Overview

Dataset statistics

Number of variables17
Number of observations64
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory9.6 KiB
Average record size in memory154.1 B

Variable types

Text1
Numeric16

Dataset

Description한국부동산원(구.한국감정원)에서 제공하는 상업용부동산 임대동향조사 중 오피스의 분기별 지역별 전환률 데이터입니다. - (단위: %) - 공표시기 : 계간(분기)
Author한국부동산원
URLhttps://www.data.go.kr/data/15069753/fileData.do

Alerts

2013_1분기 is highly overall correlated with 2013_2분기 and 14 other fieldsHigh correlation
2013_2분기 is highly overall correlated with 2013_1분기 and 14 other fieldsHigh correlation
2013_3분기 is highly overall correlated with 2013_1분기 and 14 other fieldsHigh correlation
2013_4분기 is highly overall correlated with 2013_1분기 and 14 other fieldsHigh correlation
2014_1분기 is highly overall correlated with 2013_1분기 and 14 other fieldsHigh correlation
2014_2분기 is highly overall correlated with 2013_1분기 and 14 other fieldsHigh correlation
2014_3분기 is highly overall correlated with 2013_1분기 and 14 other fieldsHigh correlation
2014_4분기 is highly overall correlated with 2013_1분기 and 14 other fieldsHigh correlation
2015_1분기 is highly overall correlated with 2013_1분기 and 14 other fieldsHigh correlation
2015_2분기 is highly overall correlated with 2013_1분기 and 14 other fieldsHigh correlation
2015_3분기 is highly overall correlated with 2013_1분기 and 14 other fieldsHigh correlation
2015_4분기 is highly overall correlated with 2013_1분기 and 14 other fieldsHigh correlation
2016_1분기 is highly overall correlated with 2013_1분기 and 14 other fieldsHigh correlation
2016_2분기 is highly overall correlated with 2013_1분기 and 14 other fieldsHigh correlation
2016_3분기 is highly overall correlated with 2013_1분기 and 14 other fieldsHigh correlation
2016_4분기 is highly overall correlated with 2013_1분기 and 14 other fieldsHigh correlation
지역 has unique valuesUnique

Reproduction

Analysis started2023-12-12 16:13:24.514358
Analysis finished2023-12-12 16:13:49.555582
Duration25.04 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

지역
Text

UNIQUE 

Distinct64
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size644.0 B
2023-12-13T01:13:49.702557image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length12
Median length9
Mean length6.546875
Min length3

Characters and Unicode

Total characters419
Distinct characters87
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique64 ?
Unique (%)100.0%

Sample

1st row서울
2nd row서울 도심
3rd row서울 도심 광화문
4th row서울 도심 동대문
5th row서울 도심 명동
ValueCountFrequency (%)
서울 27
20.1%
기타 9
 
6.7%
도심 7
 
5.2%
강남 6
 
4.5%
부산 6
 
4.5%
경기 5
 
3.7%
대전 4
 
3.0%
대구 4
 
3.0%
여의도마포 4
 
3.0%
인천 4
 
3.0%
Other values (54) 58
43.3%
2023-12-13T01:13:50.067624image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
90
21.5%
31
 
7.4%
31
 
7.4%
16
 
3.8%
14
 
3.3%
14
 
3.3%
14
 
3.3%
11
 
2.6%
9
 
2.1%
9
 
2.1%
Other values (77) 180
43.0%

Most occurring categories

ValueCountFrequency (%)
Other Letter 328
78.3%
Space Separator 90
 
21.5%
Other Punctuation 1
 
0.2%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
31
 
9.5%
31
 
9.5%
16
 
4.9%
14
 
4.3%
14
 
4.3%
14
 
4.3%
11
 
3.4%
9
 
2.7%
9
 
2.7%
9
 
2.7%
Other values (75) 170
51.8%
Space Separator
ValueCountFrequency (%)
90
100.0%
Other Punctuation
ValueCountFrequency (%)
/ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 328
78.3%
Common 91
 
21.7%

Most frequent character per script

Hangul
ValueCountFrequency (%)
31
 
9.5%
31
 
9.5%
16
 
4.9%
14
 
4.3%
14
 
4.3%
14
 
4.3%
11
 
3.4%
9
 
2.7%
9
 
2.7%
9
 
2.7%
Other values (75) 170
51.8%
Common
ValueCountFrequency (%)
90
98.9%
/ 1
 
1.1%

Most occurring blocks

ValueCountFrequency (%)
Hangul 328
78.3%
ASCII 91
 
21.7%

Most frequent character per block

ASCII
ValueCountFrequency (%)
90
98.9%
/ 1
 
1.1%
Hangul
ValueCountFrequency (%)
31
 
9.5%
31
 
9.5%
16
 
4.9%
14
 
4.3%
14
 
4.3%
14
 
4.3%
11
 
3.4%
9
 
2.7%
9
 
2.7%
9
 
2.7%
Other values (75) 170
51.8%

2013_1분기
Real number (ℝ)

HIGH CORRELATION 

Distinct20
Distinct (%)31.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean11.7625
Minimum10
Maximum14.2
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size708.0 B
2023-12-13T01:13:50.190894image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum10
5-th percentile10.16
Q111.6
median12
Q312
95-th percentile12.355
Maximum14.2
Range4.2
Interquartile range (IQR)0.4

Descriptive statistics

Standard deviation0.68787688
Coefficient of variation (CV)0.0584805
Kurtosis3.4605574
Mean11.7625
Median Absolute Deviation (MAD)0
Skewness-0.38434801
Sum752.8
Variance0.4731746
MonotonicityNot monotonic
2023-12-13T01:13:50.293117image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=20)
ValueCountFrequency (%)
12.0 34
53.1%
11.9 4
 
6.2%
11.6 3
 
4.7%
11.8 3
 
4.7%
10.0 3
 
4.7%
11.5 2
 
3.1%
11.1 2
 
3.1%
12.6 1
 
1.6%
12.4 1
 
1.6%
14.2 1
 
1.6%
Other values (10) 10
 
15.6%
ValueCountFrequency (%)
10.0 3
4.7%
10.1 1
 
1.6%
10.5 1
 
1.6%
10.6 1
 
1.6%
10.7 1
 
1.6%
11.0 1
 
1.6%
11.1 2
3.1%
11.2 1
 
1.6%
11.4 1
 
1.6%
11.5 2
3.1%
ValueCountFrequency (%)
14.2 1
 
1.6%
13.3 1
 
1.6%
12.6 1
 
1.6%
12.4 1
 
1.6%
12.1 1
 
1.6%
12.0 34
53.1%
11.9 4
 
6.2%
11.8 3
 
4.7%
11.7 1
 
1.6%
11.6 3
 
4.7%

2013_2분기
Real number (ℝ)

HIGH CORRELATION 

Distinct20
Distinct (%)31.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean11.771875
Minimum10
Maximum14
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size708.0 B
2023-12-13T01:13:50.398822image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum10
5-th percentile10.245
Q111.7
median12
Q312
95-th percentile12.355
Maximum14
Range4
Interquartile range (IQR)0.3

Descriptive statistics

Standard deviation0.66510979
Coefficient of variation (CV)0.056499902
Kurtosis3.0507226
Mean11.771875
Median Absolute Deviation (MAD)0
Skewness-0.51284343
Sum753.4
Variance0.44237103
MonotonicityNot monotonic
2023-12-13T01:13:50.517515image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=20)
ValueCountFrequency (%)
12.0 33
51.6%
11.9 5
 
7.8%
11.7 3
 
4.7%
11.6 2
 
3.1%
12.1 2
 
3.1%
11.8 2
 
3.1%
10.0 2
 
3.1%
10.2 2
 
3.1%
11.1 2
 
3.1%
10.5 1
 
1.6%
Other values (10) 10
 
15.6%
ValueCountFrequency (%)
10.0 2
3.1%
10.2 2
3.1%
10.5 1
1.6%
10.6 1
1.6%
10.7 1
1.6%
11.0 1
1.6%
11.1 2
3.1%
11.2 1
1.6%
11.4 1
1.6%
11.5 1
1.6%
ValueCountFrequency (%)
14.0 1
 
1.6%
13.3 1
 
1.6%
12.6 1
 
1.6%
12.4 1
 
1.6%
12.1 2
 
3.1%
12.0 33
51.6%
11.9 5
 
7.8%
11.8 2
 
3.1%
11.7 3
 
4.7%
11.6 2
 
3.1%

2013_3분기
Real number (ℝ)

HIGH CORRELATION 

Distinct20
Distinct (%)31.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean11.74375
Minimum9
Maximum14
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size708.0 B
2023-12-13T01:13:50.649714image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum9
5-th percentile10.2
Q111.7
median12
Q312
95-th percentile12.355
Maximum14
Range5
Interquartile range (IQR)0.3

Descriptive statistics

Standard deviation0.74041494
Coefficient of variation (CV)0.063047574
Kurtosis4.0612903
Mean11.74375
Median Absolute Deviation (MAD)0
Skewness-1.0670672
Sum751.6
Variance0.54821429
MonotonicityNot monotonic
2023-12-13T01:13:50.763798image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=20)
ValueCountFrequency (%)
12.0 34
53.1%
11.9 4
 
6.2%
11.7 3
 
4.7%
11.1 2
 
3.1%
12.1 2
 
3.1%
11.8 2
 
3.1%
11.6 2
 
3.1%
10.2 2
 
3.1%
10.0 2
 
3.1%
9.0 1
 
1.6%
Other values (10) 10
 
15.6%
ValueCountFrequency (%)
9.0 1
1.6%
10.0 2
3.1%
10.2 2
3.1%
10.5 1
1.6%
10.6 1
1.6%
11.0 1
1.6%
11.1 2
3.1%
11.2 1
1.6%
11.3 1
1.6%
11.4 1
1.6%
ValueCountFrequency (%)
14.0 1
 
1.6%
13.3 1
 
1.6%
12.6 1
 
1.6%
12.4 1
 
1.6%
12.1 2
 
3.1%
12.0 34
53.1%
11.9 4
 
6.2%
11.8 2
 
3.1%
11.7 3
 
4.7%
11.6 2
 
3.1%

2013_4분기
Real number (ℝ)

HIGH CORRELATION 

Distinct19
Distinct (%)29.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean11.635938
Minimum9
Maximum13.7
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size708.0 B
2023-12-13T01:13:50.872127image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum9
5-th percentile10
Q111.375
median12
Q312
95-th percentile12.355
Maximum13.7
Range4.7
Interquartile range (IQR)0.625

Descriptive statistics

Standard deviation0.7874748
Coefficient of variation (CV)0.067676094
Kurtosis2.074514
Mean11.635938
Median Absolute Deviation (MAD)0.1
Skewness-1.0176076
Sum744.7
Variance0.62011657
MonotonicityNot monotonic
2023-12-13T01:13:50.977423image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=19)
ValueCountFrequency (%)
12.0 30
46.9%
10.0 4
 
6.2%
11.9 3
 
4.7%
11.7 3
 
4.7%
11.1 3
 
4.7%
11.5 2
 
3.1%
12.1 2
 
3.1%
11.8 2
 
3.1%
11.0 2
 
3.1%
11.3 2
 
3.1%
Other values (9) 11
 
17.2%
ValueCountFrequency (%)
9.0 1
 
1.6%
10.0 4
6.2%
10.2 2
3.1%
10.5 2
3.1%
11.0 2
3.1%
11.1 3
4.7%
11.3 2
3.1%
11.4 1
 
1.6%
11.5 2
3.1%
11.6 1
 
1.6%
ValueCountFrequency (%)
13.7 1
 
1.6%
13.2 1
 
1.6%
12.5 1
 
1.6%
12.4 1
 
1.6%
12.1 2
 
3.1%
12.0 30
46.9%
11.9 3
 
4.7%
11.8 2
 
3.1%
11.7 3
 
4.7%
11.6 1
 
1.6%

2014_1분기
Real number (ℝ)

HIGH CORRELATION 

Distinct20
Distinct (%)31.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean11.571875
Minimum9
Maximum13.7
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size708.0 B
2023-12-13T01:13:51.089945image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum9
5-th percentile10
Q111.1
median12
Q312
95-th percentile12.355
Maximum13.7
Range4.7
Interquartile range (IQR)0.9

Descriptive statistics

Standard deviation0.83542001
Coefficient of variation (CV)0.072194005
Kurtosis2.0886228
Mean11.571875
Median Absolute Deviation (MAD)0.15
Skewness-1.0329821
Sum740.6
Variance0.69792659
MonotonicityNot monotonic
2023-12-13T01:13:51.190740image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=20)
ValueCountFrequency (%)
12.0 27
42.2%
11.0 5
 
7.8%
11.7 3
 
4.7%
11.1 3
 
4.7%
11.9 3
 
4.7%
10.0 3
 
4.7%
11.5 2
 
3.1%
12.1 2
 
3.1%
9.0 2
 
3.1%
10.2 2
 
3.1%
Other values (10) 12
18.8%
ValueCountFrequency (%)
9.0 2
 
3.1%
10.0 3
4.7%
10.2 2
 
3.1%
10.5 2
 
3.1%
11.0 5
7.8%
11.1 3
4.7%
11.2 1
 
1.6%
11.3 1
 
1.6%
11.4 1
 
1.6%
11.5 2
 
3.1%
ValueCountFrequency (%)
13.7 1
 
1.6%
13.2 1
 
1.6%
12.5 1
 
1.6%
12.4 1
 
1.6%
12.1 2
 
3.1%
12.0 27
42.2%
11.9 3
 
4.7%
11.8 2
 
3.1%
11.7 3
 
4.7%
11.6 1
 
1.6%

2014_2분기
Real number (ℝ)

HIGH CORRELATION 

Distinct22
Distinct (%)34.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean11.514062
Minimum8.5
Maximum13.2
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size708.0 B
2023-12-13T01:13:51.288383image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum8.5
5-th percentile10
Q111.1
median12
Q312
95-th percentile12.355
Maximum13.2
Range4.7
Interquartile range (IQR)0.9

Descriptive statistics

Standard deviation0.84306079
Coefficient of variation (CV)0.073220098
Kurtosis2.4655186
Mean11.514062
Median Absolute Deviation (MAD)0.25
Skewness-1.3609999
Sum736.9
Variance0.71075149
MonotonicityNot monotonic
2023-12-13T01:13:51.390177image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=22)
ValueCountFrequency (%)
12.0 27
42.2%
11.1 5
 
7.8%
11.7 3
 
4.7%
11.0 3
 
4.7%
10.0 3
 
4.7%
11.8 2
 
3.1%
10.5 2
 
3.1%
12.4 2
 
3.1%
10.2 2
 
3.1%
11.4 2
 
3.1%
Other values (12) 13
20.3%
ValueCountFrequency (%)
8.5 1
 
1.6%
9.0 1
 
1.6%
10.0 3
4.7%
10.2 2
 
3.1%
10.5 2
 
3.1%
10.6 1
 
1.6%
10.8 1
 
1.6%
11.0 3
4.7%
11.1 5
7.8%
11.2 1
 
1.6%
ValueCountFrequency (%)
13.2 1
 
1.6%
12.9 1
 
1.6%
12.4 2
 
3.1%
12.1 2
 
3.1%
12.0 27
42.2%
11.9 1
 
1.6%
11.8 2
 
3.1%
11.7 3
 
4.7%
11.6 1
 
1.6%
11.5 1
 
1.6%

2014_3분기
Real number (ℝ)

HIGH CORRELATION 

Distinct22
Distinct (%)34.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean11.507812
Minimum8.2
Maximum13.2
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size708.0 B
2023-12-13T01:13:51.497449image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum8.2
5-th percentile10
Q111.1
median12
Q312
95-th percentile12.355
Maximum13.2
Range5
Interquartile range (IQR)0.9

Descriptive statistics

Standard deviation0.86543955
Coefficient of variation (CV)0.075204523
Kurtosis3.075036
Mean11.507812
Median Absolute Deviation (MAD)0.25
Skewness-1.4771517
Sum736.5
Variance0.74898562
MonotonicityNot monotonic
2023-12-13T01:13:51.616998image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=22)
ValueCountFrequency (%)
12.0 26
40.6%
11.1 5
 
7.8%
11.7 3
 
4.7%
11.0 3
 
4.7%
12.1 3
 
4.7%
10.0 3
 
4.7%
11.8 2
 
3.1%
10.5 2
 
3.1%
12.4 2
 
3.1%
10.2 2
 
3.1%
Other values (12) 13
20.3%
ValueCountFrequency (%)
8.2 1
 
1.6%
9.0 1
 
1.6%
10.0 3
4.7%
10.2 2
 
3.1%
10.4 1
 
1.6%
10.5 2
 
3.1%
10.8 1
 
1.6%
11.0 3
4.7%
11.1 5
7.8%
11.2 1
 
1.6%
ValueCountFrequency (%)
13.2 1
 
1.6%
12.9 1
 
1.6%
12.4 2
 
3.1%
12.1 3
 
4.7%
12.0 26
40.6%
11.9 1
 
1.6%
11.8 2
 
3.1%
11.7 3
 
4.7%
11.6 1
 
1.6%
11.5 1
 
1.6%

2014_4분기
Real number (ℝ)

HIGH CORRELATION 

Distinct21
Distinct (%)32.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean11.435937
Minimum8
Maximum13.1
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size708.0 B
2023-12-13T01:13:51.723931image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum8
5-th percentile10
Q111
median11.85
Q312
95-th percentile12.1
Maximum13.1
Range5.1
Interquartile range (IQR)1

Descriptive statistics

Standard deviation0.86764911
Coefficient of variation (CV)0.075870396
Kurtosis3.5285022
Mean11.435937
Median Absolute Deviation (MAD)0.25
Skewness-1.6190214
Sum731.9
Variance0.75281498
MonotonicityNot monotonic
2023-12-13T01:13:51.837958image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=21)
ValueCountFrequency (%)
12.0 21
32.8%
11.9 5
 
7.8%
11.0 5
 
7.8%
11.7 4
 
6.2%
11.1 4
 
6.2%
11.4 4
 
6.2%
12.1 3
 
4.7%
10.5 2
 
3.1%
12.3 2
 
3.1%
10.2 2
 
3.1%
Other values (11) 12
18.8%
ValueCountFrequency (%)
8.0 1
 
1.6%
9.0 1
 
1.6%
9.5 1
 
1.6%
10.0 2
 
3.1%
10.2 2
 
3.1%
10.4 1
 
1.6%
10.5 2
 
3.1%
10.8 1
 
1.6%
10.9 1
 
1.6%
11.0 5
7.8%
ValueCountFrequency (%)
13.1 1
 
1.6%
12.3 2
 
3.1%
12.1 3
 
4.7%
12.0 21
32.8%
11.9 5
 
7.8%
11.8 1
 
1.6%
11.7 4
 
6.2%
11.6 1
 
1.6%
11.4 4
 
6.2%
11.2 1
 
1.6%

2015_1분기
Real number (ℝ)

HIGH CORRELATION 

Distinct23
Distinct (%)35.9%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean11.35625
Minimum8
Maximum12.7
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size708.0 B
2023-12-13T01:13:52.285813image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum8
5-th percentile10
Q111
median11.6
Q312
95-th percentile12.085
Maximum12.7
Range4.7
Interquartile range (IQR)1

Descriptive statistics

Standard deviation0.83701567
Coefficient of variation (CV)0.073705288
Kurtosis3.6798165
Mean11.35625
Median Absolute Deviation (MAD)0.4
Skewness-1.7020064
Sum726.8
Variance0.70059524
MonotonicityNot monotonic
2023-12-13T01:13:52.391953image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=23)
ValueCountFrequency (%)
12.0 15
23.4%
11.6 6
 
9.4%
11.8 6
 
9.4%
11.0 4
 
6.2%
11.7 3
 
4.7%
10.0 3
 
4.7%
11.4 3
 
4.7%
10.9 3
 
4.7%
11.5 3
 
4.7%
11.2 2
 
3.1%
Other values (13) 16
25.0%
ValueCountFrequency (%)
8.0 1
 
1.6%
9.0 1
 
1.6%
9.5 1
 
1.6%
10.0 3
4.7%
10.2 1
 
1.6%
10.3 1
 
1.6%
10.4 1
 
1.6%
10.5 1
 
1.6%
10.8 2
3.1%
10.9 3
4.7%
ValueCountFrequency (%)
12.7 1
 
1.6%
12.2 1
 
1.6%
12.1 2
 
3.1%
12.0 15
23.4%
11.9 2
 
3.1%
11.8 6
 
9.4%
11.7 3
 
4.7%
11.6 6
 
9.4%
11.5 3
 
4.7%
11.4 3
 
4.7%

2015_2분기
Real number (ℝ)

HIGH CORRELATION 

Distinct24
Distinct (%)37.5%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean11.309375
Minimum7.3
Maximum12.7
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size708.0 B
2023-12-13T01:13:52.491559image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum7.3
5-th percentile9.915
Q110.9
median11.6
Q312
95-th percentile12
Maximum12.7
Range5.4
Interquartile range (IQR)1.1

Descriptive statistics

Standard deviation0.8842033
Coefficient of variation (CV)0.078183215
Kurtosis6.0016043
Mean11.309375
Median Absolute Deviation (MAD)0.4
Skewness-1.9989453
Sum723.8
Variance0.78181548
MonotonicityNot monotonic
2023-12-13T01:13:52.600560image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=24)
ValueCountFrequency (%)
12.0 15
23.4%
11.8 6
 
9.4%
11.6 5
 
7.8%
10.8 5
 
7.8%
11.4 4
 
6.2%
11.3 3
 
4.7%
11.0 3
 
4.7%
10.0 2
 
3.1%
10.9 2
 
3.1%
11.9 2
 
3.1%
Other values (14) 17
26.6%
ValueCountFrequency (%)
7.3 1
 
1.6%
9.0 1
 
1.6%
9.5 1
 
1.6%
9.9 1
 
1.6%
10.0 2
 
3.1%
10.2 1
 
1.6%
10.3 1
 
1.6%
10.4 1
 
1.6%
10.5 1
 
1.6%
10.8 5
7.8%
ValueCountFrequency (%)
12.7 1
 
1.6%
12.2 1
 
1.6%
12.1 1
 
1.6%
12.0 15
23.4%
11.9 2
 
3.1%
11.8 6
 
9.4%
11.7 2
 
3.1%
11.6 5
 
7.8%
11.5 2
 
3.1%
11.4 4
 
6.2%

2015_3분기
Real number (ℝ)

HIGH CORRELATION 

Distinct25
Distinct (%)39.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean11.2875
Minimum7.3
Maximum12.7
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size708.0 B
2023-12-13T01:13:52.712940image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum7.3
5-th percentile9.915
Q110.9
median11.6
Q312
95-th percentile12
Maximum12.7
Range5.4
Interquartile range (IQR)1.1

Descriptive statistics

Standard deviation0.88452301
Coefficient of variation (CV)0.078363057
Kurtosis5.7784454
Mean11.2875
Median Absolute Deviation (MAD)0.4
Skewness-1.9334711
Sum722.4
Variance0.78238095
MonotonicityNot monotonic
2023-12-13T01:13:52.823890image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=25)
ValueCountFrequency (%)
12.0 15
23.4%
11.8 6
 
9.4%
11.6 5
 
7.8%
11.0 4
 
6.2%
10.8 4
 
6.2%
11.9 3
 
4.7%
11.2 3
 
4.7%
11.3 3
 
4.7%
10.0 2
 
3.1%
10.9 2
 
3.1%
Other values (15) 17
26.6%
ValueCountFrequency (%)
7.3 1
1.6%
9.0 1
1.6%
9.5 1
1.6%
9.9 1
1.6%
10.0 2
3.1%
10.2 1
1.6%
10.3 1
1.6%
10.4 1
1.6%
10.5 1
1.6%
10.6 1
1.6%
ValueCountFrequency (%)
12.7 1
 
1.6%
12.2 1
 
1.6%
12.0 15
23.4%
11.9 3
 
4.7%
11.8 6
 
9.4%
11.7 2
 
3.1%
11.6 5
 
7.8%
11.5 1
 
1.6%
11.4 2
 
3.1%
11.3 3
 
4.7%

2015_4분기
Real number (ℝ)

HIGH CORRELATION 

Distinct23
Distinct (%)35.9%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean11.257812
Minimum7.3
Maximum12.7
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size708.0 B
2023-12-13T01:13:52.964200image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum7.3
5-th percentile9.915
Q110.8
median11.55
Q311.9
95-th percentile12
Maximum12.7
Range5.4
Interquartile range (IQR)1.1

Descriptive statistics

Standard deviation0.88869526
Coefficient of variation (CV)0.078940315
Kurtosis5.3637675
Mean11.257812
Median Absolute Deviation (MAD)0.45
Skewness-1.8399614
Sum720.5
Variance0.78977927
MonotonicityNot monotonic
2023-12-13T01:13:53.080927image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=23)
ValueCountFrequency (%)
12.0 13
20.3%
11.9 5
 
7.8%
10.8 5
 
7.8%
11.7 5
 
7.8%
11.2 5
 
7.8%
11.6 4
 
6.2%
11.0 4
 
6.2%
11.8 3
 
4.7%
11.5 2
 
3.1%
10.0 2
 
3.1%
Other values (13) 16
25.0%
ValueCountFrequency (%)
7.3 1
 
1.6%
9.0 1
 
1.6%
9.5 1
 
1.6%
9.9 1
 
1.6%
10.0 2
 
3.1%
10.2 1
 
1.6%
10.3 2
 
3.1%
10.4 2
 
3.1%
10.7 1
 
1.6%
10.8 5
7.8%
ValueCountFrequency (%)
12.7 1
 
1.6%
12.2 1
 
1.6%
12.0 13
20.3%
11.9 5
 
7.8%
11.8 3
 
4.7%
11.7 5
 
7.8%
11.6 4
 
6.2%
11.5 2
 
3.1%
11.4 2
 
3.1%
11.2 5
 
7.8%

2016_1분기
Real number (ℝ)

HIGH CORRELATION 

Distinct24
Distinct (%)37.5%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean11.2375
Minimum7.3
Maximum12.7
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size708.0 B
2023-12-13T01:13:53.195079image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum7.3
5-th percentile9.745
Q110.8
median11.5
Q311.9
95-th percentile12
Maximum12.7
Range5.4
Interquartile range (IQR)1.1

Descriptive statistics

Standard deviation0.89540272
Coefficient of variation (CV)0.079679886
Kurtosis5.0077463
Mean11.2375
Median Absolute Deviation (MAD)0.5
Skewness-1.7715962
Sum719.2
Variance0.80174603
MonotonicityNot monotonic
2023-12-13T01:13:53.301342image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=24)
ValueCountFrequency (%)
12.0 12
18.8%
11.9 6
 
9.4%
11.0 4
 
6.2%
11.7 4
 
6.2%
11.6 4
 
6.2%
11.2 4
 
6.2%
11.5 3
 
4.7%
11.1 3
 
4.7%
11.8 3
 
4.7%
10.8 3
 
4.7%
Other values (14) 18
28.1%
ValueCountFrequency (%)
7.3 1
1.6%
9.0 1
1.6%
9.5 1
1.6%
9.7 1
1.6%
10.0 2
3.1%
10.2 1
1.6%
10.3 2
3.1%
10.4 2
3.1%
10.6 2
3.1%
10.7 1
1.6%
ValueCountFrequency (%)
12.7 1
 
1.6%
12.2 1
 
1.6%
12.0 12
18.8%
11.9 6
9.4%
11.8 3
 
4.7%
11.7 4
 
6.2%
11.6 4
 
6.2%
11.5 3
 
4.7%
11.4 1
 
1.6%
11.2 4
 
6.2%

2016_2분기
Real number (ℝ)

HIGH CORRELATION 

Distinct24
Distinct (%)37.5%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean11.2125
Minimum7.3
Maximum12.7
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size708.0 B
2023-12-13T01:13:53.404888image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum7.3
5-th percentile9.745
Q110.8
median11.45
Q311.9
95-th percentile12
Maximum12.7
Range5.4
Interquartile range (IQR)1.1

Descriptive statistics

Standard deviation0.89522543
Coefficient of variation (CV)0.079841733
Kurtosis4.8086977
Mean11.2125
Median Absolute Deviation (MAD)0.55
Skewness-1.710799
Sum717.6
Variance0.80142857
MonotonicityNot monotonic
2023-12-13T01:13:53.519166image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=24)
ValueCountFrequency (%)
12.0 11
17.2%
11.7 5
 
7.8%
10.8 5
 
7.8%
11.9 5
 
7.8%
11.2 4
 
6.2%
11.8 4
 
6.2%
11.0 3
 
4.7%
11.6 3
 
4.7%
10.7 2
 
3.1%
10.0 2
 
3.1%
Other values (14) 20
31.2%
ValueCountFrequency (%)
7.3 1
1.6%
9.0 1
1.6%
9.5 1
1.6%
9.7 1
1.6%
10.0 2
3.1%
10.2 2
3.1%
10.3 1
1.6%
10.4 2
3.1%
10.6 2
3.1%
10.7 2
3.1%
ValueCountFrequency (%)
12.7 1
 
1.6%
12.2 1
 
1.6%
12.0 11
17.2%
11.9 5
7.8%
11.8 4
 
6.2%
11.7 5
7.8%
11.6 3
 
4.7%
11.5 2
 
3.1%
11.4 2
 
3.1%
11.3 1
 
1.6%

2016_3분기
Real number (ℝ)

HIGH CORRELATION 

Distinct25
Distinct (%)39.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean11.132813
Minimum7.2
Maximum12.7
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size708.0 B
2023-12-13T01:13:53.625738image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum7.2
5-th percentile9.73
Q110.7
median11.2
Q311.9
95-th percentile12
Maximum12.7
Range5.5
Interquartile range (IQR)1.2

Descriptive statistics

Standard deviation0.90484668
Coefficient of variation (CV)0.081277456
Kurtosis4.5407392
Mean11.132813
Median Absolute Deviation (MAD)0.6
Skewness-1.5475755
Sum712.5
Variance0.81874752
MonotonicityNot monotonic
2023-12-13T01:13:53.746105image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=25)
ValueCountFrequency (%)
12.0 11
17.2%
10.8 6
 
9.4%
11.0 5
 
7.8%
11.5 4
 
6.2%
10.7 4
 
6.2%
11.9 4
 
6.2%
11.8 3
 
4.7%
11.7 3
 
4.7%
10.0 2
 
3.1%
11.2 2
 
3.1%
Other values (15) 20
31.2%
ValueCountFrequency (%)
7.2 1
1.6%
9.0 1
1.6%
9.5 1
1.6%
9.7 1
1.6%
9.9 1
1.6%
10.0 2
3.1%
10.2 1
1.6%
10.3 1
1.6%
10.4 2
3.1%
10.5 1
1.6%
ValueCountFrequency (%)
12.7 1
 
1.6%
12.2 1
 
1.6%
12.0 11
17.2%
11.9 4
 
6.2%
11.8 3
 
4.7%
11.7 3
 
4.7%
11.6 2
 
3.1%
11.5 4
 
6.2%
11.4 2
 
3.1%
11.2 2
 
3.1%

2016_4분기
Real number (ℝ)

HIGH CORRELATION 

Distinct27
Distinct (%)42.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean11.073438
Minimum7.2
Maximum12.6
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size708.0 B
2023-12-13T01:13:53.897745image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum7.2
5-th percentile9.515
Q110.6
median11.1
Q311.825
95-th percentile12
Maximum12.6
Range5.4
Interquartile range (IQR)1.225

Descriptive statistics

Standard deviation0.92586162
Coefficient of variation (CV)0.08361104
Kurtosis3.6441
Mean11.073438
Median Absolute Deviation (MAD)0.65
Skewness-1.3941868
Sum708.7
Variance0.85721974
MonotonicityNot monotonic
2023-12-13T01:13:54.027887image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=27)
ValueCountFrequency (%)
12.0 9
 
14.1%
11.9 5
 
7.8%
11.8 4
 
6.2%
10.8 4
 
6.2%
11.4 3
 
4.7%
11.5 3
 
4.7%
10.5 3
 
4.7%
10.9 3
 
4.7%
11.0 3
 
4.7%
11.7 3
 
4.7%
Other values (17) 24
37.5%
ValueCountFrequency (%)
7.2 1
1.6%
9.0 1
1.6%
9.4 1
1.6%
9.5 1
1.6%
9.6 1
1.6%
9.9 1
1.6%
10.0 1
1.6%
10.1 1
1.6%
10.3 2
3.1%
10.4 2
3.1%
ValueCountFrequency (%)
12.6 1
 
1.6%
12.2 1
 
1.6%
12.0 9
14.1%
11.9 5
7.8%
11.8 4
6.2%
11.7 3
 
4.7%
11.6 1
 
1.6%
11.5 3
 
4.7%
11.4 3
 
4.7%
11.2 1
 
1.6%

Interactions

2023-12-13T01:13:47.565878image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T01:13:25.155080image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T01:13:26.547835image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T01:13:28.232076image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T01:13:29.769688image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T01:13:31.137312image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T01:13:32.829914image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T01:13:34.199941image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T01:13:35.571918image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T01:13:37.051663image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T01:13:38.677335image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T01:13:40.092574image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T01:13:41.438831image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T01:13:42.863861image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T01:13:44.296979image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T01:13:46.117554image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T01:13:47.662516image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T01:13:25.238892image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T01:13:26.638579image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T01:13:28.320920image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T01:13:29.841945image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T01:13:31.218600image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T01:13:32.919438image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T01:13:34.285170image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T01:13:35.665989image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T01:13:37.124029image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T01:13:38.762719image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T01:13:40.160415image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T01:13:41.511465image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T01:13:42.950153image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T01:13:44.401042image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T01:13:46.194696image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T01:13:47.782158image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T01:13:25.353937image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T01:13:26.756895image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T01:13:28.475687image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T01:13:29.944423image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T01:13:31.647632image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T01:13:33.017651image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T01:13:34.376739image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
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2023-12-13T01:13:37.218220image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
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2023-12-13T01:13:47.353747image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T01:13:49.094694image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T01:13:26.453687image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T01:13:28.114155image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T01:13:29.673423image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T01:13:31.054112image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T01:13:32.739358image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T01:13:34.109350image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T01:13:35.464052image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T01:13:36.962828image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T01:13:38.599810image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T01:13:40.011920image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T01:13:41.361198image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T01:13:42.769043image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T01:13:44.208076image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T01:13:46.028275image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T01:13:47.448454image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-13T01:13:54.133740image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
지역2013_1분기2013_2분기2013_3분기2013_4분기2014_1분기2014_2분기2014_3분기2014_4분기2015_1분기2015_2분기2015_3분기2015_4분기2016_1분기2016_2분기2016_3분기2016_4분기
지역1.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.000
2013_1분기1.0001.0000.9910.9920.9850.9810.9530.9350.8110.9020.7020.6980.6690.6670.6660.7030.687
2013_2분기1.0000.9911.0000.9930.9880.9850.9640.9480.8090.9220.7430.7410.7260.7220.7230.7140.688
2013_3분기1.0000.9920.9931.0000.9930.9890.9710.9570.8550.9500.8170.8170.7990.7960.7970.7980.779
2013_4분기1.0000.9850.9880.9931.0000.9980.9850.9770.8820.9550.8490.8470.8310.8290.8290.8270.818
2014_1분기1.0000.9810.9850.9890.9981.0000.9890.9810.8940.9610.8680.8650.8480.8450.8440.8360.825
2014_2분기1.0000.9530.9640.9710.9850.9891.0000.9950.9200.9700.9070.9040.8930.8910.8900.8920.898
2014_3분기1.0000.9350.9480.9570.9770.9810.9951.0000.9600.9660.9130.9100.8970.8960.8940.8850.880
2014_4분기1.0000.8110.8090.8550.8820.8940.9200.9601.0000.9480.9390.9360.9300.9290.9270.9140.905
2015_1분기1.0000.9020.9220.9500.9550.9610.9700.9660.9481.0000.9450.9410.9430.9400.9360.9260.912
2015_2분기1.0000.7020.7430.8170.8490.8680.9070.9130.9390.9451.0001.0000.9990.9990.9990.9920.990
2015_3분기1.0000.6980.7410.8170.8470.8650.9040.9100.9360.9411.0001.0001.0000.9990.9990.9920.991
2015_4분기1.0000.6690.7260.7990.8310.8480.8930.8970.9300.9430.9991.0001.0001.0001.0000.9940.993
2016_1분기1.0000.6670.7220.7960.8290.8450.8910.8960.9290.9400.9990.9991.0001.0001.0000.9950.993
2016_2분기1.0000.6660.7230.7970.8290.8440.8900.8940.9270.9360.9990.9991.0001.0001.0000.9950.992
2016_3분기1.0000.7030.7140.7980.8270.8360.8920.8850.9140.9260.9920.9920.9940.9950.9951.0000.999
2016_4분기1.0000.6870.6880.7790.8180.8250.8980.8800.9050.9120.9900.9910.9930.9930.9920.9991.000
2023-12-13T01:13:54.322531image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2013_1분기2013_2분기2013_3분기2013_4분기2014_1분기2014_2분기2014_3분기2014_4분기2015_1분기2015_2분기2015_3분기2015_4분기2016_1분기2016_2분기2016_3분기2016_4분기
2013_1분기1.0000.9470.9160.7970.7290.7210.7170.6790.5830.5760.5600.5540.5480.5490.5870.590
2013_2분기0.9471.0000.9700.8480.7770.7680.7630.7240.6260.6030.5880.5840.5780.5530.5690.567
2013_3분기0.9160.9701.0000.8780.8090.7980.7920.7590.6670.6440.6310.6230.6180.5930.6080.606
2013_4분기0.7970.8480.8781.0000.9410.9340.9290.8990.8130.7920.7790.7670.7610.7400.7500.740
2014_1분기0.7290.7770.8090.9411.0000.9940.9880.9520.8690.8420.8270.8200.8120.7970.7960.780
2014_2분기0.7210.7680.7980.9340.9941.0000.9950.9600.8790.8530.8370.8290.8200.8050.8080.793
2014_3분기0.7170.7630.7920.9290.9880.9951.0000.9490.8630.8350.8220.8130.8030.7890.7960.782
2014_4분기0.6790.7240.7590.8990.9520.9600.9491.0000.9300.9100.8900.8770.8750.8620.8550.834
2015_1분기0.5830.6260.6670.8130.8690.8790.8630.9301.0000.9790.9690.9590.9550.9420.9250.898
2015_2분기0.5760.6030.6440.7920.8420.8530.8350.9100.9791.0000.9940.9860.9840.9730.9500.923
2015_3분기0.5600.5880.6310.7790.8270.8370.8220.8900.9690.9941.0000.9940.9910.9800.9530.927
2015_4분기0.5540.5840.6230.7670.8200.8290.8130.8770.9590.9860.9941.0000.9970.9860.9560.930
2016_1분기0.5480.5780.6180.7610.8120.8200.8030.8750.9550.9840.9910.9971.0000.9930.9600.935
2016_2분기0.5490.5530.5930.7400.7970.8050.7890.8620.9420.9730.9800.9860.9931.0000.9690.946
2016_3분기0.5870.5690.6080.7500.7960.8080.7960.8550.9250.9500.9530.9560.9600.9691.0000.988
2016_4분기0.5900.5670.6060.7400.7800.7930.7820.8340.8980.9230.9270.9300.9350.9460.9881.000

Missing values

2023-12-13T01:13:49.241440image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-13T01:13:49.472896image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Nullity matrix is a data-dense display which lets you quickly visually pick out patterns in data completion.

Sample

지역2013_1분기2013_2분기2013_3분기2013_4분기2014_1분기2014_2분기2014_3분기2014_4분기2015_1분기2015_2분기2015_3분기2015_4분기2016_1분기2016_2분기2016_3분기2016_4분기
0서울12.012.011.911.911.811.811.811.711.611.611.611.511.511.511.411.4
1서울 도심11.611.611.611.511.511.411.411.411.411.311.311.211.211.210.810.7
2서울 도심 광화문11.711.711.711.711.511.411.411.411.611.511.511.511.511.511.511.5
3서울 도심 동대문11.111.111.111.111.111.111.111.111.411.411.411.411.411.410.510.5
4서울 도심 명동10.610.610.610.510.510.510.510.510.510.510.510.310.310.210.210.1
5서울 도심 서울역12.012.012.012.012.012.012.012.012.011.411.211.011.011.011.010.9
6서울 도심 종로12.012.012.012.011.911.511.511.411.211.211.211.211.211.211.011.0
7서울 도심 충무로12.012.012.012.012.012.012.012.011.811.811.811.711.711.710.810.5
8서울 강남12.612.612.612.512.512.412.412.311.811.811.811.811.811.811.811.8
9서울 강남 강남대로12.412.412.412.412.412.412.412.112.212.212.212.212.212.212.212.2
지역2013_1분기2013_2분기2013_3분기2013_4분기2014_1분기2014_2분기2014_3분기2014_4분기2015_1분기2015_2분기2015_3분기2015_4분기2016_1분기2016_2분기2016_3분기2016_4분기
54경기 일산동구12.012.012.010.09.08.58.28.08.07.37.37.37.37.37.27.2
55경기 평촌범계12.012.012.012.012.012.012.012.011.911.911.911.911.911.911.911.9
56강원11.411.411.411.411.410.810.810.810.910.910.910.910.910.810.710.3
57충북12.112.112.112.112.112.112.112.112.112.112.012.012.012.012.011.9
58충남11.111.111.111.111.111.111.111.110.810.810.610.410.410.410.410.4
59전북12.012.012.012.012.012.012.012.012.012.011.911.911.911.911.911.9
60전남11.911.911.911.011.010.610.410.410.09.99.99.99.79.79.79.6
61경북11.211.211.211.111.111.111.111.011.010.810.810.810.710.710.710.6
62경남12.012.012.012.012.012.012.011.911.811.811.811.711.611.311.211.0
63제주10.010.010.010.010.010.010.010.010.010.010.010.010.010.010.010.0