Overview

Dataset statistics

Number of variables5
Number of observations180
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory7.9 KiB
Average record size in memory44.7 B

Variable types

DateTime1
Numeric4

Dataset

Description산업통상자원부에서 발간하는 보도자료를 기반으로 국내 자동차 산업의 생산량, 내수판매(국산차 기준), 수출량, 수출금액(천달러)에 대한 정보를 제공합니다.
Author산업통상자원부
URLhttps://www.data.go.kr/data/15051118/fileData.do

Alerts

생산량 is highly overall correlated with 수출량 and 1 other fieldsHigh correlation
수출량 is highly overall correlated with 생산량 and 1 other fieldsHigh correlation
수출금액(천달러) is highly overall correlated with 생산량 and 1 other fieldsHigh correlation
기간 has unique valuesUnique
생산량 has unique valuesUnique
내수판매(국산차) has unique valuesUnique
수출량 has unique valuesUnique
수출금액(천달러) has unique valuesUnique

Reproduction

Analysis started2024-04-13 12:01:44.662756
Analysis finished2024-04-13 12:01:50.567683
Duration5.9 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

기간
Date

UNIQUE 

Distinct180
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size1.5 KiB
Minimum2009-01-01 00:00:00
Maximum2023-12-01 00:00:00
2024-04-13T21:01:50.778417image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-13T21:01:51.193433image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

생산량
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct180
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean343880.58
Minimum189230
Maximum444049
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.7 KiB
2024-04-13T21:01:51.607962image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum189230
5-th percentile237453.45
Q1305227.75
median351707
Q3386423.5
95-th percentile425315.8
Maximum444049
Range254819
Interquartile range (IQR)81195.75

Descriptive statistics

Standard deviation56185.903
Coefficient of variation (CV)0.16338783
Kurtosis-0.42709378
Mean343880.58
Median Absolute Deviation (MAD)39914.5
Skewness-0.45105371
Sum61898505
Variance3.1568556 × 109
MonotonicityNot monotonic
2024-04-13T21:01:52.051480image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
189333 1
 
0.6%
306376 1
 
0.6%
291971 1
 
0.6%
381655 1
 
0.6%
390562 1
 
0.6%
356932 1
 
0.6%
354305 1
 
0.6%
257276 1
 
0.6%
345821 1
 
0.6%
371931 1
 
0.6%
Other values (170) 170
94.4%
ValueCountFrequency (%)
189230 1
0.6%
189333 1
0.6%
217097 1
0.6%
229423 1
0.6%
231116 1
0.6%
232552 1
0.6%
233363 1
0.6%
234963 1
0.6%
237006 1
0.6%
237477 1
0.6%
ValueCountFrequency (%)
444049 1
0.6%
437607 1
0.6%
434850 1
0.6%
434709 1
0.6%
433799 1
0.6%
428350 1
0.6%
426571 1
0.6%
425510 1
0.6%
425369 1
0.6%
425313 1
0.6%

내수판매(국산차)
Real number (ℝ)

UNIQUE 

Distinct180
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean124099.99
Minimum73874
Maximum176821
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.7 KiB
2024-04-13T21:01:52.609254image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum73874
5-th percentile96856.75
Q1113516
median123453.5
Q3134548.5
95-th percentile146928.2
Maximum176821
Range102947
Interquartile range (IQR)21032.5

Descriptive statistics

Standard deviation16350.905
Coefficient of variation (CV)0.13175589
Kurtosis0.8832128
Mean124099.99
Median Absolute Deviation (MAD)10839
Skewness0.069263383
Sum22337999
Variance2.673521 × 108
MonotonicityNot monotonic
2024-04-13T21:01:53.059775image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
73874 1
 
0.6%
134355 1
 
0.6%
110537 1
 
0.6%
140068 1
 
0.6%
140381 1
 
0.6%
139414 1
 
0.6%
117959 1
 
0.6%
104732 1
 
0.6%
138849 1
 
0.6%
136809 1
 
0.6%
Other values (170) 170
94.4%
ValueCountFrequency (%)
73874 1
0.6%
82128 1
0.6%
86077 1
0.6%
87903 1
0.6%
91467 1
0.6%
92343 1
0.6%
94387 1
0.6%
94523 1
0.6%
95484 1
0.6%
96929 1
0.6%
ValueCountFrequency (%)
176821 1
0.6%
176091 1
0.6%
165918 1
0.6%
162240 1
0.6%
157129 1
0.6%
154887 1
0.6%
151478 1
0.6%
149888 1
0.6%
147084 1
0.6%
146920 1
0.6%

수출량
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct180
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean218703.97
Minimum95791
Maximum307077
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.7 KiB
2024-04-13T21:01:53.482864image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum95791
5-th percentile148178.15
Q1182805.25
median218185
Q3254186
95-th percentile298546.55
Maximum307077
Range211286
Interquartile range (IQR)71380.75

Descriptive statistics

Standard deviation45502.015
Coefficient of variation (CV)0.20805299
Kurtosis-0.58781659
Mean218703.97
Median Absolute Deviation (MAD)36115
Skewness-0.11016511
Sum39366714
Variance2.0704334 × 109
MonotonicityNot monotonic
2024-04-13T21:01:53.905648image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
122946 1
 
0.6%
193439 1
 
0.6%
180051 1
 
0.6%
232366 1
 
0.6%
237941 1
 
0.6%
220333 1
 
0.6%
209906 1
 
0.6%
164048 1
 
0.6%
208121 1
 
0.6%
222395 1
 
0.6%
Other values (170) 170
94.4%
ValueCountFrequency (%)
95791 1
0.6%
119942 1
0.6%
122946 1
0.6%
123240 1
0.6%
126677 1
0.6%
130213 1
0.6%
130477 1
0.6%
140506 1
0.6%
141189 1
0.6%
148546 1
0.6%
ValueCountFrequency (%)
307077 1
0.6%
304774 1
0.6%
304326 1
0.6%
301433 1
0.6%
301417 1
0.6%
300502 1
0.6%
300005 1
0.6%
299947 1
0.6%
299355 1
0.6%
298504 1
0.6%

수출금액(천달러)
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct180
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean3714497.8
Minimum1376094
Maximum6529081
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.7 KiB
2024-04-13T21:01:54.320243image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1376094
5-th percentile2229904.4
Q13128398
median3777735
Q34137993.5
95-th percentile5429440.5
Maximum6529081
Range5152987
Interquartile range (IQR)1009595.5

Descriptive statistics

Standard deviation946217.01
Coefficient of variation (CV)0.25473619
Kurtosis1.0160482
Mean3714497.8
Median Absolute Deviation (MAD)487413.5
Skewness0.43358305
Sum6.686096 × 108
Variance8.9532663 × 1011
MonotonicityNot monotonic
2024-04-13T21:01:54.766129image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1376094 1
 
0.6%
3144271 1
 
0.6%
2963642 1
 
0.6%
3916857 1
 
0.6%
3964687 1
 
0.6%
3772267 1
 
0.6%
3664503 1
 
0.6%
2880723 1
 
0.6%
3705511 1
 
0.6%
3752114 1
 
0.6%
Other values (170) 170
94.4%
ValueCountFrequency (%)
1376094 1
0.6%
1699904 1
0.6%
1704574 1
0.6%
1774136 1
0.6%
1803194 1
0.6%
1808416 1
0.6%
1942569 1
0.6%
2050591 1
0.6%
2133771 1
0.6%
2234964 1
0.6%
ValueCountFrequency (%)
6529081 1
0.6%
6495857 1
0.6%
6384449 1
0.6%
6227738 1
0.6%
6194208 1
0.6%
6155913 1
0.6%
5902529 1
0.6%
5880107 1
0.6%
5594086 1
0.6%
5420775 1
0.6%

Interactions

2024-04-13T21:01:49.059760image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-13T21:01:46.132305image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-13T21:01:47.109064image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-13T21:01:48.086450image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-13T21:01:49.302465image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-13T21:01:46.385118image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-13T21:01:47.363334image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-13T21:01:48.327050image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-13T21:01:49.545110image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-13T21:01:46.631302image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-13T21:01:47.605479image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-13T21:01:48.598938image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-13T21:01:49.779035image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-13T21:01:46.868116image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-13T21:01:47.846955image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-13T21:01:48.823150image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-04-13T21:01:55.031366image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
생산량내수판매(국산차)수출량수출금액(천달러)
생산량1.0000.7070.8320.623
내수판매(국산차)0.7071.0000.5250.456
수출량0.8320.5251.0000.649
수출금액(천달러)0.6230.4560.6491.000
2024-04-13T21:01:55.289898image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
생산량내수판매(국산차)수출량수출금액(천달러)
생산량1.0000.4950.9560.574
내수판매(국산차)0.4951.0000.3250.224
수출량0.9560.3251.0000.580
수출금액(천달러)0.5740.2240.5801.000

Missing values

2024-04-13T21:01:50.093628image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-04-13T21:01:50.426267image/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

기간생산량내수판매(국산차)수출량수출금액(천달러)
02009-01189333738741229461376094
12009-02237006879031515731699904
22009-03261701954841617651808416
32009-04269263945231698151942569
42009-052563291244791530931774136
52009-063159211434131796452050591
62009-073103421192771813822133771
72009-08232552914671411891704574
82009-093693471382832254112664644
92009-103372521309322094602565717
기간생산량내수판매(국산차)수출량수출금액(천달러)
1702023-034098111413882629146495857
1712023-043810271291022491056155913
1722023-053821221308762474066194208
1732023-063702931345212403276227738
1742023-073529721153902297465902529
1752023-083119571071322010625292713
1762023-093018041072581968775227442
1772023-103410241177932250305880107
1782023-113705131327862449306529081
1792023-123676311151392472066384449