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 소득수익률 데이터입니다. - (단위 : %) - 공표시기 : 계간(분기)
Author한국부동산원
URLhttps://www.data.go.kr/data/15043984/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 07:02:24.266020
Analysis finished2023-12-12 07:02:54.095378
Duration29.83 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
2023-12-12T16:02:54.255050image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length12
Median length8
Mean length6.40625
Min length2

Characters and Unicode

Total characters410
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%
2023-12-12T16:02:54.669468image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
81
19.8%
31
 
7.6%
31
 
7.6%
16
 
3.9%
14
 
3.4%
14
 
3.4%
14
 
3.4%
11
 
2.7%
9
 
2.2%
9
 
2.2%
Other values (77) 180
43.9%

Most occurring categories

ValueCountFrequency (%)
Other Letter 328
80.0%
Space Separator 81
 
19.8%
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 (%)
81
100.0%
Other Punctuation
ValueCountFrequency (%)
/ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 328
80.0%
Common 82
 
20.0%

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 (%)
81
98.8%
/ 1
 
1.2%

Most occurring blocks

ValueCountFrequency (%)
Hangul 328
80.0%
ASCII 82
 
20.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
81
98.8%
/ 1
 
1.2%
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 

Distinct54
Distinct (%)84.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1.2948437
Minimum0.53
Maximum2.27
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size708.0 B
2023-12-12T16:02:54.855410image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0.53
5-th percentile0.7515
Q11.04
median1.32
Q31.49
95-th percentile1.7555
Maximum2.27
Range1.74
Interquartile range (IQR)0.45

Descriptive statistics

Standard deviation0.35657984
Coefficient of variation (CV)0.27538445
Kurtosis0.65020035
Mean1.2948437
Median Absolute Deviation (MAD)0.225
Skewness0.31918007
Sum82.87
Variance0.12714918
MonotonicityNot monotonic
2023-12-12T16:02:55.033516image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1.49 3
 
4.7%
1.32 3
 
4.7%
1.08 2
 
3.1%
1.53 2
 
3.1%
1.37 2
 
3.1%
1.04 2
 
3.1%
1.45 2
 
3.1%
1.65 2
 
3.1%
1.22 1
 
1.6%
1.56 1
 
1.6%
Other values (44) 44
68.8%
ValueCountFrequency (%)
0.53 1
1.6%
0.62 1
1.6%
0.63 1
1.6%
0.75 1
1.6%
0.76 1
1.6%
0.79 1
1.6%
0.82 1
1.6%
0.9 1
1.6%
0.91 1
1.6%
0.92 1
1.6%
ValueCountFrequency (%)
2.27 1
1.6%
2.26 1
1.6%
2.08 1
1.6%
1.76 1
1.6%
1.73 1
1.6%
1.72 1
1.6%
1.65 2
3.1%
1.64 1
1.6%
1.63 1
1.6%
1.62 1
1.6%

2013_2분기
Real number (ℝ)

HIGH CORRELATION 

Distinct53
Distinct (%)82.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1.2785938
Minimum0.52
Maximum2.25
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size708.0 B
2023-12-12T16:02:55.172755image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0.52
5-th percentile0.743
Q11.0475
median1.28
Q31.5125
95-th percentile1.7485
Maximum2.25
Range1.73
Interquartile range (IQR)0.465

Descriptive statistics

Standard deviation0.34115521
Coefficient of variation (CV)0.26682065
Kurtosis0.41260422
Mean1.2785938
Median Absolute Deviation (MAD)0.235
Skewness0.10408203
Sum81.83
Variance0.11638688
MonotonicityNot monotonic
2023-12-12T16:02:55.327034image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1.29 3
 
4.7%
1.37 3
 
4.7%
1.63 3
 
4.7%
1.17 2
 
3.1%
1.45 2
 
3.1%
1.4 2
 
3.1%
1.27 2
 
3.1%
1.52 2
 
3.1%
1.43 1
 
1.6%
1.51 1
 
1.6%
Other values (43) 43
67.2%
ValueCountFrequency (%)
0.52 1
1.6%
0.54 1
1.6%
0.63 1
1.6%
0.74 1
1.6%
0.76 1
1.6%
0.79 1
1.6%
0.83 1
1.6%
0.86 1
1.6%
0.92 1
1.6%
0.93 1
1.6%
ValueCountFrequency (%)
2.25 1
 
1.6%
2.08 1
 
1.6%
1.76 1
 
1.6%
1.75 1
 
1.6%
1.74 1
 
1.6%
1.7 1
 
1.6%
1.66 1
 
1.6%
1.64 1
 
1.6%
1.63 3
4.7%
1.58 1
 
1.6%

2013_3분기
Real number (ℝ)

HIGH CORRELATION 

Distinct49
Distinct (%)76.6%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1.0125
Minimum0.16
Maximum1.95
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size708.0 B
2023-12-12T16:02:55.508301image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0.16
5-th percentile0.3975
Q10.795
median1.04
Q31.265
95-th percentile1.5385
Maximum1.95
Range1.79
Interquartile range (IQR)0.47

Descriptive statistics

Standard deviation0.35979271
Coefficient of variation (CV)0.35535082
Kurtosis-0.067497315
Mean1.0125
Median Absolute Deviation (MAD)0.25
Skewness-0.17290148
Sum64.8
Variance0.12945079
MonotonicityNot monotonic
2023-12-12T16:02:55.679588image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=49)
ValueCountFrequency (%)
0.8 3
 
4.7%
0.94 3
 
4.7%
1.11 3
 
4.7%
1.31 2
 
3.1%
1.04 2
 
3.1%
1.0 2
 
3.1%
1.14 2
 
3.1%
1.32 2
 
3.1%
1.19 2
 
3.1%
1.09 2
 
3.1%
Other values (39) 41
64.1%
ValueCountFrequency (%)
0.16 1
1.6%
0.29 1
1.6%
0.32 1
1.6%
0.39 1
1.6%
0.44 1
1.6%
0.45 1
1.6%
0.51 1
1.6%
0.56 1
1.6%
0.57 1
1.6%
0.61 1
1.6%
ValueCountFrequency (%)
1.95 1
1.6%
1.58 1
1.6%
1.55 1
1.6%
1.54 1
1.6%
1.53 1
1.6%
1.49 1
1.6%
1.43 1
1.6%
1.4 2
3.1%
1.39 1
1.6%
1.37 1
1.6%

2013_4분기
Real number (ℝ)

HIGH CORRELATION 

Distinct49
Distinct (%)76.6%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1.2278125
Minimum0.46
Maximum1.98
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size708.0 B
2023-12-12T16:02:55.830374image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0.46
5-th percentile0.7275
Q11.0375
median1.23
Q31.44
95-th percentile1.6385
Maximum1.98
Range1.52
Interquartile range (IQR)0.4025

Descriptive statistics

Standard deviation0.30972834
Coefficient of variation (CV)0.2522603
Kurtosis0.098495516
Mean1.2278125
Median Absolute Deviation (MAD)0.205
Skewness-0.29552539
Sum78.58
Variance0.095931647
MonotonicityNot monotonic
2023-12-12T16:02:56.350125image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=49)
ValueCountFrequency (%)
1.35 3
 
4.7%
1.22 2
 
3.1%
1.0 2
 
3.1%
1.44 2
 
3.1%
1.51 2
 
3.1%
1.08 2
 
3.1%
1.23 2
 
3.1%
1.49 2
 
3.1%
1.3 2
 
3.1%
1.13 2
 
3.1%
Other values (39) 43
67.2%
ValueCountFrequency (%)
0.46 1
1.6%
0.53 1
1.6%
0.54 1
1.6%
0.72 1
1.6%
0.77 1
1.6%
0.78 1
1.6%
0.81 1
1.6%
0.82 1
1.6%
0.87 1
1.6%
0.88 1
1.6%
ValueCountFrequency (%)
1.98 1
1.6%
1.75 1
1.6%
1.72 1
1.6%
1.64 1
1.6%
1.63 1
1.6%
1.62 1
1.6%
1.61 2
3.1%
1.6 1
1.6%
1.57 1
1.6%
1.51 2
3.1%

2014_1분기
Real number (ℝ)

HIGH CORRELATION 

Distinct53
Distinct (%)82.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1.2375
Minimum0.48
Maximum2.02
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size708.0 B
2023-12-12T16:02:56.493361image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0.48
5-th percentile0.7915
Q11.0075
median1.25
Q31.4175
95-th percentile1.6685
Maximum2.02
Range1.54
Interquartile range (IQR)0.41

Descriptive statistics

Standard deviation0.30704945
Coefficient of variation (CV)0.24812077
Kurtosis-0.057278063
Mean1.2375
Median Absolute Deviation (MAD)0.215
Skewness-0.16712639
Sum79.2
Variance0.094279365
MonotonicityNot monotonic
2023-12-12T16:02:56.629706image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1.38 3
 
4.7%
1.39 2
 
3.1%
1.12 2
 
3.1%
0.99 2
 
3.1%
0.81 2
 
3.1%
1.19 2
 
3.1%
1.24 2
 
3.1%
0.96 2
 
3.1%
1.41 2
 
3.1%
1.21 2
 
3.1%
Other values (43) 43
67.2%
ValueCountFrequency (%)
0.48 1
1.6%
0.58 1
1.6%
0.63 1
1.6%
0.79 1
1.6%
0.8 1
1.6%
0.81 2
3.1%
0.82 1
1.6%
0.89 1
1.6%
0.91 1
1.6%
0.96 2
3.1%
ValueCountFrequency (%)
2.02 1
1.6%
1.75 1
1.6%
1.69 1
1.6%
1.67 1
1.6%
1.66 1
1.6%
1.64 1
1.6%
1.62 1
1.6%
1.61 1
1.6%
1.59 1
1.6%
1.58 1
1.6%

2014_2분기
Real number (ℝ)

HIGH CORRELATION 

Distinct44
Distinct (%)68.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1.2314063
Minimum0.46
Maximum1.78
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size708.0 B
2023-12-12T16:02:56.786619image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0.46
5-th percentile0.7745
Q11.035
median1.26
Q31.45
95-th percentile1.684
Maximum1.78
Range1.32
Interquartile range (IQR)0.415

Descriptive statistics

Standard deviation0.29591326
Coefficient of variation (CV)0.24030515
Kurtosis-0.21390873
Mean1.2314063
Median Absolute Deviation (MAD)0.21
Skewness-0.36691863
Sum78.81
Variance0.087564658
MonotonicityNot monotonic
2023-12-12T16:02:56.961900image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=44)
ValueCountFrequency (%)
1.56 3
 
4.7%
1.47 3
 
4.7%
1.3 3
 
4.7%
1.11 2
 
3.1%
1.24 2
 
3.1%
1.32 2
 
3.1%
1.26 2
 
3.1%
1.42 2
 
3.1%
1.02 2
 
3.1%
1.04 2
 
3.1%
Other values (34) 41
64.1%
ValueCountFrequency (%)
0.46 1
1.6%
0.58 1
1.6%
0.67 1
1.6%
0.77 1
1.6%
0.8 2
3.1%
0.81 1
1.6%
0.83 1
1.6%
0.86 1
1.6%
0.89 1
1.6%
0.92 1
1.6%
ValueCountFrequency (%)
1.78 2
3.1%
1.71 1
 
1.6%
1.69 1
 
1.6%
1.65 2
3.1%
1.59 1
 
1.6%
1.56 3
4.7%
1.49 1
 
1.6%
1.47 3
4.7%
1.46 1
 
1.6%
1.45 2
3.1%

2014_3분기
Real number (ℝ)

HIGH CORRELATION 

Distinct51
Distinct (%)79.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.98859375
Minimum0.19
Maximum1.7
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size708.0 B
2023-12-12T16:02:57.119727image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0.19
5-th percentile0.429
Q10.755
median1.02
Q31.2325
95-th percentile1.4785
Maximum1.7
Range1.51
Interquartile range (IQR)0.4775

Descriptive statistics

Standard deviation0.33724781
Coefficient of variation (CV)0.34113893
Kurtosis-0.39541633
Mean0.98859375
Median Absolute Deviation (MAD)0.24
Skewness-0.27083231
Sum63.27
Variance0.11373609
MonotonicityNot monotonic
2023-12-12T16:02:57.331989image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1.29 3
 
4.7%
0.94 2
 
3.1%
0.76 2
 
3.1%
1.03 2
 
3.1%
1.01 2
 
3.1%
0.88 2
 
3.1%
1.26 2
 
3.1%
1.47 2
 
3.1%
1.04 2
 
3.1%
0.93 2
 
3.1%
Other values (41) 43
67.2%
ValueCountFrequency (%)
0.19 1
1.6%
0.29 1
1.6%
0.33 1
1.6%
0.42 1
1.6%
0.48 1
1.6%
0.49 1
1.6%
0.54 1
1.6%
0.55 1
1.6%
0.59 1
1.6%
0.6 1
1.6%
ValueCountFrequency (%)
1.7 1
 
1.6%
1.58 1
 
1.6%
1.53 1
 
1.6%
1.48 1
 
1.6%
1.47 2
3.1%
1.44 1
 
1.6%
1.37 1
 
1.6%
1.34 1
 
1.6%
1.29 3
4.7%
1.27 1
 
1.6%

2014_4분기
Real number (ℝ)

HIGH CORRELATION 

Distinct50
Distinct (%)78.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1.178125
Minimum0.39
Maximum2.06
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size708.0 B
2023-12-12T16:02:57.506850image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0.39
5-th percentile0.586
Q10.95
median1.22
Q31.4075
95-th percentile1.637
Maximum2.06
Range1.67
Interquartile range (IQR)0.4575

Descriptive statistics

Standard deviation0.33390368
Coefficient of variation (CV)0.28341957
Kurtosis-0.021928093
Mean1.178125
Median Absolute Deviation (MAD)0.24
Skewness-0.13292186
Sum75.4
Variance0.11149167
MonotonicityNot monotonic
2023-12-12T16:02:57.698943image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1.3 4
 
6.2%
1.26 3
 
4.7%
1.23 3
 
4.7%
1.11 3
 
4.7%
1.1 2
 
3.1%
1.61 2
 
3.1%
1.33 2
 
3.1%
0.95 2
 
3.1%
1.15 2
 
3.1%
0.58 1
 
1.6%
Other values (40) 40
62.5%
ValueCountFrequency (%)
0.39 1
1.6%
0.5 1
1.6%
0.53 1
1.6%
0.58 1
1.6%
0.62 1
1.6%
0.72 1
1.6%
0.74 1
1.6%
0.78 1
1.6%
0.79 1
1.6%
0.8 1
1.6%
ValueCountFrequency (%)
2.06 1
1.6%
1.73 1
1.6%
1.67 1
1.6%
1.64 1
1.6%
1.62 1
1.6%
1.61 2
3.1%
1.57 1
1.6%
1.56 1
1.6%
1.55 1
1.6%
1.52 1
1.6%

2015_1분기
Real number (ℝ)

HIGH CORRELATION 

Distinct52
Distinct (%)81.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1.183125
Minimum0.47
Maximum2.14
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size708.0 B
2023-12-12T16:02:57.896074image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0.47
5-th percentile0.5945
Q10.995
median1.2
Q31.4225
95-th percentile1.6625
Maximum2.14
Range1.67
Interquartile range (IQR)0.4275

Descriptive statistics

Standard deviation0.33361357
Coefficient of variation (CV)0.28197661
Kurtosis0.12037157
Mean1.183125
Median Absolute Deviation (MAD)0.22
Skewness0.047658788
Sum75.72
Variance0.11129802
MonotonicityNot monotonic
2023-12-12T16:02:58.072964image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1.0 4
 
6.2%
0.88 3
 
4.7%
1.29 2
 
3.1%
1.08 2
 
3.1%
1.45 2
 
3.1%
1.58 2
 
3.1%
1.32 2
 
3.1%
1.23 2
 
3.1%
1.11 2
 
3.1%
0.7 1
 
1.6%
Other values (42) 42
65.6%
ValueCountFrequency (%)
0.47 1
 
1.6%
0.5 1
 
1.6%
0.56 1
 
1.6%
0.59 1
 
1.6%
0.62 1
 
1.6%
0.7 1
 
1.6%
0.76 1
 
1.6%
0.78 1
 
1.6%
0.82 1
 
1.6%
0.88 3
4.7%
ValueCountFrequency (%)
2.14 1
1.6%
1.76 1
1.6%
1.69 1
1.6%
1.67 1
1.6%
1.62 1
1.6%
1.61 1
1.6%
1.58 2
3.1%
1.56 1
1.6%
1.55 1
1.6%
1.54 1
1.6%

2015_2분기
Real number (ℝ)

HIGH CORRELATION 

Distinct50
Distinct (%)78.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1.1853125
Minimum0.56
Maximum2.16
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size708.0 B
2023-12-12T16:02:58.294426image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0.56
5-th percentile0.62
Q10.9575
median1.195
Q31.4175
95-th percentile1.6525
Maximum2.16
Range1.6
Interquartile range (IQR)0.46

Descriptive statistics

Standard deviation0.33586169
Coefficient of variation (CV)0.28335286
Kurtosis-0.078603384
Mean1.1853125
Median Absolute Deviation (MAD)0.24
Skewness0.16076377
Sum75.86
Variance0.11280308
MonotonicityNot monotonic
2023-12-12T16:02:58.457699image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1.11 3
 
4.7%
1.32 2
 
3.1%
1.08 2
 
3.1%
1.25 2
 
3.1%
1.35 2
 
3.1%
0.56 2
 
3.1%
1.55 2
 
3.1%
0.74 2
 
3.1%
0.62 2
 
3.1%
0.98 2
 
3.1%
Other values (40) 43
67.2%
ValueCountFrequency (%)
0.56 2
3.1%
0.58 1
1.6%
0.62 2
3.1%
0.74 2
3.1%
0.77 1
1.6%
0.79 1
1.6%
0.81 1
1.6%
0.85 1
1.6%
0.86 1
1.6%
0.88 1
1.6%
ValueCountFrequency (%)
2.16 1
1.6%
1.78 1
1.6%
1.71 1
1.6%
1.66 1
1.6%
1.61 2
3.1%
1.6 1
1.6%
1.58 1
1.6%
1.57 1
1.6%
1.55 2
3.1%
1.53 1
1.6%

2015_3분기
Real number (ℝ)

HIGH CORRELATION 

Distinct52
Distinct (%)81.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.92875
Minimum0.22
Maximum1.86
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size708.0 B
2023-12-12T16:02:58.642172image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0.22
5-th percentile0.37
Q10.7
median0.92
Q31.2025
95-th percentile1.464
Maximum1.86
Range1.64
Interquartile range (IQR)0.5025

Descriptive statistics

Standard deviation0.35740467
Coefficient of variation (CV)0.38482333
Kurtosis-0.45373981
Mean0.92875
Median Absolute Deviation (MAD)0.255
Skewness0.13653944
Sum59.44
Variance0.1277381
MonotonicityNot monotonic
2023-12-12T16:02:58.826061image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.52 3
 
4.7%
0.92 2
 
3.1%
0.81 2
 
3.1%
0.89 2
 
3.1%
1.31 2
 
3.1%
0.99 2
 
3.1%
0.37 2
 
3.1%
0.93 2
 
3.1%
0.67 2
 
3.1%
1.11 2
 
3.1%
Other values (42) 43
67.2%
ValueCountFrequency (%)
0.22 1
 
1.6%
0.34 1
 
1.6%
0.35 1
 
1.6%
0.37 2
3.1%
0.39 2
3.1%
0.51 1
 
1.6%
0.52 3
4.7%
0.53 1
 
1.6%
0.6 1
 
1.6%
0.61 1
 
1.6%
ValueCountFrequency (%)
1.86 1
1.6%
1.57 1
1.6%
1.56 1
1.6%
1.47 1
1.6%
1.43 1
1.6%
1.4 1
1.6%
1.39 1
1.6%
1.36 1
1.6%
1.31 2
3.1%
1.3 1
1.6%

2015_4분기
Real number (ℝ)

HIGH CORRELATION 

Distinct53
Distinct (%)82.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1.1325
Minimum0.44
Maximum2.15
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size708.0 B
2023-12-12T16:02:59.004203image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0.44
5-th percentile0.5515
Q10.9075
median1.1
Q31.385
95-th percentile1.6525
Maximum2.15
Range1.71
Interquartile range (IQR)0.4775

Descriptive statistics

Standard deviation0.34966651
Coefficient of variation (CV)0.3087563
Kurtosis-0.039146125
Mean1.1325
Median Absolute Deviation (MAD)0.26
Skewness0.21478651
Sum72.48
Variance0.12226667
MonotonicityNot monotonic
2023-12-12T16:02:59.201171image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1.1 3
 
4.7%
0.91 2
 
3.1%
0.93 2
 
3.1%
1.55 2
 
3.1%
1.09 2
 
3.1%
1.36 2
 
3.1%
1.41 2
 
3.1%
1.04 2
 
3.1%
0.7 2
 
3.1%
1.08 2
 
3.1%
Other values (43) 43
67.2%
ValueCountFrequency (%)
0.44 1
1.6%
0.5 1
1.6%
0.54 1
1.6%
0.55 1
1.6%
0.56 1
1.6%
0.68 1
1.6%
0.7 2
3.1%
0.72 1
1.6%
0.73 1
1.6%
0.75 1
1.6%
ValueCountFrequency (%)
2.15 1
1.6%
1.76 1
1.6%
1.68 1
1.6%
1.66 1
1.6%
1.61 1
1.6%
1.6 1
1.6%
1.59 1
1.6%
1.55 2
3.1%
1.53 1
1.6%
1.47 1
1.6%

2016_1분기
Real number (ℝ)

HIGH CORRELATION 

Distinct52
Distinct (%)81.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1.1459375
Minimum0.45
Maximum2.17
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size708.0 B
2023-12-12T16:02:59.382425image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0.45
5-th percentile0.593
Q10.925
median1.115
Q31.3825
95-th percentile1.7
Maximum2.17
Range1.72
Interquartile range (IQR)0.4575

Descriptive statistics

Standard deviation0.34679814
Coefficient of variation (CV)0.30263268
Kurtosis0.052071186
Mean1.1459375
Median Absolute Deviation (MAD)0.23
Skewness0.33897448
Sum73.34
Variance0.12026895
MonotonicityNot monotonic
2023-12-12T16:02:59.532516image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1.01 3
 
4.7%
1.32 2
 
3.1%
0.94 2
 
3.1%
0.76 2
 
3.1%
1.18 2
 
3.1%
1.1 2
 
3.1%
1.43 2
 
3.1%
1.25 2
 
3.1%
1.47 2
 
3.1%
1.11 2
 
3.1%
Other values (42) 43
67.2%
ValueCountFrequency (%)
0.45 1
1.6%
0.57 1
1.6%
0.58 1
1.6%
0.59 1
1.6%
0.61 1
1.6%
0.7 1
1.6%
0.71 1
1.6%
0.74 1
1.6%
0.76 2
3.1%
0.77 1
1.6%
ValueCountFrequency (%)
2.17 1
1.6%
1.76 1
1.6%
1.75 1
1.6%
1.7 2
3.1%
1.63 1
1.6%
1.61 1
1.6%
1.58 1
1.6%
1.55 1
1.6%
1.54 1
1.6%
1.47 2
3.1%

2016_2분기
Real number (ℝ)

HIGH CORRELATION 

Distinct51
Distinct (%)79.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1.139375
Minimum0.44
Maximum2.16
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size708.0 B
2023-12-12T16:02:59.706821image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0.44
5-th percentile0.59
Q10.9
median1.125
Q31.3525
95-th percentile1.674
Maximum2.16
Range1.72
Interquartile range (IQR)0.4525

Descriptive statistics

Standard deviation0.3450966
Coefficient of variation (CV)0.30288237
Kurtosis0.072744289
Mean1.139375
Median Absolute Deviation (MAD)0.225
Skewness0.28324927
Sum72.92
Variance0.11909167
MonotonicityNot monotonic
2023-12-12T16:02:59.888232image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1.21 3
 
4.7%
0.99 2
 
3.1%
1.42 2
 
3.1%
0.72 2
 
3.1%
0.59 2
 
3.1%
1.16 2
 
3.1%
1.33 2
 
3.1%
1.12 2
 
3.1%
1.34 2
 
3.1%
0.95 2
 
3.1%
Other values (41) 43
67.2%
ValueCountFrequency (%)
0.44 1
1.6%
0.55 1
1.6%
0.56 1
1.6%
0.59 2
3.1%
0.7 1
1.6%
0.72 2
3.1%
0.73 1
1.6%
0.75 1
1.6%
0.76 1
1.6%
0.79 1
1.6%
ValueCountFrequency (%)
2.16 1
1.6%
1.76 1
1.6%
1.75 1
1.6%
1.68 1
1.6%
1.64 1
1.6%
1.61 1
1.6%
1.57 1
1.6%
1.56 1
1.6%
1.55 1
1.6%
1.51 1
1.6%

2016_3분기
Real number (ℝ)

HIGH CORRELATION 

Distinct48
Distinct (%)75.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.90375
Minimum0.18
Maximum1.88
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size708.0 B
2023-12-12T16:03:00.026013image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0.18
5-th percentile0.3135
Q10.6275
median0.925
Q31.18
95-th percentile1.5155
Maximum1.88
Range1.7
Interquartile range (IQR)0.5525

Descriptive statistics

Standard deviation0.37276956
Coefficient of variation (CV)0.41246977
Kurtosis-0.3152165
Mean0.90375
Median Absolute Deviation (MAD)0.265
Skewness0.13380542
Sum57.84
Variance0.13895714
MonotonicityNot monotonic
2023-12-12T16:03:00.177152image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=48)
ValueCountFrequency (%)
1.31 3
 
4.7%
0.44 3
 
4.7%
0.78 3
 
4.7%
1.01 3
 
4.7%
1.18 2
 
3.1%
1.16 2
 
3.1%
0.39 2
 
3.1%
0.72 2
 
3.1%
0.94 2
 
3.1%
0.99 2
 
3.1%
Other values (38) 40
62.5%
ValueCountFrequency (%)
0.18 1
 
1.6%
0.2 1
 
1.6%
0.24 1
 
1.6%
0.3 1
 
1.6%
0.39 2
3.1%
0.44 3
4.7%
0.45 1
 
1.6%
0.48 1
 
1.6%
0.51 1
 
1.6%
0.53 1
 
1.6%
ValueCountFrequency (%)
1.88 1
 
1.6%
1.61 1
 
1.6%
1.53 1
 
1.6%
1.52 1
 
1.6%
1.49 1
 
1.6%
1.39 1
 
1.6%
1.37 1
 
1.6%
1.33 1
 
1.6%
1.31 3
4.7%
1.23 1
 
1.6%

2016_4분기
Real number (ℝ)

HIGH CORRELATION 

Distinct53
Distinct (%)82.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1.1160938
Minimum0.41
Maximum2.18
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size708.0 B
2023-12-12T16:03:00.339809image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0.41
5-th percentile0.543
Q10.8775
median1.1
Q31.3275
95-th percentile1.667
Maximum2.18
Range1.77
Interquartile range (IQR)0.45

Descriptive statistics

Standard deviation0.35757391
Coefficient of variation (CV)0.32037982
Kurtosis0.19296006
Mean1.1160938
Median Absolute Deviation (MAD)0.225
Skewness0.2487828
Sum71.43
Variance0.1278591
MonotonicityNot monotonic
2023-12-12T16:03:00.835055image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1.29 3
 
4.7%
1.19 2
 
3.1%
1.76 2
 
3.1%
1.28 2
 
3.1%
1.1 2
 
3.1%
1.04 2
 
3.1%
1.56 2
 
3.1%
1.39 2
 
3.1%
1.21 2
 
3.1%
1.37 2
 
3.1%
Other values (43) 43
67.2%
ValueCountFrequency (%)
0.41 1
1.6%
0.45 1
1.6%
0.47 1
1.6%
0.54 1
1.6%
0.56 1
1.6%
0.63 1
1.6%
0.65 1
1.6%
0.67 1
1.6%
0.68 1
1.6%
0.72 1
1.6%
ValueCountFrequency (%)
2.18 1
1.6%
1.76 2
3.1%
1.67 1
1.6%
1.65 1
1.6%
1.61 1
1.6%
1.59 1
1.6%
1.56 2
3.1%
1.42 1
1.6%
1.41 1
1.6%
1.39 2
3.1%

Interactions

2023-12-12T16:02:52.063649image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T16:02:24.822989image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T16:02:27.009603image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T16:02:28.903227image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T16:02:30.496428image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T16:02:32.440307image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T16:02:34.219441image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T16:02:35.959425image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T16:02:38.027659image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T16:02:39.906408image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T16:02:41.530894image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T16:02:43.053565image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T16:02:45.115504image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T16:02:46.969736image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T16:02:48.420473image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T16:02:50.423124image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T16:02:52.163162image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T16:02:25.203519image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T16:02:27.141939image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T16:02:29.011759image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T16:02:30.589146image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T16:02:32.556551image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T16:02:34.331839image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T16:02:36.050619image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T16:02:38.135812image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T16:02:40.028262image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T16:02:41.634170image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T16:02:43.137196image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T16:02:45.249135image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T16:02:47.078592image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T16:02:48.522505image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T16:02:50.526672image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T16:02:52.256097image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T16:02:25.319528image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T16:02:27.254281image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T16:02:29.120455image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T16:02:30.691727image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T16:02:32.661139image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T16:02:34.434931image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T16:02:36.165359image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
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2023-12-12T16:02:51.873717image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T16:02:53.598965image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T16:02:26.887592image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T16:02:28.802373image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T16:02:30.403144image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T16:02:32.324972image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T16:02:34.118579image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T16:02:35.864163image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T16:02:37.913948image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T16:02:39.788182image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T16:02:41.418375image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T16:02:42.970766image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T16:02:45.016232image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T16:02:46.864001image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T16:02:48.299075image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T16:02:50.326509image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T16:02:51.968207image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-12T16:03:00.997012image/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_1분기1.0001.0000.9190.8870.9650.9200.9160.8940.9430.8130.8360.9230.8240.8100.8390.9300.822
2013_2분기1.0000.9191.0000.9580.8950.9500.8880.7690.8360.9630.9430.7880.9310.9530.9140.8250.899
2013_3분기1.0000.8870.9581.0000.8790.9500.8050.8130.7190.8720.8730.8010.8730.8780.8730.8300.845
2013_4분기1.0000.9650.8950.8791.0000.9480.9490.9100.9400.8250.8270.9210.8200.7860.7910.9280.792
2014_1분기1.0000.9200.9500.9500.9481.0000.9000.7710.8730.8980.9180.8180.9010.8790.8890.8220.878
2014_2분기1.0000.9160.8880.8050.9490.9001.0000.8980.9490.8480.8540.8540.7960.8020.7700.8390.759
2014_3분기1.0000.8940.7690.8130.9100.7710.8981.0000.9440.8260.8010.9300.7970.8100.7920.8740.773
2014_4분기1.0000.9430.8360.7190.9400.8730.9490.9441.0000.8980.9410.9360.8890.8810.8870.9170.857
2015_1분기1.0000.8130.9630.8720.8250.8980.8480.8260.8981.0000.9770.8360.9670.9730.9560.8400.960
2015_2분기1.0000.8360.9430.8730.8270.9180.8540.8010.9410.9771.0000.8760.9900.9780.9750.8860.964
2015_3분기1.0000.9230.7880.8010.9210.8180.8540.9300.9360.8360.8761.0000.8940.8740.8800.9500.866
2015_4분기1.0000.8240.9310.8730.8200.9010.7960.7970.8890.9670.9900.8941.0000.9940.9920.8880.981
2016_1분기1.0000.8100.9530.8780.7860.8790.8020.8100.8810.9730.9780.8740.9941.0000.9950.8560.975
2016_2분기1.0000.8390.9140.8730.7910.8890.7700.7920.8870.9560.9750.8800.9920.9951.0000.8680.983
2016_3분기1.0000.9300.8250.8300.9280.8220.8390.8740.9170.8400.8860.9500.8880.8560.8681.0000.870
2016_4분기1.0000.8220.8990.8450.7920.8780.7590.7730.8570.9600.9640.8660.9810.9750.9830.8701.000
2023-12-12T16:03:01.191192image/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_1분기1.0000.9740.9420.9210.9230.9000.8980.8830.8630.8850.8720.8670.8660.8620.8590.829
2013_2분기0.9741.0000.9610.9470.9420.9220.9150.8990.8790.8950.8750.8750.8700.8590.8490.837
2013_3분기0.9420.9611.0000.9200.9140.8890.9160.8580.8370.8570.8760.8340.8270.8220.8640.807
2013_4분기0.9210.9470.9201.0000.9890.9710.9150.9400.9240.9310.8900.9070.9020.8930.8770.870
2014_1분기0.9230.9420.9140.9891.0000.9770.9130.9430.9240.9310.8890.9070.9040.8990.8810.869
2014_2분기0.9000.9220.8890.9710.9771.0000.9380.9760.9630.9610.9000.9250.9200.9170.8840.880
2014_3분기0.8980.9150.9160.9150.9130.9381.0000.9190.9010.9130.9330.8900.8770.8770.8870.844
2014_4분기0.8830.8990.8580.9400.9430.9760.9191.0000.9800.9750.8940.9340.9260.9200.8840.886
2015_1분기0.8630.8790.8370.9240.9240.9630.9010.9801.0000.9850.9110.9510.9410.9380.8920.905
2015_2분기0.8850.8950.8570.9310.9310.9610.9130.9750.9851.0000.9400.9730.9610.9610.9200.929
2015_3분기0.8720.8750.8760.8900.8890.9000.9330.8940.9110.9401.0000.9460.9390.9460.9600.938
2015_4분기0.8670.8750.8340.9070.9070.9250.8900.9340.9510.9730.9461.0000.9890.9850.9430.961
2016_1분기0.8660.8700.8270.9020.9040.9200.8770.9260.9410.9610.9390.9891.0000.9960.9460.970
2016_2분기0.8620.8590.8220.8930.8990.9170.8770.9200.9380.9610.9460.9850.9961.0000.9500.973
2016_3분기0.8590.8490.8640.8770.8810.8840.8870.8840.8920.9200.9600.9430.9460.9501.0000.961
2016_4분기0.8290.8370.8070.8700.8690.8800.8440.8860.9050.9290.9380.9610.9700.9730.9611.000

Missing values

2023-12-12T16:02:53.754741image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-12T16:02:53.995029image/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
0서울1.451.431.251.391.391.361.171.311.291.321.131.31.321.311.111.29
1서울 도심1.721.71.541.641.661.561.481.481.491.531.431.551.581.561.371.56
2서울 도심 광화문1.731.751.551.611.611.651.531.671.691.661.41.591.71.571.311.56
3서울 도심 동대문1.451.451.231.411.391.391.271.31.371.331.111.371.21.191.161.19
4서울 도심 명동1.311.291.181.361.381.371.291.261.311.321.271.181.171.210.971.19
5서울 도심 서울역2.082.081.951.982.021.451.441.31.231.411.571.661.751.751.611.76
6서울 도심 종로1.761.741.581.751.751.781.71.731.761.781.561.761.761.761.491.76
7서울 도심 충무로1.471.271.111.141.211.211.081.061.081.111.181.11.151.221.311.31
8서울 강남1.291.251.11.191.181.190.991.151.141.140.921.081.111.120.941.1
9서울 강남 강남대로1.081.020.990.990.970.980.931.011.00.980.810.820.780.80.780.89
지역2013_1분기2013_2분기2013_3분기2013_4분기2014_1분기2014_2분기2014_3분기2014_4분기2015_1분기2015_2분기2015_3분기2015_4분기2016_1분기2016_2분기2016_3분기2016_4분기
54경기 일산동구1.131.191.01.21.211.240.911.171.161.110.931.091.11.120.911.07
55경기 평촌범계1.531.51.141.471.441.461.071.491.431.551.111.471.471.51.011.39
56강원1.331.371.031.221.261.240.981.11.081.110.811.11.071.040.721.04
57충북0.790.760.440.770.810.770.480.620.620.620.390.540.570.560.180.45
58충남1.041.030.640.780.80.810.590.780.820.790.520.760.770.760.510.86
59전북1.031.010.691.00.990.960.550.860.880.860.530.750.760.750.440.78
60전남1.191.220.961.221.221.230.931.141.11.10.851.051.061.090.781.06
61경북1.41.451.071.351.361.230.941.151.121.090.781.041.010.990.680.95
62경남0.960.970.690.950.960.950.620.90.880.880.610.870.890.880.590.79
63제주0.920.920.450.820.820.830.610.790.780.770.520.720.710.70.480.68