Overview

Dataset statistics

Number of variables39
Number of observations45
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory15.5 KiB
Average record size in memory351.9 B

Variable types

Numeric37
Text2

Dataset

Description부천시 관내 개인서비스요금 현황에 대한 데이터로 외식비 24종, 서비스업 21종에 대한 광역동별 평균 금액 등의 정보를 제공합니다.
Author경기도 부천시
URLhttps://www.data.go.kr/data/3079356/fileData.do

Alerts

연번 has unique valuesUnique
품목 has unique valuesUnique
심곡2동 has 2 (4.4%) zerosZeros
심곡1동 has 12 (26.7%) zerosZeros
심곡3동 has 21 (46.7%) zerosZeros
원미1동 has 9 (20.0%) zerosZeros
원미2동 has 10 (22.2%) zerosZeros
역곡1동 has 9 (20.0%) zerosZeros
역곡2동 has 11 (24.4%) zerosZeros
도당동 has 5 (11.1%) zerosZeros
춘의동 has 4 (8.9%) zerosZeros
중동 has 3 (6.7%) zerosZeros
중2동 has 4 (8.9%) zerosZeros
상동 has 4 (8.9%) zerosZeros
상2동 has 5 (11.1%) zerosZeros
약대동 has 9 (20.0%) zerosZeros
중1동 has 4 (8.9%) zerosZeros
중3동 has 13 (28.9%) zerosZeros
상1동 has 4 (8.9%) zerosZeros
중4동 has 10 (22.2%) zerosZeros
상3동 has 6 (13.3%) zerosZeros
심곡본동 has 7 (15.6%) zerosZeros
심곡본1동 has 11 (24.4%) zerosZeros
소사본동 has 6 (13.3%) zerosZeros
소사동 has 13 (28.9%) zerosZeros
송내1동 has 7 (15.6%) zerosZeros
송내2동 has 7 (15.6%) zerosZeros
범박동 has 8 (17.8%) zerosZeros
소사본3동 has 8 (17.8%) zerosZeros
역곡3동 has 6 (13.3%) zerosZeros
괴안동 has 14 (31.1%) zerosZeros
성곡동 has 9 (20.0%) zerosZeros
고강본동 has 7 (15.6%) zerosZeros
고강1동 has 11 (24.4%) zerosZeros
원종1동 has 9 (20.0%) zerosZeros
원종2동 has 8 (17.8%) zerosZeros
오정동 has 9 (20.0%) zerosZeros
신흥동 has 10 (22.2%) zerosZeros

Reproduction

Analysis started2023-12-11 23:05:31.780733
Analysis finished2023-12-11 23:05:32.232422
Duration0.45 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

연번
Real number (ℝ)

UNIQUE 

Distinct45
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean23
Minimum1
Maximum45
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size537.0 B
2023-12-12T08:05:32.327570image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile3.2
Q112
median23
Q334
95-th percentile42.8
Maximum45
Range44
Interquartile range (IQR)22

Descriptive statistics

Standard deviation13.133926
Coefficient of variation (CV)0.57104024
Kurtosis-1.2
Mean23
Median Absolute Deviation (MAD)11
Skewness0
Sum1035
Variance172.5
MonotonicityStrictly increasing
2023-12-12T08:05:32.478656image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=45)
ValueCountFrequency (%)
1 1
 
2.2%
35 1
 
2.2%
26 1
 
2.2%
27 1
 
2.2%
28 1
 
2.2%
29 1
 
2.2%
30 1
 
2.2%
31 1
 
2.2%
32 1
 
2.2%
33 1
 
2.2%
Other values (35) 35
77.8%
ValueCountFrequency (%)
1 1
2.2%
2 1
2.2%
3 1
2.2%
4 1
2.2%
5 1
2.2%
6 1
2.2%
7 1
2.2%
8 1
2.2%
9 1
2.2%
10 1
2.2%
ValueCountFrequency (%)
45 1
2.2%
44 1
2.2%
43 1
2.2%
42 1
2.2%
41 1
2.2%
40 1
2.2%
39 1
2.2%
38 1
2.2%
37 1
2.2%
36 1
2.2%

품목
Text

UNIQUE 

Distinct45
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size492.0 B
2023-12-12T08:05:32.687493image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length8
Median length7
Mean length4.8
Min length2

Characters and Unicode

Total characters216
Distinct characters106
Distinct categories5 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique45 ?
Unique (%)100.0%

Sample

1st row설렁탕
2nd row냉 면
3rd row비빔밥
4th row갈비탕
5th row삼계탕
ValueCountFrequency (%)
이용료 6
 
11.5%
설렁탕 1
 
1.9%
택배수수료 1
 
1.9%
세탁료 1
 
1.9%
의복수선료 1
 
1.9%
숙박(호텔 1
 
1.9%
숙박(여관 1
 
1.9%
미용료(파마 1
 
1.9%
미용료(컷트 1
 
1.9%
목욕료 1
 
1.9%
Other values (37) 37
71.2%
2023-12-12T08:05:33.078802image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
료 19
 
8.8%
용 10
 
4.6%
) 9
 
4.2%
( 9
 
4.2%
이 8
 
3.7%
7
 
3.2%
장 7
 
3.2%
수 6
 
2.8%
외 5
 
2.3%
식 5
 
2.3%
Other values (96) 131
60.6%

Most occurring categories

ValueCountFrequency (%)
Other Letter 189
87.5%
Close Punctuation 9
 
4.2%
Open Punctuation 9
 
4.2%
Space Separator 7
 
3.2%
Uppercase Letter 2
 
0.9%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
료 19
 
10.1%
용 10
 
5.3%
이 8
 
4.2%
장 7
 
3.7%
수 6
 
3.2%
외 5
 
2.6%
식 5
 
2.6%
탕 4
 
2.1%
방 3
 
1.6%
김 3
 
1.6%
Other values (91) 119
63.0%
Uppercase Letter
ValueCountFrequency (%)
P 1
50.0%
C 1
50.0%
Close Punctuation
ValueCountFrequency (%)
) 9
100.0%
Open Punctuation
ValueCountFrequency (%)
( 9
100.0%
Space Separator
ValueCountFrequency (%)
7
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 189
87.5%
Common 25
 
11.6%
Latin 2
 
0.9%

Most frequent character per script

Hangul
ValueCountFrequency (%)
료 19
 
10.1%
용 10
 
5.3%
이 8
 
4.2%
장 7
 
3.7%
수 6
 
3.2%
외 5
 
2.6%
식 5
 
2.6%
탕 4
 
2.1%
방 3
 
1.6%
김 3
 
1.6%
Other values (91) 119
63.0%
Common
ValueCountFrequency (%)
) 9
36.0%
( 9
36.0%
7
28.0%
Latin
ValueCountFrequency (%)
P 1
50.0%
C 1
50.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 189
87.5%
ASCII 27
 
12.5%

Most frequent character per block

Hangul
ValueCountFrequency (%)
료 19
 
10.1%
용 10
 
5.3%
이 8
 
4.2%
장 7
 
3.7%
수 6
 
3.2%
외 5
 
2.6%
식 5
 
2.6%
탕 4
 
2.1%
방 3
 
1.6%
김 3
 
1.6%
Other values (91) 119
63.0%
ASCII
ValueCountFrequency (%)
) 9
33.3%
( 9
33.3%
7
25.9%
P 1
 
3.7%
C 1
 
3.7%

규격
Text

Distinct40
Distinct (%)88.9%
Missing0
Missing (%)0.0%
Memory size492.0 B
2023-12-12T08:05:33.424700image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length26
Median length20
Mean length13.711111
Min length5

Characters and Unicode

Total characters617
Distinct characters162
Distinct categories7 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique38 ?
Unique (%)84.4%

Sample

1st row1인분(보통)
2nd row물냉면. 1인분(보통)
3rd row1인분(보통)
4th row1인분(보통)
5th row닭1마리. 1인분(보통)
ValueCountFrequency (%)
1인분(보통 7
 
6.0%
1회 5
 
4.3%
1인분 3
 
2.6%
1그릇 3
 
2.6%
1시간 3
 
2.6%
일반인 3
 
2.6%
중화요리점 3
 
2.6%
전문점 3
 
2.6%
중류급 2
 
1.7%
정도 2
 
1.7%
Other values (77) 83
70.9%
2023-12-12T08:05:33.804391image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
73
 
11.8%
1 47
 
7.6%
. 40
 
6.5%
인 25
 
4.1%
) 17
 
2.8%
( 17
 
2.8%
분 16
 
2.6%
일 12
 
1.9%
0 11
 
1.8%
회 11
 
1.8%
Other values (152) 348
56.4%

Most occurring categories

ValueCountFrequency (%)
Other Letter 395
64.0%
Space Separator 73
 
11.8%
Decimal Number 66
 
10.7%
Other Punctuation 40
 
6.5%
Close Punctuation 17
 
2.8%
Open Punctuation 17
 
2.8%
Lowercase Letter 9
 
1.5%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
인 25
 
6.3%
분 16
 
4.1%
일 12
 
3.0%
회 11
 
2.8%
반 10
 
2.5%
중 10
 
2.5%
기 10
 
2.5%
시 9
 
2.3%
통 9
 
2.3%
보 8
 
2.0%
Other values (137) 275
69.6%
Decimal Number
ValueCountFrequency (%)
1 47
71.2%
0 11
 
16.7%
2 5
 
7.6%
4 1
 
1.5%
6 1
 
1.5%
3 1
 
1.5%
Lowercase Letter
ValueCountFrequency (%)
g 5
55.6%
c 1
 
11.1%
m 1
 
11.1%
x 1
 
11.1%
k 1
 
11.1%
Space Separator
ValueCountFrequency (%)
73
100.0%
Other Punctuation
ValueCountFrequency (%)
. 40
100.0%
Close Punctuation
ValueCountFrequency (%)
) 17
100.0%
Open Punctuation
ValueCountFrequency (%)
( 17
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 395
64.0%
Common 213
34.5%
Latin 9
 
1.5%

Most frequent character per script

Hangul
ValueCountFrequency (%)
인 25
 
6.3%
분 16
 
4.1%
일 12
 
3.0%
회 11
 
2.8%
반 10
 
2.5%
중 10
 
2.5%
기 10
 
2.5%
시 9
 
2.3%
통 9
 
2.3%
보 8
 
2.0%
Other values (137) 275
69.6%
Common
ValueCountFrequency (%)
73
34.3%
1 47
22.1%
. 40
18.8%
) 17
 
8.0%
( 17
 
8.0%
0 11
 
5.2%
2 5
 
2.3%
4 1
 
0.5%
6 1
 
0.5%
3 1
 
0.5%
Latin
ValueCountFrequency (%)
g 5
55.6%
c 1
 
11.1%
m 1
 
11.1%
x 1
 
11.1%
k 1
 
11.1%

Most occurring blocks

ValueCountFrequency (%)
Hangul 395
64.0%
ASCII 222
36.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
73
32.9%
1 47
21.2%
. 40
18.0%
) 17
 
7.7%
( 17
 
7.7%
0 11
 
5.0%
2 5
 
2.3%
g 5
 
2.3%
4 1
 
0.5%
c 1
 
0.5%
Other values (5) 5
 
2.3%
Hangul
ValueCountFrequency (%)
인 25
 
6.3%
분 16
 
4.1%
일 12
 
3.0%
회 11
 
2.8%
반 10
 
2.5%
중 10
 
2.5%
기 10
 
2.5%
시 9
 
2.3%
통 9
 
2.3%
보 8
 
2.0%
Other values (137) 275
69.6%

심곡2동
Real number (ℝ)

ZEROS 

Distinct28
Distinct (%)62.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean17377.778
Minimum0
Maximum150000
Zeros2
Zeros (%)4.4%
Negative0
Negative (%)0.0%
Memory size537.0 B
2023-12-12T08:05:33.903956image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile2060
Q16000
median9800
Q316000
95-th percentile58000
Maximum150000
Range150000
Interquartile range (IQR)10000

Descriptive statistics

Standard deviation26035.56
Coefficient of variation (CV)1.49821
Kurtosis16.190734
Mean17377.778
Median Absolute Deviation (MAD)5300
Skewness3.753406
Sum782000
Variance6.778504 × 108
MonotonicityNot monotonic
2023-12-12T08:05:33.997420image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=28)
ValueCountFrequency (%)
8000 5
 
11.1%
15000 4
 
8.9%
7000 2
 
4.4%
11000 2
 
4.4%
0 2
 
4.4%
10000 2
 
4.4%
30000 2
 
4.4%
4000 2
 
4.4%
14000 2
 
4.4%
8500 2
 
4.4%
Other values (18) 20
44.4%
ValueCountFrequency (%)
0 2
4.4%
2000 1
2.2%
2300 1
2.2%
2500 1
2.2%
3000 1
2.2%
3500 1
2.2%
4000 2
4.4%
4500 2
4.4%
6000 1
2.2%
7000 2
4.4%
ValueCountFrequency (%)
150000 1
2.2%
90000 1
2.2%
60000 1
2.2%
50000 1
2.2%
30000 2
4.4%
25000 1
2.2%
21000 1
2.2%
19900 1
2.2%
17000 2
4.4%
16000 1
2.2%

심곡1동
Real number (ℝ)

ZEROS 

Distinct21
Distinct (%)46.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean8451.1111
Minimum0
Maximum60000
Zeros12
Zeros (%)26.7%
Negative0
Negative (%)0.0%
Memory size537.0 B
2023-12-12T08:05:34.093770image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median6500
Q310000
95-th percentile28000
Maximum60000
Range60000
Interquartile range (IQR)10000

Descriptive statistics

Standard deviation11211.431
Coefficient of variation (CV)1.3266222
Kurtosis10.571718
Mean8451.1111
Median Absolute Deviation (MAD)3500
Skewness2.9204009
Sum380300
Variance1.2569619 × 108
MonotonicityNot monotonic
2023-12-12T08:05:34.181322image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=21)
ValueCountFrequency (%)
0 12
26.7%
8000 6
13.3%
10000 3
 
6.7%
3500 3
 
6.7%
7000 2
 
4.4%
9000 2
 
4.4%
5000 2
 
4.4%
13000 2
 
4.4%
40000 1
 
2.2%
60000 1
 
2.2%
Other values (11) 11
24.4%
ValueCountFrequency (%)
0 12
26.7%
1200 1
 
2.2%
3500 3
 
6.7%
4000 1
 
2.2%
4500 1
 
2.2%
4700 1
 
2.2%
5000 2
 
4.4%
6000 1
 
2.2%
6500 1
 
2.2%
7000 2
 
4.4%
ValueCountFrequency (%)
60000 1
 
2.2%
40000 1
 
2.2%
30000 1
 
2.2%
20000 1
 
2.2%
17000 1
 
2.2%
15900 1
 
2.2%
14000 1
 
2.2%
13000 2
4.4%
10000 3
6.7%
9000 2
4.4%

심곡3동
Real number (ℝ)

ZEROS 

Distinct17
Distinct (%)37.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean7015.5556
Minimum0
Maximum60000
Zeros21
Zeros (%)46.7%
Negative0
Negative (%)0.0%
Memory size537.0 B
2023-12-12T08:05:34.277569image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median3500
Q310000
95-th percentile22400
Maximum60000
Range60000
Interquartile range (IQR)10000

Descriptive statistics

Standard deviation11035.458
Coefficient of variation (CV)1.5729985
Kurtosis11.467166
Mean7015.5556
Median Absolute Deviation (MAD)3500
Skewness2.9139661
Sum315700
Variance1.2178134 × 108
MonotonicityNot monotonic
2023-12-12T08:05:34.361048image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=17)
ValueCountFrequency (%)
0 21
46.7%
7000 4
 
8.9%
10000 3
 
6.7%
20000 2
 
4.4%
8000 2
 
4.4%
15000 2
 
4.4%
23000 1
 
2.2%
16000 1
 
2.2%
4500 1
 
2.2%
3500 1
 
2.2%
Other values (7) 7
 
15.6%
ValueCountFrequency (%)
0 21
46.7%
1200 1
 
2.2%
3500 1
 
2.2%
4500 1
 
2.2%
5000 1
 
2.2%
5500 1
 
2.2%
6000 1
 
2.2%
7000 4
 
8.9%
8000 2
 
4.4%
10000 3
 
6.7%
ValueCountFrequency (%)
60000 1
 
2.2%
30000 1
 
2.2%
23000 1
 
2.2%
20000 2
4.4%
17000 1
 
2.2%
16000 1
 
2.2%
15000 2
4.4%
10000 3
6.7%
8000 2
4.4%
7000 4
8.9%

원미1동
Real number (ℝ)

ZEROS 

Distinct20
Distinct (%)44.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean12640
Minimum0
Maximum200000
Zeros9
Zeros (%)20.0%
Negative0
Negative (%)0.0%
Memory size537.0 B
2023-12-12T08:05:34.478719image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q13000
median8000
Q312000
95-th percentile30000
Maximum200000
Range200000
Interquartile range (IQR)9000

Descriptive statistics

Standard deviation29786.478
Coefficient of variation (CV)2.3565252
Kurtosis37.597402
Mean12640
Median Absolute Deviation (MAD)4500
Skewness5.9226605
Sum568800
Variance8.8723427 × 108
MonotonicityNot monotonic
2023-12-12T08:05:34.593280image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=20)
ValueCountFrequency (%)
0 9
20.0%
8000 6
13.3%
6000 3
 
6.7%
3500 3
 
6.7%
9000 3
 
6.7%
12000 3
 
6.7%
15000 3
 
6.7%
13000 2
 
4.4%
30000 2
 
4.4%
18000 1
 
2.2%
Other values (10) 10
22.2%
ValueCountFrequency (%)
0 9
20.0%
1000 1
 
2.2%
2500 1
 
2.2%
3000 1
 
2.2%
3500 3
 
6.7%
3800 1
 
2.2%
4500 1
 
2.2%
5000 1
 
2.2%
6000 3
 
6.7%
8000 6
13.3%
ValueCountFrequency (%)
200000 1
 
2.2%
40000 1
 
2.2%
30000 2
4.4%
18000 1
 
2.2%
15000 3
6.7%
13000 2
4.4%
12000 3
6.7%
11000 1
 
2.2%
9500 1
 
2.2%
9000 3
6.7%

원미2동
Real number (ℝ)

ZEROS 

Distinct25
Distinct (%)55.6%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean8527.7778
Minimum0
Maximum40000
Zeros10
Zeros (%)22.2%
Negative0
Negative (%)0.0%
Memory size537.0 B
2023-12-12T08:05:34.723269image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q11000
median6000
Q313000
95-th percentile28600
Maximum40000
Range40000
Interquartile range (IQR)12000

Descriptive statistics

Standard deviation9304.0042
Coefficient of variation (CV)1.0910233
Kurtosis3.0965694
Mean8527.7778
Median Absolute Deviation (MAD)6000
Skewness1.683242
Sum383750
Variance86564495
MonotonicityNot monotonic
2023-12-12T08:05:34.855573image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=25)
ValueCountFrequency (%)
0 10
22.2%
6000 4
 
8.9%
15000 4
 
8.9%
3000 3
 
6.7%
13000 2
 
4.4%
9000 2
 
4.4%
8000 2
 
4.4%
40000 1
 
2.2%
450 1
 
2.2%
1000 1
 
2.2%
Other values (15) 15
33.3%
ValueCountFrequency (%)
0 10
22.2%
450 1
 
2.2%
1000 1
 
2.2%
2500 1
 
2.2%
2900 1
 
2.2%
3000 3
 
6.7%
4000 1
 
2.2%
5000 1
 
2.2%
5500 1
 
2.2%
6000 4
 
8.9%
ValueCountFrequency (%)
40000 1
 
2.2%
35000 1
 
2.2%
30000 1
 
2.2%
23000 1
 
2.2%
19000 1
 
2.2%
15000 4
8.9%
14000 1
 
2.2%
13000 2
4.4%
12000 1
 
2.2%
11000 1
 
2.2%

역곡1동
Real number (ℝ)

ZEROS 

Distinct24
Distinct (%)53.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean9428.8889
Minimum0
Maximum60000
Zeros9
Zeros (%)20.0%
Negative0
Negative (%)0.0%
Memory size537.0 B
2023-12-12T08:05:34.961634image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q12500
median6500
Q311900
95-th percentile37000
Maximum60000
Range60000
Interquartile range (IQR)9400

Descriptive statistics

Standard deviation12388.569
Coefficient of variation (CV)1.3138949
Kurtosis8.1498824
Mean9428.8889
Median Absolute Deviation (MAD)4500
Skewness2.7429763
Sum424300
Variance1.5347665 × 108
MonotonicityNot monotonic
2023-12-12T08:05:35.069551image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=24)
ValueCountFrequency (%)
0 9
20.0%
8000 5
 
11.1%
6500 4
 
8.9%
12000 3
 
6.7%
7000 3
 
6.7%
6000 2
 
4.4%
11900 2
 
4.4%
3000 1
 
2.2%
60000 1
 
2.2%
400 1
 
2.2%
Other values (14) 14
31.1%
ValueCountFrequency (%)
0 9
20.0%
400 1
 
2.2%
2000 1
 
2.2%
2500 1
 
2.2%
3000 1
 
2.2%
3900 1
 
2.2%
4000 1
 
2.2%
4200 1
 
2.2%
4600 1
 
2.2%
6000 2
 
4.4%
ValueCountFrequency (%)
60000 1
 
2.2%
50000 1
 
2.2%
40000 1
 
2.2%
25000 1
 
2.2%
18000 1
 
2.2%
15000 1
 
2.2%
13000 1
 
2.2%
12000 3
6.7%
11900 2
4.4%
10000 1
 
2.2%

역곡2동
Real number (ℝ)

ZEROS 

Distinct20
Distinct (%)44.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean13295.556
Minimum0
Maximum220000
Zeros11
Zeros (%)24.4%
Negative0
Negative (%)0.0%
Memory size537.0 B
2023-12-12T08:05:35.178879image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q13000
median6000
Q312000
95-th percentile41000
Maximum220000
Range220000
Interquartile range (IQR)9000

Descriptive statistics

Standard deviation33459.283
Coefficient of variation (CV)2.5165765
Kurtosis34.856394
Mean13295.556
Median Absolute Deviation (MAD)6000
Skewness5.6709505
Sum598300
Variance1.1195236 × 109
MonotonicityNot monotonic
2023-12-12T08:05:35.270548image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=20)
ValueCountFrequency (%)
0 11
24.4%
7000 5
11.1%
13000 4
 
8.9%
6000 4
 
8.9%
3000 3
 
6.7%
8000 3
 
6.7%
4500 2
 
4.4%
17000 1
 
2.2%
5000 1
 
2.2%
15000 1
 
2.2%
Other values (10) 10
22.2%
ValueCountFrequency (%)
0 11
24.4%
3000 3
 
6.7%
3900 1
 
2.2%
4000 1
 
2.2%
4500 2
 
4.4%
5000 1
 
2.2%
6000 4
 
8.9%
7000 5
11.1%
8000 3
 
6.7%
10000 1
 
2.2%
ValueCountFrequency (%)
220000 1
 
2.2%
60000 1
 
2.2%
45000 1
 
2.2%
25000 1
 
2.2%
17500 1
 
2.2%
17000 1
 
2.2%
15000 1
 
2.2%
13000 4
8.9%
12000 1
 
2.2%
10900 1
 
2.2%

도당동
Real number (ℝ)

ZEROS 

Distinct22
Distinct (%)48.9%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean15442.222
Minimum0
Maximum235000
Zeros5
Zeros (%)11.1%
Negative0
Negative (%)0.0%
Memory size537.0 B
2023-12-12T08:05:35.371997image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q14000
median9000
Q313000
95-th percentile29000
Maximum235000
Range235000
Interquartile range (IQR)9000

Descriptive statistics

Standard deviation35110.737
Coefficient of variation (CV)2.2736842
Kurtosis36.694832
Mean15442.222
Median Absolute Deviation (MAD)4000
Skewness5.8445449
Sum694900
Variance1.2327639 × 109
MonotonicityNot monotonic
2023-12-12T08:05:35.731490image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=22)
ValueCountFrequency (%)
9000 5
 
11.1%
0 5
 
11.1%
3000 4
 
8.9%
10000 3
 
6.7%
25000 3
 
6.7%
8000 3
 
6.7%
7000 3
 
6.7%
22000 2
 
4.4%
12000 2
 
4.4%
13000 2
 
4.4%
Other values (12) 13
28.9%
ValueCountFrequency (%)
0 5
11.1%
400 1
 
2.2%
1000 1
 
2.2%
3000 4
8.9%
4000 1
 
2.2%
5000 1
 
2.2%
6000 2
 
4.4%
6500 1
 
2.2%
7000 3
6.7%
8000 3
6.7%
ValueCountFrequency (%)
235000 1
 
2.2%
60000 1
 
2.2%
30000 1
 
2.2%
25000 3
6.7%
22000 2
4.4%
15000 1
 
2.2%
14000 1
 
2.2%
13000 2
4.4%
12000 2
4.4%
11000 1
 
2.2%

춘의동
Real number (ℝ)

ZEROS 

Distinct24
Distinct (%)53.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean15431.111
Minimum0
Maximum250000
Zeros4
Zeros (%)8.9%
Negative0
Negative (%)0.0%
Memory size537.0 B
2023-12-12T08:05:35.850346image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q14000
median8000
Q312000
95-th percentile28600
Maximum250000
Range250000
Interquartile range (IQR)8000

Descriptive statistics

Standard deviation37494.635
Coefficient of variation (CV)2.4298078
Kurtosis36.811721
Mean15431.111
Median Absolute Deviation (MAD)4000
Skewness5.8796553
Sum694400
Variance1.4058476 × 109
MonotonicityNot monotonic
2023-12-12T08:05:35.959772image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=24)
ValueCountFrequency (%)
10000 6
13.3%
7000 6
13.3%
3000 4
 
8.9%
0 4
 
8.9%
8000 3
 
6.7%
4000 2
 
4.4%
13000 2
 
4.4%
9000 2
 
4.4%
30000 1
 
2.2%
70000 1
 
2.2%
Other values (14) 14
31.1%
ValueCountFrequency (%)
0 4
8.9%
400 1
 
2.2%
1000 1
 
2.2%
2500 1
 
2.2%
3000 4
8.9%
4000 2
 
4.4%
5500 1
 
2.2%
6000 1
 
2.2%
7000 6
13.3%
8000 3
6.7%
ValueCountFrequency (%)
250000 1
2.2%
70000 1
2.2%
30000 1
2.2%
23000 1
2.2%
21000 1
2.2%
20000 1
2.2%
19000 1
2.2%
18000 1
2.2%
15000 1
2.2%
13000 2
4.4%

중동
Real number (ℝ)

ZEROS 

Distinct29
Distinct (%)64.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean15513.333
Minimum0
Maximum150000
Zeros3
Zeros (%)6.7%
Negative0
Negative (%)0.0%
Memory size537.0 B
2023-12-12T08:05:36.054391image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile80
Q15000
median8000
Q314000
95-th percentile56000
Maximum150000
Range150000
Interquartile range (IQR)9000

Descriptive statistics

Standard deviation25766.809
Coefficient of variation (CV)1.660946
Kurtosis17.784256
Mean15513.333
Median Absolute Deviation (MAD)4100
Skewness3.9478554
Sum698100
Variance6.6392845 × 108
MonotonicityNot monotonic
2023-12-12T08:05:36.159733image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=29)
ValueCountFrequency (%)
8000 4
 
8.9%
5000 3
 
6.7%
9000 3
 
6.7%
0 3
 
6.7%
15000 3
 
6.7%
14000 3
 
6.7%
7000 2
 
4.4%
12000 2
 
4.4%
6000 2
 
4.4%
85000 1
 
2.2%
Other values (19) 19
42.2%
ValueCountFrequency (%)
0 3
6.7%
400 1
 
2.2%
500 1
 
2.2%
2000 1
 
2.2%
3000 1
 
2.2%
3500 1
 
2.2%
3900 1
 
2.2%
4900 1
 
2.2%
5000 3
6.7%
5100 1
 
2.2%
ValueCountFrequency (%)
150000 1
 
2.2%
85000 1
 
2.2%
60000 1
 
2.2%
40000 1
 
2.2%
35000 1
 
2.2%
22000 1
 
2.2%
20000 1
 
2.2%
18000 1
 
2.2%
15000 3
6.7%
14000 3
6.7%

중2동
Real number (ℝ)

ZEROS 

Distinct25
Distinct (%)55.6%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean14975.556
Minimum0
Maximum150000
Zeros4
Zeros (%)8.9%
Negative0
Negative (%)0.0%
Memory size537.0 B
2023-12-12T08:05:36.263653image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q14100
median8000
Q315000
95-th percentile47000
Maximum150000
Range150000
Interquartile range (IQR)10900

Descriptive statistics

Standard deviation25896.21
Coefficient of variation (CV)1.729232
Kurtosis18.535965
Mean14975.556
Median Absolute Deviation (MAD)4000
Skewness4.094988
Sum673900
Variance6.7061371 × 108
MonotonicityNot monotonic
2023-12-12T08:05:36.376066image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=25)
ValueCountFrequency (%)
8000 4
 
8.9%
18000 4
 
8.9%
0 4
 
8.9%
10000 4
 
8.9%
6000 3
 
6.7%
9000 3
 
6.7%
15000 2
 
4.4%
12000 2
 
4.4%
7000 2
 
4.4%
3000 2
 
4.4%
Other values (15) 15
33.3%
ValueCountFrequency (%)
0 4
8.9%
500 1
 
2.2%
1000 1
 
2.2%
2500 1
 
2.2%
3000 2
4.4%
3900 1
 
2.2%
4000 1
 
2.2%
4100 1
 
2.2%
4500 1
 
2.2%
6000 3
6.7%
ValueCountFrequency (%)
150000 1
 
2.2%
95000 1
 
2.2%
50000 1
 
2.2%
35000 1
 
2.2%
24000 1
 
2.2%
20000 1
 
2.2%
18000 4
8.9%
15000 2
4.4%
12000 2
4.4%
10000 4
8.9%

상동
Real number (ℝ)

ZEROS 

Distinct27
Distinct (%)60.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean16133.333
Minimum0
Maximum120000
Zeros4
Zeros (%)8.9%
Negative0
Negative (%)0.0%
Memory size537.0 B
2023-12-12T08:05:36.506492image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q15000
median9000
Q315000
95-th percentile81000
Maximum120000
Range120000
Interquartile range (IQR)10000

Descriptive statistics

Standard deviation25033.823
Coefficient of variation (CV)1.5516832
Kurtosis9.8444464
Mean16133.333
Median Absolute Deviation (MAD)6000
Skewness3.1759399
Sum726000
Variance6.2669227 × 108
MonotonicityNot monotonic
2023-12-12T08:05:36.624431image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=27)
ValueCountFrequency (%)
15000 5
 
11.1%
9000 4
 
8.9%
0 4
 
8.9%
5500 3
 
6.7%
16000 3
 
6.7%
5000 2
 
4.4%
10000 2
 
4.4%
13000 2
 
4.4%
8000 2
 
4.4%
90000 1
 
2.2%
Other values (17) 17
37.8%
ValueCountFrequency (%)
0 4
8.9%
1000 1
 
2.2%
2000 1
 
2.2%
2200 1
 
2.2%
3000 1
 
2.2%
3500 1
 
2.2%
4500 1
 
2.2%
5000 2
4.4%
5500 3
6.7%
6500 1
 
2.2%
ValueCountFrequency (%)
120000 1
 
2.2%
100000 1
 
2.2%
90000 1
 
2.2%
45000 1
 
2.2%
23000 1
 
2.2%
20000 1
 
2.2%
17000 1
 
2.2%
16000 3
6.7%
15000 5
11.1%
13000 2
 
4.4%

상2동
Real number (ℝ)

ZEROS 

Distinct29
Distinct (%)64.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean20206.667
Minimum0
Maximum362000
Zeros5
Zeros (%)11.1%
Negative0
Negative (%)0.0%
Memory size537.0 B
2023-12-12T08:05:36.727152image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q14100
median8000
Q313400
95-th percentile56000
Maximum362000
Range362000
Interquartile range (IQR)9300

Descriptive statistics

Standard deviation55679.437
Coefficient of variation (CV)2.7554984
Kurtosis34.055141
Mean20206.667
Median Absolute Deviation (MAD)5000
Skewness5.6310873
Sum909300
Variance3.1001997 × 109
MonotonicityNot monotonic
2023-12-12T08:05:36.833231image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=29)
ValueCountFrequency (%)
6000 5
 
11.1%
0 5
 
11.1%
9000 4
 
8.9%
8000 3
 
6.7%
12000 3
 
6.7%
17000 2
 
4.4%
362000 1
 
2.2%
5000 1
 
2.2%
60000 1
 
2.2%
40000 1
 
2.2%
Other values (19) 19
42.2%
ValueCountFrequency (%)
0 5
11.1%
300 1
 
2.2%
1000 1
 
2.2%
1500 1
 
2.2%
2000 1
 
2.2%
2500 1
 
2.2%
3000 1
 
2.2%
4100 1
 
2.2%
4500 1
 
2.2%
5000 1
 
2.2%
ValueCountFrequency (%)
362000 1
2.2%
120000 1
2.2%
60000 1
2.2%
40000 1
2.2%
22000 1
2.2%
21000 1
2.2%
20000 1
2.2%
17000 2
4.4%
16000 1
2.2%
15000 1
2.2%

약대동
Real number (ℝ)

ZEROS 

Distinct26
Distinct (%)57.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean10962.222
Minimum0
Maximum60000
Zeros9
Zeros (%)20.0%
Negative0
Negative (%)0.0%
Memory size537.0 B
2023-12-12T08:05:36.949178image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q12500
median8000
Q314000
95-th percentile37000
Maximum60000
Range60000
Interquartile range (IQR)11500

Descriptive statistics

Standard deviation12277.572
Coefficient of variation (CV)1.1199893
Kurtosis6.046987
Mean10962.222
Median Absolute Deviation (MAD)5500
Skewness2.237241
Sum493300
Variance1.5073877 × 108
MonotonicityNot monotonic
2023-12-12T08:05:37.054661image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=26)
ValueCountFrequency (%)
0 9
20.0%
8000 3
 
6.7%
7000 3
 
6.7%
9000 3
 
6.7%
2500 3
 
6.7%
15000 2
 
4.4%
12000 2
 
4.4%
14000 2
 
4.4%
9900 1
 
2.2%
60000 1
 
2.2%
Other values (16) 16
35.6%
ValueCountFrequency (%)
0 9
20.0%
2500 3
 
6.7%
3500 1
 
2.2%
4000 1
 
2.2%
5000 1
 
2.2%
5500 1
 
2.2%
7000 3
 
6.7%
7500 1
 
2.2%
8000 3
 
6.7%
9000 3
 
6.7%
ValueCountFrequency (%)
60000 1
2.2%
45000 1
2.2%
40000 1
2.2%
25000 1
2.2%
24000 1
2.2%
22000 1
2.2%
19000 1
2.2%
17900 1
2.2%
15000 2
4.4%
14000 2
4.4%

중1동
Real number (ℝ)

ZEROS 

Distinct27
Distinct (%)60.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean14646.667
Minimum0
Maximum80000
Zeros4
Zeros (%)8.9%
Negative0
Negative (%)0.0%
Memory size537.0 B
2023-12-12T08:05:37.159493image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q16000
median9000
Q316000
95-th percentile56600
Maximum80000
Range80000
Interquartile range (IQR)10000

Descriptive statistics

Standard deviation17524.173
Coefficient of variation (CV)1.1964615
Kurtosis5.9270401
Mean14646.667
Median Absolute Deviation (MAD)5000
Skewness2.4237752
Sum659100
Variance3.0709664 × 108
MonotonicityNot monotonic
2023-12-12T08:05:37.274253image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=27)
ValueCountFrequency (%)
8000 5
 
11.1%
0 4
 
8.9%
9000 3
 
6.7%
7000 3
 
6.7%
17000 2
 
4.4%
3200 2
 
4.4%
1000 2
 
4.4%
6000 2
 
4.4%
14000 2
 
4.4%
16000 2
 
4.4%
Other values (17) 18
40.0%
ValueCountFrequency (%)
0 4
8.9%
1000 2
 
4.4%
3200 2
 
4.4%
4000 1
 
2.2%
4200 1
 
2.2%
4500 1
 
2.2%
6000 2
 
4.4%
7000 3
6.7%
7500 1
 
2.2%
8000 5
11.1%
ValueCountFrequency (%)
80000 1
2.2%
70000 1
2.2%
60000 1
2.2%
43000 1
2.2%
35000 1
2.2%
30000 1
2.2%
23000 1
2.2%
20000 1
2.2%
17000 2
4.4%
16000 2
4.4%

중3동
Real number (ℝ)

ZEROS 

Distinct24
Distinct (%)53.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean8746.6667
Minimum0
Maximum60000
Zeros13
Zeros (%)28.9%
Negative0
Negative (%)0.0%
Memory size537.0 B
2023-12-12T08:05:37.376436image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median6000
Q311000
95-th percentile22800
Maximum60000
Range60000
Interquartile range (IQR)11000

Descriptive statistics

Standard deviation12071.164
Coefficient of variation (CV)1.3800873
Kurtosis9.035325
Mean8746.6667
Median Absolute Deviation (MAD)6000
Skewness2.7422042
Sum393600
Variance1.45713 × 108
MonotonicityNot monotonic
2023-12-12T08:05:37.489304image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=24)
ValueCountFrequency (%)
0 13
28.9%
6000 4
 
8.9%
9000 3
 
6.7%
7000 3
 
6.7%
14000 2
 
4.4%
2000 2
 
4.4%
10000 1
 
2.2%
4000 1
 
2.2%
60000 1
 
2.2%
1000 1
 
2.2%
Other values (14) 14
31.1%
ValueCountFrequency (%)
0 13
28.9%
1000 1
 
2.2%
2000 2
 
4.4%
2500 1
 
2.2%
3300 1
 
2.2%
3500 1
 
2.2%
4000 1
 
2.2%
6000 4
 
8.9%
7000 3
 
6.7%
7500 1
 
2.2%
ValueCountFrequency (%)
60000 1
2.2%
50000 1
2.2%
23000 1
2.2%
22000 1
2.2%
20000 1
2.2%
16900 1
2.2%
16000 1
2.2%
15900 1
2.2%
15000 1
2.2%
14000 2
4.4%

상1동
Real number (ℝ)

ZEROS 

Distinct31
Distinct (%)68.9%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean18204.444
Minimum0
Maximum300000
Zeros4
Zeros (%)8.9%
Negative0
Negative (%)0.0%
Memory size537.0 B
2023-12-12T08:05:37.622349image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q13500
median8000
Q315600
95-th percentile56000
Maximum300000
Range300000
Interquartile range (IQR)12100

Descriptive statistics

Standard deviation45017.234
Coefficient of variation (CV)2.4728705
Kurtosis36.839099
Mean18204.444
Median Absolute Deviation (MAD)4800
Skewness5.8623572
Sum819200
Variance2.0265513 × 109
MonotonicityNot monotonic
2023-12-12T08:05:37.746632image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=31)
ValueCountFrequency (%)
7500 4
 
8.9%
0 4
 
8.9%
8000 3
 
6.7%
3500 3
 
6.7%
20000 2
 
4.4%
3200 2
 
4.4%
10000 2
 
4.4%
7000 2
 
4.4%
300000 1
 
2.2%
1000 1
 
2.2%
Other values (21) 21
46.7%
ValueCountFrequency (%)
0 4
8.9%
800 1
 
2.2%
1000 1
 
2.2%
3000 1
 
2.2%
3200 2
4.4%
3500 3
6.7%
4000 1
 
2.2%
4500 1
 
2.2%
6000 1
 
2.2%
6500 1
 
2.2%
ValueCountFrequency (%)
300000 1
2.2%
65000 1
2.2%
60000 1
2.2%
40000 1
2.2%
23000 1
2.2%
20000 2
4.4%
19000 1
2.2%
18000 1
2.2%
17000 1
2.2%
16000 1
2.2%

중4동
Real number (ℝ)

ZEROS 

Distinct24
Distinct (%)53.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean16780.444
Minimum0
Maximum300000
Zeros10
Zeros (%)22.2%
Negative0
Negative (%)0.0%
Memory size537.0 B
2023-12-12T08:05:37.875898image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q13000
median7000
Q312000
95-th percentile56600
Maximum300000
Range300000
Interquartile range (IQR)9000

Descriptive statistics

Standard deviation45761.537
Coefficient of variation (CV)2.7270754
Kurtosis35.137958
Mean16780.444
Median Absolute Deviation (MAD)5000
Skewness5.7097799
Sum755120
Variance2.0941182 × 109
MonotonicityNot monotonic
2023-12-12T08:05:37.982579image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=24)
ValueCountFrequency (%)
0 10
22.2%
7000 5
 
11.1%
8000 4
 
8.9%
17000 3
 
6.7%
23000 2
 
4.4%
6500 2
 
4.4%
3200 2
 
4.4%
4000 1
 
2.2%
80000 1
 
2.2%
1000 1
 
2.2%
Other values (14) 14
31.1%
ValueCountFrequency (%)
0 10
22.2%
1000 1
 
2.2%
3000 1
 
2.2%
3200 2
 
4.4%
3500 1
 
2.2%
4000 1
 
2.2%
4500 1
 
2.2%
6000 1
 
2.2%
6500 2
 
4.4%
7000 5
11.1%
ValueCountFrequency (%)
300000 1
 
2.2%
80000 1
 
2.2%
65000 1
 
2.2%
23000 2
4.4%
22000 1
 
2.2%
18640 1
 
2.2%
17000 3
6.7%
16000 1
 
2.2%
12000 1
 
2.2%
10680 1
 
2.2%

상3동
Real number (ℝ)

ZEROS 

Distinct26
Distinct (%)57.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean13233.333
Minimum0
Maximum100000
Zeros6
Zeros (%)13.3%
Negative0
Negative (%)0.0%
Memory size537.0 B
2023-12-12T08:05:38.115823image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q13500
median9000
Q315000
95-th percentile60800
Maximum100000
Range100000
Interquartile range (IQR)11500

Descriptive statistics

Standard deviation19365.445
Coefficient of variation (CV)1.4633837
Kurtosis11.184607
Mean13233.333
Median Absolute Deviation (MAD)5500
Skewness3.2634887
Sum595500
Variance3.7502045 × 108
MonotonicityNot monotonic
2023-12-12T08:05:38.262983image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=26)
ValueCountFrequency (%)
0 6
 
13.3%
10000 4
 
8.9%
9000 3
 
6.7%
16000 3
 
6.7%
3500 3
 
6.7%
7000 3
 
6.7%
6000 2
 
4.4%
15000 2
 
4.4%
70000 2
 
4.4%
3000 1
 
2.2%
Other values (16) 16
35.6%
ValueCountFrequency (%)
0 6
13.3%
1000 1
 
2.2%
2500 1
 
2.2%
3000 1
 
2.2%
3500 3
6.7%
4000 1
 
2.2%
5000 1
 
2.2%
6000 2
 
4.4%
6500 1
 
2.2%
7000 3
6.7%
ValueCountFrequency (%)
100000 1
 
2.2%
70000 2
4.4%
24000 1
 
2.2%
20000 1
 
2.2%
19900 1
 
2.2%
16900 1
 
2.2%
16000 3
6.7%
15000 2
4.4%
13000 1
 
2.2%
12800 1
 
2.2%

심곡본동
Real number (ℝ)

ZEROS 

Distinct24
Distinct (%)53.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean10302.222
Minimum0
Maximum70000
Zeros7
Zeros (%)15.6%
Negative0
Negative (%)0.0%
Memory size537.0 B
2023-12-12T08:05:38.412046image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q13200
median7000
Q310900
95-th percentile33000
Maximum70000
Range70000
Interquartile range (IQR)7700

Descriptive statistics

Standard deviation13141.01
Coefficient of variation (CV)1.275551
Kurtosis10.531751
Mean10302.222
Median Absolute Deviation (MAD)3800
Skewness2.9722353
Sum463600
Variance1.7268613 × 108
MonotonicityNot monotonic
2023-12-12T08:05:38.523734image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=24)
ValueCountFrequency (%)
0 7
15.6%
6000 6
13.3%
15000 4
 
8.9%
7000 3
 
6.7%
10000 3
 
6.7%
3200 2
 
4.4%
8000 2
 
4.4%
10500 2
 
4.4%
15400 1
 
2.2%
50000 1
 
2.2%
Other values (14) 14
31.1%
ValueCountFrequency (%)
0 7
15.6%
400 1
 
2.2%
1000 1
 
2.2%
2000 1
 
2.2%
3200 2
 
4.4%
3300 1
 
2.2%
4000 1
 
2.2%
4500 1
 
2.2%
6000 6
13.3%
7000 3
6.7%
ValueCountFrequency (%)
70000 1
 
2.2%
50000 1
 
2.2%
35000 1
 
2.2%
25000 1
 
2.2%
22000 1
 
2.2%
15400 1
 
2.2%
15000 4
8.9%
11900 1
 
2.2%
10900 1
 
2.2%
10500 2
4.4%

심곡본1동
Real number (ℝ)

ZEROS 

Distinct21
Distinct (%)46.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean8206.6667
Minimum0
Maximum49000
Zeros11
Zeros (%)24.4%
Negative0
Negative (%)0.0%
Memory size537.0 B
2023-12-12T08:05:38.671393image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q11000
median7000
Q310000
95-th percentile26920
Maximum49000
Range49000
Interquartile range (IQR)9000

Descriptive statistics

Standard deviation9828.701
Coefficient of variation (CV)1.1976484
Kurtosis6.7473544
Mean8206.6667
Median Absolute Deviation (MAD)4500
Skewness2.3398338
Sum369300
Variance96603364
MonotonicityNot monotonic
2023-12-12T08:05:38.788502image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=21)
ValueCountFrequency (%)
0 11
24.4%
8000 4
 
8.9%
7000 4
 
8.9%
10000 3
 
6.7%
6500 3
 
6.7%
4000 2
 
4.4%
12000 2
 
4.4%
9000 2
 
4.4%
3000 2
 
4.4%
1000 1
 
2.2%
Other values (11) 11
24.4%
ValueCountFrequency (%)
0 11
24.4%
1000 1
 
2.2%
2000 1
 
2.2%
2500 1
 
2.2%
3000 2
 
4.4%
4000 2
 
4.4%
6000 1
 
2.2%
6500 3
 
6.7%
7000 4
 
8.9%
7500 1
 
2.2%
ValueCountFrequency (%)
49000 1
 
2.2%
35000 1
 
2.2%
27900 1
 
2.2%
23000 1
 
2.2%
20000 1
 
2.2%
18000 1
 
2.2%
12000 2
4.4%
11900 1
 
2.2%
10000 3
6.7%
9000 2
4.4%

소사본동
Real number (ℝ)

ZEROS 

Distinct26
Distinct (%)57.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean13835.556
Minimum0
Maximum200000
Zeros6
Zeros (%)13.3%
Negative0
Negative (%)0.0%
Memory size537.0 B
2023-12-12T08:05:38.929387image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q13000
median7000
Q312000
95-th percentile32400
Maximum200000
Range200000
Interquartile range (IQR)9000

Descriptive statistics

Standard deviation29984.52
Coefficient of variation (CV)2.1672075
Kurtosis35.566551
Mean13835.556
Median Absolute Deviation (MAD)5000
Skewness5.7153723
Sum622600
Variance8.9907143 × 108
MonotonicityNot monotonic
2023-12-12T08:05:39.073717image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=26)
ValueCountFrequency (%)
12000 7
15.6%
0 6
 
13.3%
6000 3
 
6.7%
15000 2
 
4.4%
2000 2
 
4.4%
4500 2
 
4.4%
5000 2
 
4.4%
10000 2
 
4.4%
7000 2
 
4.4%
500 1
 
2.2%
Other values (16) 16
35.6%
ValueCountFrequency (%)
0 6
13.3%
500 1
 
2.2%
1000 1
 
2.2%
2000 2
 
4.4%
2500 1
 
2.2%
3000 1
 
2.2%
4500 2
 
4.4%
5000 2
 
4.4%
5500 1
 
2.2%
6000 3
6.7%
ValueCountFrequency (%)
200000 1
 
2.2%
50000 1
 
2.2%
33000 1
 
2.2%
30000 1
 
2.2%
20000 1
 
2.2%
19800 1
 
2.2%
18000 1
 
2.2%
15900 1
 
2.2%
15000 2
 
4.4%
12000 7
15.6%

소사동
Real number (ℝ)

ZEROS 

Distinct21
Distinct (%)46.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean6017.7778
Minimum0
Maximum20000
Zeros13
Zeros (%)28.9%
Negative0
Negative (%)0.0%
Memory size537.0 B
2023-12-12T08:05:39.214518image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median5500
Q39000
95-th percentile14800
Maximum20000
Range20000
Interquartile range (IQR)9000

Descriptive statistics

Standard deviation5328.9641
Coefficient of variation (CV)0.88553687
Kurtosis-0.35103216
Mean6017.7778
Median Absolute Deviation (MAD)4500
Skewness0.58903386
Sum270800
Variance28397859
MonotonicityNot monotonic
2023-12-12T08:05:39.353055image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=21)
ValueCountFrequency (%)
0 13
28.9%
10000 4
 
8.9%
5500 3
 
6.7%
9000 3
 
6.7%
6000 2
 
4.4%
14000 2
 
4.4%
7000 2
 
4.4%
8000 2
 
4.4%
5000 2
 
4.4%
3000 1
 
2.2%
Other values (11) 11
24.4%
ValueCountFrequency (%)
0 13
28.9%
2000 1
 
2.2%
2500 1
 
2.2%
3000 1
 
2.2%
3500 1
 
2.2%
4000 1
 
2.2%
5000 2
 
4.4%
5400 1
 
2.2%
5500 3
 
6.7%
6000 2
 
4.4%
ValueCountFrequency (%)
20000 1
 
2.2%
16000 1
 
2.2%
15000 1
 
2.2%
14000 2
4.4%
13900 1
 
2.2%
13500 1
 
2.2%
10000 4
8.9%
9000 3
6.7%
8500 1
 
2.2%
8000 2
4.4%

송내1동
Real number (ℝ)

ZEROS 

Distinct26
Distinct (%)57.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean10266.667
Minimum0
Maximum80000
Zeros7
Zeros (%)15.6%
Negative0
Negative (%)0.0%
Memory size537.0 B
2023-12-12T08:05:39.477813image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q13000
median8000
Q313000
95-th percentile24600
Maximum80000
Range80000
Interquartile range (IQR)10000

Descriptive statistics

Standard deviation13006.851
Coefficient of variation (CV)1.2669011
Kurtosis18.651917
Mean10266.667
Median Absolute Deviation (MAD)5000
Skewness3.7158702
Sum462000
Variance1.6917818 × 108
MonotonicityNot monotonic
2023-12-12T08:05:39.598320image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=26)
ValueCountFrequency (%)
0 7
15.6%
8000 4
 
8.9%
3000 3
 
6.7%
20000 2
 
4.4%
9000 2
 
4.4%
6000 2
 
4.4%
10000 2
 
4.4%
5500 2
 
4.4%
12000 2
 
4.4%
7000 2
 
4.4%
Other values (16) 17
37.8%
ValueCountFrequency (%)
0 7
15.6%
100 1
 
2.2%
400 1
 
2.2%
2500 1
 
2.2%
3000 3
6.7%
3500 1
 
2.2%
4100 1
 
2.2%
5500 2
 
4.4%
6000 2
 
4.4%
7000 2
 
4.4%
ValueCountFrequency (%)
80000 1
2.2%
30000 1
2.2%
25000 1
2.2%
23000 1
2.2%
22000 1
2.2%
20000 2
4.4%
17000 1
2.2%
15000 1
2.2%
14000 2
4.4%
13000 1
2.2%

송내2동
Real number (ℝ)

ZEROS 

Distinct29
Distinct (%)64.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean14646.667
Minimum0
Maximum200000
Zeros7
Zeros (%)15.6%
Negative0
Negative (%)0.0%
Memory size537.0 B
2023-12-12T08:05:39.742153image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q13000
median7000
Q315000
95-th percentile40400
Maximum200000
Range200000
Interquartile range (IQR)12000

Descriptive statistics

Standard deviation30791.259
Coefficient of variation (CV)2.1022708
Kurtosis31.229364
Mean14646.667
Median Absolute Deviation (MAD)5800
Skewness5.2871952
Sum659100
Variance9.4810164 × 108
MonotonicityNot monotonic
2023-12-12T08:05:39.897464image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=29)
ValueCountFrequency (%)
0 7
 
15.6%
7000 5
 
11.1%
9500 2
 
4.4%
6000 2
 
4.4%
15000 2
 
4.4%
8000 2
 
4.4%
2500 2
 
4.4%
13000 2
 
4.4%
26000 1
 
2.2%
44000 1
 
2.2%
Other values (19) 19
42.2%
ValueCountFrequency (%)
0 7
15.6%
300 1
 
2.2%
1200 1
 
2.2%
2500 2
 
4.4%
3000 1
 
2.2%
3300 1
 
2.2%
3500 1
 
2.2%
3900 1
 
2.2%
4000 1
 
2.2%
6000 2
 
4.4%
ValueCountFrequency (%)
200000 1
2.2%
66000 1
2.2%
44000 1
2.2%
26000 1
2.2%
25000 1
2.2%
23000 1
2.2%
22000 1
2.2%
18000 1
2.2%
17000 1
2.2%
16000 1
2.2%

범박동
Real number (ℝ)

ZEROS 

Distinct26
Distinct (%)57.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean16404.444
Minimum0
Maximum250000
Zeros8
Zeros (%)17.8%
Negative0
Negative (%)0.0%
Memory size537.0 B
2023-12-12T08:05:40.011398image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q13000
median8000
Q314000
95-th percentile54000
Maximum250000
Range250000
Interquartile range (IQR)11000

Descriptive statistics

Standard deviation38957.727
Coefficient of variation (CV)2.3748276
Kurtosis30.84077
Mean16404.444
Median Absolute Deviation (MAD)5000
Skewness5.2964781
Sum738200
Variance1.5177045 × 109
MonotonicityNot monotonic
2023-12-12T08:05:40.149832image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=26)
ValueCountFrequency (%)
0 8
17.8%
9000 4
 
8.9%
13000 3
 
6.7%
7000 3
 
6.7%
3000 2
 
4.4%
10000 2
 
4.4%
15000 2
 
4.4%
6000 2
 
4.4%
5000 2
 
4.4%
90000 1
 
2.2%
Other values (16) 16
35.6%
ValueCountFrequency (%)
0 8
17.8%
500 1
 
2.2%
1500 1
 
2.2%
3000 2
 
4.4%
3300 1
 
2.2%
4200 1
 
2.2%
4900 1
 
2.2%
5000 2
 
4.4%
6000 2
 
4.4%
7000 3
 
6.7%
ValueCountFrequency (%)
250000 1
2.2%
90000 1
2.2%
60000 1
2.2%
30000 1
2.2%
23000 1
2.2%
18000 1
2.2%
17000 1
2.2%
16000 1
2.2%
15400 1
2.2%
15000 2
4.4%

소사본3동
Real number (ℝ)

ZEROS 

Distinct28
Distinct (%)62.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean13362.222
Minimum0
Maximum150000
Zeros8
Zeros (%)17.8%
Negative0
Negative (%)0.0%
Memory size537.0 B
2023-12-12T08:05:40.267634image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q13000
median7500
Q310200
95-th percentile50000
Maximum150000
Range150000
Interquartile range (IQR)7200

Descriptive statistics

Standard deviation25369.168
Coefficient of variation (CV)1.898574
Kurtosis20.165343
Mean13362.222
Median Absolute Deviation (MAD)4500
Skewness4.2140974
Sum601300
Variance6.4359468 × 108
MonotonicityNot monotonic
2023-12-12T08:05:40.415625image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=28)
ValueCountFrequency (%)
0 8
17.8%
10000 4
 
8.9%
8000 3
 
6.7%
7000 2
 
4.4%
9000 2
 
4.4%
3200 2
 
4.4%
5000 2
 
4.4%
6000 2
 
4.4%
55000 1
 
2.2%
80000 1
 
2.2%
Other values (18) 18
40.0%
ValueCountFrequency (%)
0 8
17.8%
500 1
 
2.2%
1000 1
 
2.2%
2500 1
 
2.2%
3000 1
 
2.2%
3200 2
 
4.4%
3300 1
 
2.2%
3500 1
 
2.2%
5000 2
 
4.4%
6000 2
 
4.4%
ValueCountFrequency (%)
150000 1
2.2%
80000 1
2.2%
55000 1
2.2%
30000 1
2.2%
25000 1
2.2%
21000 1
2.2%
20000 1
2.2%
17000 1
2.2%
13900 1
2.2%
13000 1
2.2%

역곡3동
Real number (ℝ)

ZEROS 

Distinct25
Distinct (%)55.6%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean13840
Minimum0
Maximum100000
Zeros6
Zeros (%)13.3%
Negative0
Negative (%)0.0%
Memory size537.0 B
2023-12-12T08:05:40.565457image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q13500
median8300
Q315000
95-th percentile47000
Maximum100000
Range100000
Interquartile range (IQR)11500

Descriptive statistics

Standard deviation19345.841
Coefficient of variation (CV)1.3978208
Kurtosis11.022908
Mean13840
Median Absolute Deviation (MAD)5700
Skewness3.148848
Sum622800
Variance3.7426155 × 108
MonotonicityNot monotonic
2023-12-12T08:05:40.712154image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=25)
ValueCountFrequency (%)
0 6
 
13.3%
6000 5
 
11.1%
12000 4
 
8.9%
7000 3
 
6.7%
15000 3
 
6.7%
2000 2
 
4.4%
3500 2
 
4.4%
14000 2
 
4.4%
20000 2
 
4.4%
35000 1
 
2.2%
Other values (15) 15
33.3%
ValueCountFrequency (%)
0 6
13.3%
1000 1
 
2.2%
2000 2
 
4.4%
3100 1
 
2.2%
3500 2
 
4.4%
4000 1
 
2.2%
6000 5
11.1%
6500 1
 
2.2%
7000 3
6.7%
8300 1
 
2.2%
ValueCountFrequency (%)
100000 1
 
2.2%
80000 1
 
2.2%
50000 1
 
2.2%
35000 1
 
2.2%
25000 1
 
2.2%
22000 1
 
2.2%
20000 2
4.4%
18000 1
 
2.2%
17000 1
 
2.2%
15000 3
6.7%

괴안동
Real number (ℝ)

ZEROS 

Distinct19
Distinct (%)42.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean7393.3333
Minimum0
Maximum50000
Zeros14
Zeros (%)31.1%
Negative0
Negative (%)0.0%
Memory size537.0 B
2023-12-12T08:05:40.874604image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median6000
Q312000
95-th percentile19780
Maximum50000
Range50000
Interquartile range (IQR)12000

Descriptive statistics

Standard deviation9326.8771
Coefficient of variation (CV)1.2615253
Kurtosis8.877146
Mean7393.3333
Median Absolute Deviation (MAD)6000
Skewness2.4470239
Sum332700
Variance86990636
MonotonicityNot monotonic
2023-12-12T08:05:41.297910image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=19)
ValueCountFrequency (%)
0 14
31.1%
7000 4
 
8.9%
6000 4
 
8.9%
12000 3
 
6.7%
3000 3
 
6.7%
15000 2
 
4.4%
2000 2
 
4.4%
8000 2
 
4.4%
18900 1
 
2.2%
1000 1
 
2.2%
Other values (9) 9
20.0%
ValueCountFrequency (%)
0 14
31.1%
1000 1
 
2.2%
2000 2
 
4.4%
3000 3
 
6.7%
3300 1
 
2.2%
5500 1
 
2.2%
6000 4
 
8.9%
7000 4
 
8.9%
8000 2
 
4.4%
12000 3
 
6.7%
ValueCountFrequency (%)
50000 1
 
2.2%
25000 1
 
2.2%
20000 1
 
2.2%
18900 1
 
2.2%
18000 1
 
2.2%
17000 1
 
2.2%
15000 2
4.4%
14000 1
 
2.2%
13000 1
 
2.2%
12000 3
6.7%

성곡동
Real number (ℝ)

ZEROS 

Distinct24
Distinct (%)53.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean11762.222
Minimum0
Maximum80000
Zeros9
Zeros (%)20.0%
Negative0
Negative (%)0.0%
Memory size537.0 B
2023-12-12T08:05:41.424426image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q12000
median6000
Q316000
95-th percentile42000
Maximum80000
Range80000
Interquartile range (IQR)14000

Descriptive statistics

Standard deviation17436.199
Coefficient of variation (CV)1.4823899
Kurtosis9.4557543
Mean11762.222
Median Absolute Deviation (MAD)6000
Skewness2.9534998
Sum529300
Variance3.0402104 × 108
MonotonicityNot monotonic
2023-12-12T08:05:41.581827image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=24)
ValueCountFrequency (%)
0 9
20.0%
6000 3
 
6.7%
7000 3
 
6.7%
17000 3
 
6.7%
5500 3
 
6.7%
6500 2
 
4.4%
16000 2
 
4.4%
80000 2
 
4.4%
20000 2
 
4.4%
4500 2
 
4.4%
Other values (14) 14
31.1%
ValueCountFrequency (%)
0 9
20.0%
500 1
 
2.2%
1000 1
 
2.2%
2000 1
 
2.2%
2500 1
 
2.2%
3500 1
 
2.2%
3900 1
 
2.2%
4500 2
 
4.4%
5500 3
 
6.7%
6000 3
 
6.7%
ValueCountFrequency (%)
80000 2
4.4%
45000 1
 
2.2%
30000 1
 
2.2%
22000 1
 
2.2%
20000 2
4.4%
17000 3
6.7%
16000 2
4.4%
15000 1
 
2.2%
13000 1
 
2.2%
11400 1
 
2.2%

고강본동
Real number (ℝ)

ZEROS 

Distinct22
Distinct (%)48.9%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean9648.8889
Minimum0
Maximum50000
Zeros7
Zeros (%)15.6%
Negative0
Negative (%)0.0%
Memory size537.0 B
2023-12-12T08:05:41.703400image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q13500
median8000
Q311000
95-th percentile25000
Maximum50000
Range50000
Interquartile range (IQR)7500

Descriptive statistics

Standard deviation9966.0246
Coefficient of variation (CV)1.0328676
Kurtosis6.58348
Mean9648.8889
Median Absolute Deviation (MAD)4000
Skewness2.2513903
Sum434200
Variance99321646
MonotonicityNot monotonic
2023-12-12T08:05:41.826517image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=22)
ValueCountFrequency (%)
0 7
15.6%
9000 4
 
8.9%
10000 4
 
8.9%
11000 3
 
6.7%
8000 3
 
6.7%
3500 3
 
6.7%
7000 2
 
4.4%
14000 2
 
4.4%
25000 2
 
4.4%
6000 2
 
4.4%
Other values (12) 13
28.9%
ValueCountFrequency (%)
0 7
15.6%
500 1
 
2.2%
1000 1
 
2.2%
2800 1
 
2.2%
3500 3
6.7%
4000 2
 
4.4%
6000 2
 
4.4%
7000 2
 
4.4%
7500 1
 
2.2%
8000 3
6.7%
ValueCountFrequency (%)
50000 1
 
2.2%
40000 1
 
2.2%
25000 2
4.4%
20000 1
 
2.2%
18000 1
 
2.2%
15000 1
 
2.2%
14000 2
4.4%
12000 1
 
2.2%
11900 1
 
2.2%
11000 3
6.7%

고강1동
Real number (ℝ)

ZEROS 

Distinct25
Distinct (%)55.6%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean8364.4444
Minimum0
Maximum55000
Zeros11
Zeros (%)24.4%
Negative0
Negative (%)0.0%
Memory size537.0 B
2023-12-12T08:05:41.938214image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q11000
median6000
Q310900
95-th percentile27600
Maximum55000
Range55000
Interquartile range (IQR)9900

Descriptive statistics

Standard deviation10607.355
Coefficient of variation (CV)1.2681482
Kurtosis9.1816628
Mean8364.4444
Median Absolute Deviation (MAD)5000
Skewness2.7331377
Sum376400
Variance1.1251598 × 108
MonotonicityNot monotonic
2023-12-12T08:05:42.040742image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=25)
ValueCountFrequency (%)
0 11
24.4%
10000 4
 
8.9%
14000 3
 
6.7%
6000 3
 
6.7%
6500 2
 
4.4%
3200 2
 
4.4%
4000 2
 
4.4%
2500 1
 
2.2%
55000 1
 
2.2%
1000 1
 
2.2%
Other values (15) 15
33.3%
ValueCountFrequency (%)
0 11
24.4%
1000 1
 
2.2%
2500 1
 
2.2%
3000 1
 
2.2%
3200 2
 
4.4%
4000 2
 
4.4%
4500 1
 
2.2%
5000 1
 
2.2%
5900 1
 
2.2%
6000 3
 
6.7%
ValueCountFrequency (%)
55000 1
 
2.2%
40000 1
 
2.2%
30000 1
 
2.2%
18000 1
 
2.2%
14000 3
6.7%
13000 1
 
2.2%
12900 1
 
2.2%
12000 1
 
2.2%
11400 1
 
2.2%
10900 1
 
2.2%

원종1동
Real number (ℝ)

ZEROS 

Distinct28
Distinct (%)62.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean13343.778
Minimum0
Maximum120000
Zeros9
Zeros (%)20.0%
Negative0
Negative (%)0.0%
Memory size537.0 B
2023-12-12T08:05:42.151824image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q12500
median6000
Q313900
95-th percentile50000
Maximum120000
Range120000
Interquartile range (IQR)11400

Descriptive statistics

Standard deviation23515.38
Coefficient of variation (CV)1.762273
Kurtosis12.917117
Mean13343.778
Median Absolute Deviation (MAD)6000
Skewness3.496481
Sum600470
Variance5.5297309 × 108
MonotonicityNot monotonic
2023-12-12T08:05:42.265727image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=28)
ValueCountFrequency (%)
0 9
20.0%
6000 4
 
8.9%
5000 3
 
6.7%
30000 2
 
4.4%
4000 2
 
4.4%
2500 2
 
4.4%
8000 2
 
4.4%
10000 1
 
2.2%
100000 1
 
2.2%
1330 1
 
2.2%
Other values (18) 18
40.0%
ValueCountFrequency (%)
0 9
20.0%
1330 1
 
2.2%
1670 1
 
2.2%
2500 2
 
4.4%
3500 1
 
2.2%
4000 2
 
4.4%
4100 1
 
2.2%
5000 3
 
6.7%
6000 4
8.9%
8000 2
 
4.4%
ValueCountFrequency (%)
120000 1
2.2%
100000 1
2.2%
55000 1
2.2%
30000 2
4.4%
21000 1
2.2%
18900 1
2.2%
17000 1
2.2%
16000 1
2.2%
14740 1
2.2%
14000 1
2.2%

원종2동
Real number (ℝ)

ZEROS 

Distinct28
Distinct (%)62.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean11899.333
Minimum0
Maximum100000
Zeros8
Zeros (%)17.8%
Negative0
Negative (%)0.0%
Memory size537.0 B
2023-12-12T08:05:42.368430image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q12800
median8000
Q313600
95-th percentile38000
Maximum100000
Range100000
Interquartile range (IQR)10800

Descriptive statistics

Standard deviation18259.626
Coefficient of variation (CV)1.5345083
Kurtosis13.806568
Mean11899.333
Median Absolute Deviation (MAD)5500
Skewness3.4768141
Sum535470
Variance3.3341393 × 108
MonotonicityNot monotonic
2023-12-12T08:05:42.478101image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=28)
ValueCountFrequency (%)
0 8
17.8%
8000 3
 
6.7%
9000 3
 
6.7%
14000 3
 
6.7%
4000 2
 
4.4%
18000 2
 
4.4%
10000 2
 
4.4%
5000 2
 
4.4%
2800 1
 
2.2%
100000 1
 
2.2%
Other values (18) 18
40.0%
ValueCountFrequency (%)
0 8
17.8%
1000 1
 
2.2%
1670 1
 
2.2%
2500 1
 
2.2%
2800 1
 
2.2%
3000 1
 
2.2%
3500 1
 
2.2%
4000 2
 
4.4%
4500 1
 
2.2%
5000 2
 
4.4%
ValueCountFrequency (%)
100000 1
 
2.2%
70000 1
 
2.2%
40000 1
 
2.2%
30000 1
 
2.2%
26000 1
 
2.2%
18000 2
4.4%
15000 1
 
2.2%
14000 3
6.7%
13600 1
 
2.2%
13500 1
 
2.2%

오정동
Real number (ℝ)

ZEROS 

Distinct26
Distinct (%)57.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean10311.111
Minimum0
Maximum60000
Zeros9
Zeros (%)20.0%
Negative0
Negative (%)0.0%
Memory size537.0 B
2023-12-12T08:05:42.585413image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q12800
median8000
Q313900
95-th percentile33000
Maximum60000
Range60000
Interquartile range (IQR)11100

Descriptive statistics

Standard deviation12370.589
Coefficient of variation (CV)1.1997338
Kurtosis6.9917889
Mean10311.111
Median Absolute Deviation (MAD)5900
Skewness2.4334498
Sum464000
Variance1.5303146 × 108
MonotonicityNot monotonic
2023-12-12T08:05:42.689727image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=26)
ValueCountFrequency (%)
0 9
20.0%
8000 4
 
8.9%
7000 3
 
6.7%
16000 2
 
4.4%
15000 2
 
4.4%
25000 2
 
4.4%
9000 2
 
4.4%
14000 2
 
4.4%
12000 2
 
4.4%
700 1
 
2.2%
Other values (16) 16
35.6%
ValueCountFrequency (%)
0 9
20.0%
700 1
 
2.2%
1000 1
 
2.2%
2800 1
 
2.2%
3000 1
 
2.2%
3200 1
 
2.2%
3500 1
 
2.2%
4500 1
 
2.2%
5000 1
 
2.2%
6000 1
 
2.2%
ValueCountFrequency (%)
60000 1
2.2%
50000 1
2.2%
35000 1
2.2%
25000 2
4.4%
16000 2
4.4%
15000 2
4.4%
14000 2
4.4%
13900 1
2.2%
13000 1
2.2%
12000 2
4.4%

신흥동
Real number (ℝ)

ZEROS 

Distinct24
Distinct (%)53.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean12553.333
Minimum0
Maximum170000
Zeros10
Zeros (%)22.2%
Negative0
Negative (%)0.0%
Memory size537.0 B
2023-12-12T08:05:42.792359image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q11000
median7000
Q314000
95-th percentile24200
Maximum170000
Range170000
Interquartile range (IQR)13000

Descriptive statistics

Standard deviation27115.968
Coefficient of variation (CV)2.1600612
Kurtosis27.408858
Mean12553.333
Median Absolute Deviation (MAD)7000
Skewness4.9898331
Sum564900
Variance7.3527573 × 108
MonotonicityNot monotonic
2023-12-12T08:05:42.888054image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=24)
ValueCountFrequency (%)
0 10
22.2%
14000 4
 
8.9%
7000 4
 
8.9%
3000 3
 
6.7%
10000 3
 
6.7%
5500 2
 
4.4%
15000 2
 
4.4%
4000 1
 
2.2%
500 1
 
2.2%
1000 1
 
2.2%
Other values (14) 14
31.1%
ValueCountFrequency (%)
0 10
22.2%
500 1
 
2.2%
1000 1
 
2.2%
2500 1
 
2.2%
3000 3
 
6.7%
4000 1
 
2.2%
4500 1
 
2.2%
5500 2
 
4.4%
6000 1
 
2.2%
7000 4
 
8.9%
ValueCountFrequency (%)
170000 1
 
2.2%
80000 1
 
2.2%
25000 1
 
2.2%
21000 1
 
2.2%
18000 1
 
2.2%
17000 1
 
2.2%
15000 2
4.4%
14900 1
 
2.2%
14000 4
8.9%
12000 1
 
2.2%

Sample

연번품목규격심곡2동심곡1동심곡3동원미1동원미2동역곡1동역곡2동도당동춘의동중동중2동상동상2동약대동중1동중3동상1동중4동상3동심곡본동심곡본1동소사본동소사동송내1동송내2동범박동소사본3동역곡3동괴안동성곡동고강본동고강1동원종1동원종2동오정동신흥동
01설렁탕1인분(보통)800080000900006000700011000110008000800090009000800090001000075008000900070008000900060001000095009000800010000700090001100009000800080009000
12냉 면물냉면. 1인분(보통)7000500070008000550065007000900090009000800080006000110008000600065006500700060006500450050007500950090008000900070005500600059005000900070007000
23비빔밥1인분(보통)850080000800050006500600090009000600090005000600055007500750075008000600060006500700055007000800060008000600080006000900065006000650085005500
34갈비탕1인분(보통)9000001300012000600010000100001000014000100001500015000150001300090001300012000130008000800012000900012000130001000090001200013000700090001000014000135001200012000
45삼계탕닭1마리. 1인분(보통)14000140000150001100013000120001400013000140001500015000160001300016000140001600001600015000120001200014000150001600013000120001500000150001400013000140001400014000
56김치찌개1인분(보통)800070007000800060006500700090008000500060005500600080007000700075007000800060007000600070005500700080006000600060006000700060006000800080007000
67된장찌개1인분(보통)8000700070008000600065007000900080007000600055006000700080006000750070001000060007000600060005500700070005000600060006000700060006000900070007000
78불고기쇠고기200g.1인분70008000080000800002200023000180001800015000800017900140000140002200016000105008000100001000020000220001300010000200001200070009000100001600013600014000
89돼지갈비(외식)대중식당. 200g 외식1인분1500013000170001200013000119001300012000180002200012000160001100014000170001600012000106809200100001000012000100001300013000160001000014000170001600014000140009330140001600018000
910삼겹살(외식)돼지고기200g.1인분15000130001500012000150001200013000130006000120001500015000120001400016000140001560018640128001540012000120001400014000170001500010000140001500015000140001400014740150001600015000
연번품목규격심곡2동심곡1동심곡3동원미1동원미2동역곡1동역곡2동도당동춘의동중동중2동상동상2동약대동중1동중3동상1동중4동상3동심곡본동심곡본1동소사본동소사동송내1동송내2동범박동소사본3동역곡3동괴안동성곡동고강본동고강1동원종1동원종2동오정동신흥동
3536볼링장 이용료일반인. 평일 오후시간(신발제외). 1시간10000003800000040000400010500900004200000350000000390000000000000
3637골프장이용료초급반(남자).회비레슨비(의복및신발제외).1개월150000002000000022000023500025000015000015000012000036200000030000030000010000002000000020000025000015000010000000001000001000000170000
3738당구장 이용료쿠션 당구대. 일반인. 저녁시간 1시간1100010000600090009000120006000100001000084008000100009000120001100001000001140088009000120009000900090001000010200120001200011400100001140010000100001000010000
3839노래방 이용료일반인. 저녁시간대. 일반실. 1시간25000200002000030000300002500025000250002000020000200002000020000250002000020000200000150002500020000200002000025000250003000025000250002500030000250003000030000300002500025000
3940PC방 이용료기본시간 1회2000120012001000100020003000100010005001000100010000100010001000010001000100010002000100120015001000100010001000100010001330100010001000
4041사진촬영료반명함판 컬러 3x4cm. 6매1조170000200000150001800001500015000150001200015000134000300000150001700001500001500002000015000150003000018000017000200000500050001500015000
4142사진인화료디지털 사진인화요금(현상료 포함).1매300000045040004004004005000300010000800100004000500040030050050000500500016701670700500
4243영화관람료주중 상영시간 100분 정도. 1매110000000000014000013000001400000000000001300001500000000000
4344운동경기관람료성인경기입장료(축구.야구 등).1회0000000010000000000000000000000000000000
4445스포츠센터입장료헬스장 (1개월) 입장료30000600006000030000400006000060000600007000085000950001000001200006000080000600006000080000100000700000500000800006600090000800008000008000050000550005500070000600000