Overview

Dataset statistics

Number of variables9
Number of observations601
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory47.1 KiB
Average record size in memory80.2 B

Variable types

DateTime1
Numeric8

Dataset

Description주간 신재생에너지 인증서(REC) 거래현황 정보를 제공합니다. 항목 : 거래일, 체결REC수량, 평균가, 체결총액, 시작가, 종가, 기준가, 최고가, 최저가 단위 : 원 ※ REC 현물시장 체결 기준 데이터입니다.
URLhttps://www.data.go.kr/data/15069394/fileData.do

Alerts

체결 수량 is highly overall correlated with 체결총액High correlation
평균가 is highly overall correlated with 시작가 and 4 other fieldsHigh correlation
체결총액 is highly overall correlated with 체결 수량High correlation
시작가 is highly overall correlated with 평균가 and 4 other fieldsHigh correlation
종가 is highly overall correlated with 평균가 and 4 other fieldsHigh correlation
기준가 is highly overall correlated with 평균가 and 4 other fieldsHigh correlation
최고가 is highly overall correlated with 평균가 and 4 other fieldsHigh correlation
최저가 is highly overall correlated with 평균가 and 4 other fieldsHigh correlation
거래일 has unique valuesUnique
체결 수량 has unique valuesUnique
체결총액 has unique valuesUnique

Reproduction

Analysis started2023-12-12 11:36:26.737137
Analysis finished2023-12-12 11:36:38.462160
Duration11.73 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

거래일
Date

UNIQUE 

Distinct601
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size4.8 KiB
Minimum2017-03-28 00:00:00
Maximum2023-03-30 00:00:00
2023-12-12T20:36:38.574455image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T20:36:38.813207image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

체결 수량
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct601
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean86490.915
Minimum2345
Maximum349490
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size5.4 KiB
2023-12-12T20:36:39.052139image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum2345
5-th percentile12917
Q143936
median75103
Q3121690
95-th percentile183449
Maximum349490
Range347145
Interquartile range (IQR)77754

Descriptive statistics

Standard deviation56924.147
Coefficient of variation (CV)0.65815175
Kurtosis2.0236028
Mean86490.915
Median Absolute Deviation (MAD)37801
Skewness1.1253368
Sum51981040
Variance3.2403585 × 109
MonotonicityNot monotonic
2023-12-12T20:36:39.282530image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
2568 1
 
0.2%
37539 1
 
0.2%
38658 1
 
0.2%
59767 1
 
0.2%
55059 1
 
0.2%
73794 1
 
0.2%
45078 1
 
0.2%
51455 1
 
0.2%
65603 1
 
0.2%
59643 1
 
0.2%
Other values (591) 591
98.3%
ValueCountFrequency (%)
2345 1
0.2%
2568 1
0.2%
3350 1
0.2%
3430 1
0.2%
4504 1
0.2%
5327 1
0.2%
5821 1
0.2%
6508 1
0.2%
6687 1
0.2%
7382 1
0.2%
ValueCountFrequency (%)
349490 1
0.2%
330080 1
0.2%
327969 1
0.2%
317576 1
0.2%
282656 1
0.2%
281848 1
0.2%
279227 1
0.2%
264511 1
0.2%
261042 1
0.2%
260105 1
0.2%

평균가
Real number (ℝ)

HIGH CORRELATION 

Distinct593
Distinct (%)98.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean66941.275
Minimum28293
Maximum132470
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size5.4 KiB
2023-12-12T20:36:39.585662image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum28293
5-th percentile31400
Q142827
median59020
Q382489
95-th percentile127498
Maximum132470
Range104177
Interquartile range (IQR)39662

Descriptive statistics

Standard deviation30572.172
Coefficient of variation (CV)0.45670137
Kurtosis-0.63837672
Mean66941.275
Median Absolute Deviation (MAD)18499
Skewness0.77701349
Sum40231706
Variance9.3465769 × 108
MonotonicityNot monotonic
2023-12-12T20:36:39.843032image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
44680 2
 
0.3%
64058 2
 
0.3%
38683 2
 
0.3%
30022 2
 
0.3%
44489 2
 
0.3%
44477 2
 
0.3%
61926 2
 
0.3%
53909 2
 
0.3%
33675 1
 
0.2%
31438 1
 
0.2%
Other values (583) 583
97.0%
ValueCountFrequency (%)
28293 1
0.2%
29264 1
0.2%
29596 1
0.2%
29659 1
0.2%
29741 1
0.2%
29908 1
0.2%
29917 1
0.2%
29932 1
0.2%
29956 1
0.2%
30003 1
0.2%
ValueCountFrequency (%)
132470 1
0.2%
132367 1
0.2%
132354 1
0.2%
132328 1
0.2%
132097 1
0.2%
130447 1
0.2%
129945 1
0.2%
129884 1
0.2%
129865 1
0.2%
129340 1
0.2%

체결총액
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct601
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean5.1249226 × 109
Minimum2.95573 × 108
Maximum2.2324223 × 1010
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size5.4 KiB
2023-12-12T20:36:40.125713image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum2.95573 × 108
5-th percentile1.1801787 × 109
Q12.4728635 × 109
median4.4691796 × 109
Q36.6937917 × 109
95-th percentile1.1377684 × 1010
Maximum2.2324223 × 1010
Range2.202865 × 1010
Interquartile range (IQR)4.2209282 × 109

Descriptive statistics

Standard deviation3.5051139 × 109
Coefficient of variation (CV)0.68393499
Kurtosis3.0399448
Mean5.1249226 × 109
Median Absolute Deviation (MAD)2.0732393 × 109
Skewness1.4724545
Sum3.0800785 × 1012
Variance1.2285823 × 1019
MonotonicityNot monotonic
2023-12-12T20:36:40.380130image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
305624400 1
 
0.2%
1180178700 1
 
0.2%
1218732900 1
 
0.2%
1969395400 1
 
0.2%
1854140900 1
 
0.2%
2631297500 1
 
0.2%
1605795200 1
 
0.2%
1820420700 1
 
0.2%
2270005000 1
 
0.2%
2074914300 1
 
0.2%
Other values (591) 591
98.3%
ValueCountFrequency (%)
295573000 1
0.2%
297217000 1
0.2%
305624400 1
0.2%
347818600 1
0.2%
415987000 1
0.2%
488293600 1
0.2%
553785900 1
0.2%
596914000 1
0.2%
626967700 1
0.2%
664322200 1
0.2%
ValueCountFrequency (%)
22324223000 1
0.2%
20221866900 1
0.2%
19334334200 1
0.2%
19139066400 1
0.2%
18310607800 1
0.2%
18243435000 1
0.2%
17751118400 1
0.2%
17538955200 1
0.2%
17079795900 1
0.2%
16643900100 1
0.2%

시작가
Real number (ℝ)

HIGH CORRELATION 

Distinct274
Distinct (%)45.6%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean65186.855
Minimum27100
Maximum130000
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size5.4 KiB
2023-12-12T20:36:40.674848image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum27100
5-th percentile30000
Q142000
median57600
Q382000
95-th percentile125000
Maximum130000
Range102900
Interquartile range (IQR)40000

Descriptive statistics

Standard deviation29979.824
Coefficient of variation (CV)0.45990597
Kurtosis-0.63547585
Mean65186.855
Median Absolute Deviation (MAD)17600
Skewness0.7830722
Sum39177300
Variance8.9878984 × 108
MonotonicityNot monotonic
2023-12-12T20:36:40.973211image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
100000 12
 
2.0%
30000 12
 
2.0%
75000 11
 
1.8%
44400 10
 
1.7%
105000 10
 
1.7%
120000 10
 
1.7%
60000 9
 
1.5%
63000 9
 
1.5%
38000 7
 
1.2%
50000 7
 
1.2%
Other values (264) 504
83.9%
ValueCountFrequency (%)
27100 1
 
0.2%
27900 1
 
0.2%
28000 3
0.5%
28100 2
0.3%
28500 1
 
0.2%
28800 1
 
0.2%
29000 2
0.3%
29300 2
0.3%
29400 1
 
0.2%
29500 3
0.5%
ValueCountFrequency (%)
130000 3
0.5%
129100 1
 
0.2%
129000 2
 
0.3%
127900 1
 
0.2%
127800 1
 
0.2%
127000 3
0.5%
126500 1
 
0.2%
126100 1
 
0.2%
126000 7
1.2%
125700 1
 
0.2%

종가
Real number (ℝ)

HIGH CORRELATION 

Distinct335
Distinct (%)55.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean66741.597
Minimum29200
Maximum133500
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size5.4 KiB
2023-12-12T20:36:41.236800image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum29200
5-th percentile31300
Q142800
median59000
Q382900
95-th percentile126500
Maximum133500
Range104300
Interquartile range (IQR)40100

Descriptive statistics

Standard deviation30298.575
Coefficient of variation (CV)0.45396839
Kurtosis-0.64935845
Mean66741.597
Median Absolute Deviation (MAD)18400
Skewness0.77013248
Sum40111700
Variance9.1800367 × 108
MonotonicityNot monotonic
2023-12-12T20:36:41.504887image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
44400 9
 
1.5%
44200 8
 
1.3%
44500 7
 
1.2%
39900 7
 
1.2%
128000 7
 
1.2%
55000 6
 
1.0%
30000 6
 
1.0%
63700 5
 
0.8%
39700 5
 
0.8%
47000 5
 
0.8%
Other values (325) 536
89.2%
ValueCountFrequency (%)
29200 1
 
0.2%
29300 1
 
0.2%
29700 1
 
0.2%
29800 1
 
0.2%
29900 2
 
0.3%
30000 6
1.0%
30200 3
0.5%
30300 3
0.5%
30400 2
 
0.3%
30500 2
 
0.3%
ValueCountFrequency (%)
133500 1
 
0.2%
132300 1
 
0.2%
132000 1
 
0.2%
130000 4
0.7%
129500 1
 
0.2%
129200 1
 
0.2%
129000 2
 
0.3%
128000 7
1.2%
127700 1
 
0.2%
127600 1
 
0.2%

기준가
Real number (ℝ)

HIGH CORRELATION 

Distinct335
Distinct (%)55.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean66851.581
Minimum29200
Maximum137600
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size5.4 KiB
2023-12-12T20:36:41.756986image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum29200
5-th percentile31300
Q142800
median59000
Q383500
95-th percentile126600
Maximum137600
Range108400
Interquartile range (IQR)40700

Descriptive statistics

Standard deviation30435.538
Coefficient of variation (CV)0.45527029
Kurtosis-0.6534825
Mean66851.581
Median Absolute Deviation (MAD)18400
Skewness0.77000077
Sum40177800
Variance9.26322 × 108
MonotonicityNot monotonic
2023-12-12T20:36:42.068665image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
44400 9
 
1.5%
44200 8
 
1.3%
39900 7
 
1.2%
128000 7
 
1.2%
44500 7
 
1.2%
55000 6
 
1.0%
30000 6
 
1.0%
39700 5
 
0.8%
39200 5
 
0.8%
31700 5
 
0.8%
Other values (325) 536
89.2%
ValueCountFrequency (%)
29200 1
 
0.2%
29300 1
 
0.2%
29700 1
 
0.2%
29800 1
 
0.2%
29900 2
 
0.3%
30000 6
1.0%
30200 3
0.5%
30300 3
0.5%
30400 2
 
0.3%
30500 2
 
0.3%
ValueCountFrequency (%)
137600 1
 
0.2%
133500 1
 
0.2%
132300 1
 
0.2%
132000 1
 
0.2%
130000 4
0.7%
129500 1
 
0.2%
129200 1
 
0.2%
129000 2
 
0.3%
128000 7
1.2%
127700 1
 
0.2%

최고가
Real number (ℝ)

HIGH CORRELATION 

Distinct281
Distinct (%)46.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean67659.068
Minimum30000
Maximum134000
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size5.4 KiB
2023-12-12T20:36:42.314678image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum30000
5-th percentile31900
Q144000
median59300
Q383000
95-th percentile128000
Maximum134000
Range104000
Interquartile range (IQR)39000

Descriptive statistics

Standard deviation30768.77
Coefficient of variation (CV)0.45476195
Kurtosis-0.64301829
Mean67659.068
Median Absolute Deviation (MAD)18300
Skewness0.77963049
Sum40663100
Variance9.4671719 × 108
MonotonicityNot monotonic
2023-12-12T20:36:42.573005image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
128000 17
 
2.8%
110000 12
 
2.0%
40000 12
 
2.0%
64000 11
 
1.8%
70000 10
 
1.7%
30500 10
 
1.7%
45000 10
 
1.7%
44500 9
 
1.5%
32000 9
 
1.5%
64300 8
 
1.3%
Other values (271) 493
82.0%
ValueCountFrequency (%)
30000 4
 
0.7%
30200 2
 
0.3%
30300 1
 
0.2%
30400 2
 
0.3%
30500 10
1.7%
31000 4
 
0.7%
31200 1
 
0.2%
31500 1
 
0.2%
31600 3
 
0.5%
31700 1
 
0.2%
ValueCountFrequency (%)
134000 1
 
0.2%
133500 2
 
0.3%
133000 2
 
0.3%
132000 1
 
0.2%
131000 2
 
0.3%
130500 2
 
0.3%
130000 8
1.3%
129500 1
 
0.2%
129000 4
0.7%
128600 2
 
0.3%

최저가
Real number (ℝ)

HIGH CORRELATION 

Distinct317
Distinct (%)52.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean64424.958
Minimum27000
Maximum130000
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size5.4 KiB
2023-12-12T20:36:42.843185image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum27000
5-th percentile30000
Q141000
median57200
Q380000
95-th percentile124800
Maximum130000
Range103000
Interquartile range (IQR)39000

Descriptive statistics

Standard deviation29641.306
Coefficient of variation (CV)0.46009041
Kurtosis-0.61020878
Mean64424.958
Median Absolute Deviation (MAD)17800
Skewness0.79198084
Sum38719400
Variance8.7860701 × 108
MonotonicityNot monotonic
2023-12-12T20:36:43.075744image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
120000 10
 
1.7%
100000 10
 
1.7%
60000 9
 
1.5%
75000 9
 
1.5%
44200 9
 
1.5%
44400 8
 
1.3%
30000 8
 
1.3%
125000 8
 
1.3%
96000 6
 
1.0%
39000 6
 
1.0%
Other values (307) 518
86.2%
ValueCountFrequency (%)
27000 1
 
0.2%
27100 1
 
0.2%
27500 1
 
0.2%
27900 1
 
0.2%
28000 1
 
0.2%
28100 2
0.3%
28500 1
 
0.2%
28800 1
 
0.2%
29000 4
0.7%
29100 1
 
0.2%
ValueCountFrequency (%)
130000 1
 
0.2%
129500 1
 
0.2%
128100 1
 
0.2%
128000 2
0.3%
126500 1
 
0.2%
126000 4
0.7%
125900 1
 
0.2%
125500 2
0.3%
125400 1
 
0.2%
125300 1
 
0.2%

Interactions

2023-12-12T20:36:36.418878image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T20:36:27.265984image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T20:36:28.570574image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T20:36:29.807718image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T20:36:31.030677image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T20:36:32.396194image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T20:36:33.771721image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T20:36:35.094670image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T20:36:36.600442image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T20:36:27.436126image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T20:36:28.753603image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T20:36:29.945298image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T20:36:31.211444image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T20:36:32.575742image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T20:36:33.941994image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T20:36:35.266881image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T20:36:36.744426image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T20:36:27.617614image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T20:36:28.921300image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T20:36:30.089209image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T20:36:31.379315image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T20:36:32.742141image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T20:36:34.101603image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T20:36:35.426094image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T20:36:36.916643image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T20:36:27.783080image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T20:36:29.089930image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T20:36:30.227403image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T20:36:31.555733image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T20:36:32.932597image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T20:36:34.287237image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T20:36:35.591521image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T20:36:37.095783image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T20:36:27.964010image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T20:36:29.228142image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T20:36:30.377943image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T20:36:31.734535image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T20:36:33.093813image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T20:36:34.426657image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T20:36:35.768760image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T20:36:37.232600image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T20:36:28.117152image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T20:36:29.374618image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T20:36:30.525977image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T20:36:31.898807image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T20:36:33.247049image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T20:36:34.599682image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T20:36:35.934706image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T20:36:37.879316image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T20:36:28.262395image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T20:36:29.526452image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T20:36:30.680004image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T20:36:32.069792image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T20:36:33.425095image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T20:36:34.762166image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T20:36:36.094166image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T20:36:37.996419image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T20:36:28.405483image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T20:36:29.668695image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T20:36:30.855770image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T20:36:32.228638image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T20:36:33.589710image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T20:36:34.929826image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T20:36:36.250577image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-12T20:36:43.267964image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
체결 수량평균가체결총액시작가종가기준가최고가최저가
체결 수량1.0000.5410.8610.5480.5720.5240.5340.554
평균가0.5411.0000.5630.9870.9950.9850.9970.990
체결총액0.8610.5631.0000.5380.5610.5020.5200.543
시작가0.5480.9870.5381.0000.9800.9780.9840.996
종가0.5720.9950.5610.9801.0000.9890.9960.987
기준가0.5240.9850.5020.9780.9891.0000.9920.981
최고가0.5340.9970.5200.9840.9960.9921.0000.985
최저가0.5540.9900.5430.9960.9870.9810.9851.000
2023-12-12T20:36:43.510152image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
체결 수량평균가체결총액시작가종가기준가최고가최저가
체결 수량1.000-0.3470.819-0.375-0.343-0.370-0.356-0.360
평균가-0.3471.0000.1920.9940.9990.9970.9990.995
체결총액0.8190.1921.0000.1610.1960.1640.1810.178
시작가-0.3750.9940.1611.0000.9930.9950.9930.998
종가-0.3430.9990.1960.9931.0000.9950.9980.994
기준가-0.3700.9970.1640.9950.9951.0000.9960.995
최고가-0.3560.9990.1810.9930.9980.9961.0000.993
최저가-0.3600.9950.1780.9980.9940.9950.9931.000

Missing values

2023-12-12T20:36:38.173172image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-12T20:36:38.386185image/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

거래일체결 수량평균가체결총액시작가종가기준가최고가최저가
02017-03-282568119012305624400119900120000137600120000117500
12017-03-30115131195461376333900120000120100120000121300115000
22017-04-04134021225341642201400115500123800120100125300115500
32017-04-06124531242461547236500120000124000123800125000120000
42017-04-11122821248871533865900123500124900124000126200122500
52017-04-13140211234811731330000123000120800124900125100119100
62017-04-18185081241632298015500120000125000120800125100120000
72017-04-20222591276502841371400122100127600125000130000122100
82017-04-25164541280942107662400117000130000127600130000117000
92017-04-2781491260071026833900124000121000130000130000120000
거래일체결 수량평균가체결총액시작가종가기준가최고가최저가
5912023-02-2819854963625126327696006300063700632006380061800
5922023-03-021508556428996983777006350064500637006460063500
5932023-03-0724573464971159655438006400065000645006530062700
5942023-03-0917075465724112225916006170065800650006600061700
5952023-03-1418344966905122736500006550067100658006720065000
5962023-03-161187166881281691002006680069100671006930066800
5972023-03-211314336950891356345006220069500691007000062200
5982023-03-231392707062098353128006800071000695007120066100
5992023-03-2816595571712119010373007100071600710007200068100
6002023-03-3023834371661170797959006700071500716007200067000