4
8.7%
7450 2
 
4.3%
ValueCountFrequency (%)
150000 1
2.2%
139385 1
2.2%
100665 1
2.2%
44000 1
2.2%
40000 1
2.2%
35000 1
2.2%
32500 1
2.2%
30000 1
2.2%
24500 1
2.2%
16700 1
2.2%

청천1동
Real number (ℝ)

ZEROS 

Distinct31
Distinct (%)67.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean11560.435
Minimum0
Maximum85000
Zeros8
Zeros (%)17.4%
Negative0
Negative (%)0.0%
Memory size546.0 B
2023-12-13T02:19:08.943355image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q14500
median7625
Q313375
95-th percentile30000
Maximum85000
Range85000
Interquartile range (IQR)8875

Descriptive statistics

Standard deviation13899.37
Coefficient of variation (CV)1.2023225
Kurtosis16.985657
Mean11560.435
Median Absolute Deviation (MAD)5000
Skewness3.5090001
Sum531780
Variance1.931925 × 108
MonotonicityNot monotonic
2023-12-13T02:19:09.038872image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=31)
ValueCountFrequency (%)
0 8
 
17.4%
7000 4
 
8.7%
30000 3
 
6.5%
6500 2
 
4.3%
13000 2
 
4.3%
7250 2
 
4.3%
17250 1
 
2.2%
6250 1
 
2.2%
24500 1
 
2.2%
7750 1
 
2.2%
Other values (21) 21
45.7%
ValueCountFrequency (%)
0 8
17.4%
2500 1
 
2.2%
2750 1
 
2.2%
3250 1
 
2.2%
4000 1
 
2.2%
6000 1
 
2.2%
6250 1
 
2.2%
6500 2
 
4.3%
7000 4
8.7%
7250 2
 
4.3%
ValueCountFrequency (%)
85000 1
 
2.2%
30000 3
6.5%
25000 1
 
2.2%
24500 1
 
2.2%
21700 1
 
2.2%
20000 1
 
2.2%
17980 1
 
2.2%
17250 1
 
2.2%
16500 1
 
2.2%
13500 1
 
2.2%

청천2동
Real number (ℝ)

ZEROS 

Distinct35
Distinct (%)76.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean20650
Minimum0
Maximum190000
Zeros3
Zeros (%)6.5%
Negative0
Negative (%)0.0%
Memory size546.0 B
2023-12-13T02:19:09.138206image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile87.5
Q15812.5
median9750
Q316875
95-th percentile81875
Maximum190000
Range190000
Interquartile range (IQR)11062.5

Descriptive statistics

Standard deviation34263.907
Coefficient of variation (CV)1.6592691
Kurtosis14.470257
Mean20650
Median Absolute Deviation (MAD)5750
Skewness3.5948056
Sum949900
Variance1.1740153 × 109
MonotonicityNot monotonic
2023-12-13T02:19:09.248044image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=35)
ValueCountFrequency (%)
0 3
 
6.5%
6500 3
 
6.5%
7000 2
 
4.3%
6000 2
 
4.3%
4000 2
 
4.3%
8000 2
 
4.3%
15500 2
 
4.3%
40000 2
 
4.3%
12000 2
 
4.3%
20500 1
 
2.2%
Other values (25) 25
54.3%
ValueCountFrequency (%)
0 3
6.5%
350 1
 
2.2%
1000 1
 
2.2%
2200 1
 
2.2%
3000 1
 
2.2%
4000 2
4.3%
4500 1
 
2.2%
5500 1
 
2.2%
5750 1
 
2.2%
6000 2
4.3%
ValueCountFrequency (%)
190000 1
2.2%
122500 1
2.2%
92500 1
2.2%
50000 1
2.2%
40000 2
4.3%
38000 1
2.2%
30000 1
2.2%
27500 1
2.2%
20500 1
2.2%
20000 1
2.2%

갈산1동
Real number (ℝ)

ZEROS 

Distinct26
Distinct (%)56.5%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean17329.457
Minimum0
Maximum150000
Zeros8
Zeros (%)17.4%
Negative0
Negative (%)0.0%
Memory size546.0 B
2023-12-13T02:19:09.358997image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q13625
median7000
Q314500
95-th percentile101388.75
Maximum150000
Range150000
Interquartile range (IQR)10875

Descriptive statistics

Standard deviation33397.513
Coefficient of variation (CV)1.9272107
Kurtosis10.597138
Mean17329.457
Median Absolute Deviation (MAD)4925
Skewness3.3585883
Sum797155
Variance1.1153939 × 109
MonotonicityNot monotonic
2023-12-13T02:19:09.469243image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=26)
ValueCountFrequency (%)
0 8
17.4%
6000 5
 
10.9%
25000 4
 
8.7%
7000 3
 
6.5%
15000 2
 
4.3%
5000 2
 
4.3%
8000 2
 
4.3%
11500 2
 
4.3%
16670 1
 
2.2%
4000 1
 
2.2%
Other values (16) 16
34.8%
ValueCountFrequency (%)
0 8
17.4%
900 1
 
2.2%
2750 1
 
2.2%
2900 1
 
2.2%
3500 1
 
2.2%
4000 1
 
2.2%
5000 2
 
4.3%
5500 1
 
2.2%
6000 5
10.9%
7000 3
 
6.5%
ValueCountFrequency (%)
150000 1
 
2.2%
140500 1
 
2.2%
125185 1
 
2.2%
30000 1
 
2.2%
25000 4
8.7%
20000 1
 
2.2%
16670 1
 
2.2%
15000 2
4.3%
13000 1
 
2.2%
12000 1
 
2.2%

갈산2동
Real number (ℝ)

ZEROS 

Distinct29
Distinct (%)63.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean12302.717
Minimum0
Maximum110600
Zeros6
Zeros (%)13.0%
Negative0
Negative (%)0.0%
Memory size546.0 B
2023-12-13T02:19:09.590009image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q14000
median7250
Q313862.5
95-th percentile31875
Maximum110600
Range110600
Interquartile range (IQR)9862.5

Descriptive statistics

Standard deviation18494.939
Coefficient of variation (CV)1.5033215
Kurtosis18.593886
Mean12302.717
Median Absolute Deviation (MAD)4950
Skewness3.9535263
Sum565925
Variance3.4206278 × 108
MonotonicityNot monotonic
2023-12-13T02:19:09.701330image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=29)
ValueCountFrequency (%)
0 6
 
13.0%
7000 5
 
10.9%
15000 3
 
6.5%
7500 3
 
6.5%
4500 2
 
4.3%
25000 2
 
4.3%
4000 2
 
4.3%
9000 2
 
4.3%
13450 1
 
2.2%
16500 1
 
2.2%
Other values (19) 19
41.3%
ValueCountFrequency (%)
0 6
13.0%
500 1
 
2.2%
1000 1
 
2.2%
2600 1
 
2.2%
2750 1
 
2.2%
3000 1
 
2.2%
4000 2
 
4.3%
4500 2
 
4.3%
5500 1
 
2.2%
5900 1
 
2.2%
ValueCountFrequency (%)
110600 1
 
2.2%
62925 1
 
2.2%
32500 1
 
2.2%
30000 1
 
2.2%
25000 2
4.3%
16500 1
 
2.2%
15000 3
6.5%
14500 1
 
2.2%
14000 1
 
2.2%
13450 1
 
2.2%

삼산1동
Real number (ℝ)

ZEROS 

Distinct33
Distinct (%)71.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean19008.261
Minimum0
Maximum215000
Zeros5
Zeros (%)10.9%
Negative0
Negative (%)0.0%
Memory size546.0 B
2023-12-13T02:19:09.808922image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q15537.5
median8250
Q315000
95-th percentile47500
Maximum215000
Range215000
Interquartile range (IQR)9462.5

Descriptive statistics

Standard deviation40028.367
Coefficient of variation (CV)2.1058406
Kurtosis18.054385
Mean19008.261
Median Absolute Deviation (MAD)4875
Skewness4.22156
Sum874380
Variance1.6022702 × 109
MonotonicityNot monotonic
2023-12-13T02:19:09.927273image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=33)
ValueCountFrequency (%)
0 5
 
10.9%
9000 3
 
6.5%
10500 3
 
6.5%
15000 3
 
6.5%
8000 2
 
4.3%
7500 2
 
4.3%
6750 2
 
4.3%
33000 1
 
2.2%
10330 1
 
2.2%
12000 1
 
2.2%
Other values (23) 23
50.0%
ValueCountFrequency (%)
0 5
10.9%
700 1
 
2.2%
1200 1
 
2.2%
2350 1
 
2.2%
3000 1
 
2.2%
3750 1
 
2.2%
4500 1
 
2.2%
5500 1
 
2.2%
5650 1
 
2.2%
5750 1
 
2.2%
ValueCountFrequency (%)
215000 1
2.2%
180000 1
2.2%
50000 1
2.2%
40000 1
2.2%
33000 1
2.2%
30000 1
2.2%
25000 1
2.2%
18000 1
2.2%
17200 1
2.2%
16950 1
2.2%

삼산2동
Real number (ℝ)

ZEROS 

Distinct39
Distinct (%)84.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean20494.109
Minimum0
Maximum140810
Zeros3
Zeros (%)6.5%
Negative0
Negative (%)0.0%
Memory size546.0 B
2023-12-13T02:19:10.039429image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile125
Q16312.5
median9750
Q318875
95-th percentile89875
Maximum140810
Range140810
Interquartile range (IQR)12562.5

Descriptive statistics

Standard deviation30568.404
Coefficient of variation (CV)1.4915703
Kurtosis7.962069
Mean20494.109
Median Absolute Deviation (MAD)6000
Skewness2.8279807
Sum942729
Variance9.3442734 × 108
MonotonicityNot monotonic
2023-12-13T02:19:10.176597image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=39)
ValueCountFrequency (%)
0 3
 
6.5%
7500 2
 
4.3%
9000 2
 
4.3%
10000 2
 
4.3%
4000 2
 
4.3%
16000 2
 
4.3%
27000 1
 
2.2%
12750 1
 
2.2%
25330 1
 
2.2%
15100 1
 
2.2%
Other values (29) 29
63.0%
ValueCountFrequency (%)
0 3
6.5%
500 1
 
2.2%
1000 1
 
2.2%
2350 1
 
2.2%
3250 1
 
2.2%
3500 1
 
2.2%
4000 2
4.3%
5000 1
 
2.2%
6250 1
 
2.2%
6500 1
 
2.2%
ValueCountFrequency (%)
140810 1
2.2%
126989 1
2.2%
100000 1
2.2%
59500 1
2.2%
54500 1
2.2%
49500 1
2.2%
30000 1
2.2%
27000 1
2.2%
25330 1
2.2%
20500 1
2.2%

부개1동
Real number (ℝ)

ZEROS 

Distinct27
Distinct (%)58.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean13262.391
Minimum0
Maximum148290
Zeros7
Zeros (%)15.2%
Negative0
Negative (%)0.0%
Memory size546.0 B
2023-12-13T02:19:10.303742image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q13937.5
median8000
Q314000
95-th percentile35625
Maximum148290
Range148290
Interquartile range (IQR)10062.5

Descriptive statistics

Standard deviation23430.1
Coefficient of variation (CV)1.7666573
Kurtosis25.441731
Mean13262.391
Median Absolute Deviation (MAD)6000
Skewness4.672628
Sum610070
Variance5.4896959 × 108
MonotonicityNot monotonic
2023-12-13T02:19:10.413735image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=27)
ValueCountFrequency (%)
0 7
15.2%
8000 6
 
13.0%
5000 5
 
10.9%
14000 3
 
6.5%
18000 2
 
4.3%
10000 2
 
4.3%
2250 1
 
2.2%
2000 1
 
2.2%
3750 1
 
2.2%
4750 1
 
2.2%
Other values (17) 17
37.0%
ValueCountFrequency (%)
0 7
15.2%
500 1
 
2.2%
1500 1
 
2.2%
2000 1
 
2.2%
2250 1
 
2.2%
3750 1
 
2.2%
4500 1
 
2.2%
4750 1
 
2.2%
5000 5
10.9%
5250 1
 
2.2%
ValueCountFrequency (%)
148290 1
2.2%
64380 1
2.2%
37500 1
2.2%
30000 1
2.2%
25000 1
2.2%
21000 1
2.2%
18000 2
4.3%
17500 1
2.2%
17000 1
2.2%
16000 1
2.2%

부개2동
Real number (ℝ)

ZEROS 

Distinct31
Distinct (%)67.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean14179.565
Minimum0
Maximum133450
Zeros10
Zeros (%)21.7%
Negative0
Negative (%)0.0%
Memory size546.0 B
2023-12-13T02:19:10.575233image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q11312.5
median7000
Q313937.5
95-th percentile49375
Maximum133450
Range133450
Interquartile range (IQR)12625

Descriptive statistics

Standard deviation25100.762
Coefficient of variation (CV)1.7702067
Kurtosis13.571874
Mean14179.565
Median Absolute Deviation (MAD)6275
Skewness3.5159663
Sum652260
Variance6.3004825 × 108
MonotonicityNot monotonic
2023-12-13T02:19:10.727454image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=31)
ValueCountFrequency (%)
0 10
21.7%
7000 3
 
6.5%
5750 3
 
6.5%
8000 2
 
4.3%
16000 2
 
4.3%
5800 1
 
2.2%
7250 1
 
2.2%
11000 1
 
2.2%
37500 1
 
2.2%
12500 1
 
2.2%
Other values (21) 21
45.7%
ValueCountFrequency (%)
0 10
21.7%
450 1
 
2.2%
1000 1
 
2.2%
2250 1
 
2.2%
2550 1
 
2.2%
3250 1
 
2.2%
3500 1
 
2.2%
5750 3
 
6.5%
5800 1
 
2.2%
6000 1
 
2.2%
ValueCountFrequency (%)
133450 1
2.2%
100860 1
2.2%
52500 1
2.2%
40000 1
2.2%
37500 1
2.2%
30000 1
2.2%
19000 1
2.2%
17400 1
2.2%
16000 2
4.3%
15000 1
2.2%

부개3동
Real number (ℝ)

ZEROS 

Distinct32
Distinct (%)69.6%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean16822.435
Minimum0
Maximum142370
Zeros9
Zeros (%)19.6%
Negative0
Negative (%)0.0%
Memory size546.0 B
2023-12-13T02:19:10.844316image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q13062.5
median8000
Q313375
95-th percentile85000
Maximum142370
Range142370
Interquartile range (IQR)10312.5

Descriptive statistics

Standard deviation30344.507
Coefficient of variation (CV)1.8038118
Kurtosis10.136559
Mean16822.435
Median Absolute Deviation (MAD)5175
Skewness3.203952
Sum773832
Variance9.2078908 × 108
MonotonicityNot monotonic
2023-12-13T02:19:10.994910image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=32)
ValueCountFrequency (%)
0 9
19.6%
8000 3
 
6.5%
12000 2
 
4.3%
9000 2
 
4.3%
40000 2
 
4.3%
6500 2
 
4.3%
22500 1
 
2.2%
13500 1
 
2.2%
13722 1
 
2.2%
7000 1
 
2.2%
Other values (22) 22
47.8%
ValueCountFrequency (%)
0 9
19.6%
1000 1
 
2.2%
2650 1
 
2.2%
3000 1
 
2.2%
3250 1
 
2.2%
3950 1
 
2.2%
4000 1
 
2.2%
4500 1
 
2.2%
5250 1
 
2.2%
6500 2
 
4.3%
ValueCountFrequency (%)
142370 1
2.2%
127040 1
2.2%
100000 1
2.2%
40000 2
4.3%
35000 1
2.2%
26000 1
2.2%
22500 1
2.2%
15000 1
2.2%
14500 1
2.2%
13722 1
2.2%

일신동
Real number (ℝ)

ZEROS 

Distinct27
Distinct (%)58.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean14982.609
Minimum0
Maximum150850
Zeros12
Zeros (%)26.1%
Negative0
Negative (%)0.0%
Memory size546.0 B
2023-12-13T02:19:11.125603image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q1562.5
median6750
Q312750
95-th percentile34875
Maximum150850
Range150850
Interquartile range (IQR)12187.5

Descriptive statistics

Standard deviation29676.078
Coefficient of variation (CV)1.9807016
Kurtosis16.109492
Mean14982.609
Median Absolute Deviation (MAD)6500
Skewness3.958759
Sum689200
Variance8.8066958 × 108
MonotonicityNot monotonic
2023-12-13T02:19:11.245858image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=27)
ValueCountFrequency (%)
0 12
26.1%
12000 3
 
6.5%
6750 3
 
6.5%
6250 2
 
4.3%
9000 2
 
4.3%
5750 2
 
4.3%
10000 2
 
4.3%
35000 1
 
2.2%
3100 1
 
2.2%
2250 1
 
2.2%
Other values (17) 17
37.0%
ValueCountFrequency (%)
0 12
26.1%
2250 1
 
2.2%
3100 1
 
2.2%
3500 1
 
2.2%
5000 1
 
2.2%
5750 2
 
4.3%
6250 2
 
4.3%
6500 1
 
2.2%
6750 3
 
6.5%
7500 1
 
2.2%
ValueCountFrequency (%)
150850 1
2.2%
140500 1
2.2%
35000 1
2.2%
34500 1
2.2%
30000 1
2.2%
25000 1
2.2%
24500 1
2.2%
23000 1
2.2%
20000 1
2.2%
16250 1
2.2%

십정1동
Real number (ℝ)

ZEROS 

Distinct28
Distinct (%)60.9%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean17703.261
Minimum0
Maximum150000
Zeros9
Zeros (%)19.6%
Negative0
Negative (%)0.0%
Memory size546.0 B
2023-12-13T02:19:11.363398image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q13250
median8000
Q311325
95-th percentile110512.5
Maximum150000
Range150000
Interquartile range (IQR)8075

Descriptive statistics

Standard deviation34249.536
Coefficient of variation (CV)1.9346456
Kurtosis9.9198277
Mean17703.261
Median Absolute Deviation (MAD)4250
Skewness3.2577803
Sum814350
Variance1.1730307 × 109
MonotonicityNot monotonic
2023-12-13T02:19:11.485738image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=28)
ValueCountFrequency (%)
0 9
19.6%
9000 3
 
6.5%
8000 3
 
6.5%
7500 3
 
6.5%
10750 2
 
4.3%
12500 2
 
4.3%
4000 2
 
4.3%
6250 2
 
4.3%
2850 1
 
2.2%
7250 1
 
2.2%
Other values (18) 18
39.1%
ValueCountFrequency (%)
0 9
19.6%
500 1
 
2.2%
2850 1
 
2.2%
3000 1
 
2.2%
4000 2
 
4.3%
6000 1
 
2.2%
6250 2
 
4.3%
7000 1
 
2.2%
7250 1
 
2.2%
7500 3
 
6.5%
ValueCountFrequency (%)
150000 1
2.2%
140800 1
2.2%
132500 1
2.2%
44550 1
2.2%
32500 1
2.2%
30000 1
2.2%
23000 1
2.2%
22500 1
2.2%
20000 1
2.2%
12500 2
4.3%

십정2동
Real number (ℝ)

ZEROS 

Distinct26
Distinct (%)56.5%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean9321.7391
Minimum0
Maximum42000
Zeros9
Zeros (%)19.6%
Negative0
Negative (%)0.0%
Memory size546.0 B
2023-12-13T02:19:11.663779image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q12150
median6500
Q311075
95-th percentile33750
Maximum42000
Range42000
Interquartile range (IQR)8925

Descriptive statistics

Standard deviation10895.385
Coefficient of variation (CV)1.1688146
Kurtosis2.6388601
Mean9321.7391
Median Absolute Deviation (MAD)4550
Skewness1.7823583
Sum428800
Variance1.1870941 × 108
MonotonicityNot monotonic
2023-12-13T02:19:11.770534image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=26)
ValueCountFrequency (%)
0 9
19.6%
7000 3
 
6.5%
4000 3
 
6.5%
6500 3
 
6.5%
30000 2
 
4.3%
9500 2
 
4.3%
13000 2
 
4.3%
42000 2
 
4.3%
7500 2
 
4.3%
4750 2
 
4.3%
Other values (16) 16
34.8%
ValueCountFrequency (%)
0 9
19.6%
350 1
 
2.2%
1000 1
 
2.2%
2000 1
 
2.2%
2600 1
 
2.2%
3550 1
 
2.2%
4000 3
 
6.5%
4750 2
 
4.3%
5000 1
 
2.2%
5500 1
 
2.2%
ValueCountFrequency (%)
42000 2
4.3%
35000 1
2.2%
30000 2
4.3%
25500 1
2.2%
18000 1
2.2%
15000 1
2.2%
13000 2
4.3%
12500 1
2.2%
11100 1
2.2%
11000 1
2.2%

Sample

구분품목명규격 및 단위전월평균금월평균차액전월대비상승율부평1동부평2동부평3동부평4동부평5동부평6동산곡1동산곡2동산곡3동산곡4동청천1동청천2동갈산1동갈산2동삼산1동삼산2동부개1동부개2동부개3동일신동십정1동십정2동
0기타서비스(21종)세탁료신사복상하드라이크리닝(다림질 포함)72397257180.25%7000700080006000700090006500700070007000650070008000590072507700800058008000800090007000
1기타서비스(21종)의복수선료신사복 하의길이 수선(바지밑단줄임)43984420230.51%5000450042504000450045004000400040004000250040008000450045005000500035004500500040004000
2기타서비스(21종)공동주택관리비(아파트,개별부과금제외)고층 약82.65㎡107879107620-259-0.24%160000098045725009100012200012031085000120000100665300009250012518562925180000126989643801008601270401405001325000
3기타서비스(21종)<NA>고층 약105.79㎡138187137499-688-0.50%19750001313389280011200014500015944099840142500139385850001225001405001106002150001408101482901334501423701508501408000
4기타서비스(21종)택배이용료크기:중형(가로+세로+높이=140cm)무게:20kg이하, 타지역(특수지역제외)7413741300.00%9000650040001300012000105000750004500700000300009000060006700850004000
5기타서비스(21종)볼링장이용료일반인 평일 1게임오후기준(신발대여료 제외)4906490600.00%45000003750040000000100000400055003500004000000
6기타서비스(21종)골프연습장이용료초급반(남자)회원 1개월이용권16777816777800.00%2600002500000000016000001500000190000150000001000000010000001500000
7기타서비스(21종)당구장이용료일반인, 저녁시간, 1시간9365936500.00%85001200095009000900090007700720012000125001040070001150001050010000700009000900090007500
8기타서비스(21종)노래방이용료성인, 저녁시간대, 일반실 기본1시간291592915900.00%19000250003000030000300003500030000200003000030000250003000025000300003000030000300003000040000300003250030000
9기타서비스(21종)PC방이용료기본 1시간12711329594.42%1250120012501000100000120010001000010005000100012001000150010001000001000
구분품목명규격 및 단위전월평균금월평균차액전월대비상승율부평1동부평2동부평3동부평4동부평5동부평6동산곡1동산곡2동산곡3동산곡4동청천1동청천2동갈산1동갈산2동삼산1동삼산2동부개1동부개2동부개3동일신동십정1동십정2동
36외식비(24종)탕 수 육일반탕수육(중, 홀)2116721190240.11%1800018000220002000023500240000260002400024500245002050015000165001650027000210001900026000230002300013000
37외식비(24종)돈 가 스일반돈가스, 1인분80308052230.28%16950900065009000945080007500700070008500775065007000750090007250800070008000575075007000
38외식비(24종)생선초밥1인분(보통), 활어기준14120142871671.17%155001495001250019900135001400014950015500900016500150001500015000130001000000000
39외식비(24종)튀 김 닭후라이드 1마리1512015111-9-0.06%185001600017500134501920010500170001700017500140001725092001300013450169502050016000160001450016250107507950
40외식비(24종)햄 버 거기본형4500450000.00%3450570047004950515027004300290047004900850045002900450056504000450003950003550
41외식비(24종)피 자기본형(라지사이즈)15848159881400.88%2820015950124501790028950845012900990024950167002170016400012700172001345012900174001090010000107500
42외식비(24종)칼 국 수1인분(보통)6509650900.00%8500600060004750650060005750725060008450650060005500750080006250475057509000650072505000
43외식비(24종)라 면(외 식)일반 보통라면, 1인분37183695-23-0.62%3250350037504500350037503500380035003500400040003500400037504000375032503000350040004000
44외식비(24종)김 밥일반김밥, 1인분2752275200.00%3000250025003000265032502250380025003000275030002750275030003250200022503250225028502000
45외식비(24종)커 피(외 식)일반원두커피 1잔29202916-5-0.16%3000385031503100510023501500320025003500325022004000260023502350225025502650310030002600