Overview

Dataset statistics

Number of variables2
Number of observations126
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory2.2 KiB
Average record size in memory18.0 B

Variable types

DateTime1
Numeric1

Dataset

Description동 데이터는 최근 10년간(2013년~2023년 현재 기준) 우리나라 외환보유액에 대한 자료입니다 월별 기준이며, 단위는 천달러 입니다.
URLhttps://www.data.go.kr/data/15117348/fileData.do

Alerts

날짜 has unique valuesUnique
외환보유액(단위_천달러) has unique valuesUnique

Reproduction

Analysis started2023-12-12 07:35:44.280934
Analysis finished2023-12-12 07:35:44.529187
Duration0.25 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

날짜
Date

UNIQUE 

Distinct126
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size1.1 KiB
Minimum2013-01-01 00:00:00
Maximum2023-06-01 00:00:00
2023-12-12T16:35:44.602304image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T16:35:44.730834image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

외환보유액(단위_천달러)
Real number (ℝ)

UNIQUE 

Distinct126
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean3.9467716 × 108
Minimum3.2643998 × 108
Maximum4.6920774 × 108
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.2 KiB
2023-12-12T16:35:44.888263image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum3.2643998 × 108
5-th percentile3.300554 × 108
Q13.6820107 × 108
median3.9758754 × 108
Q34.1840476 × 108
95-th percentile4.6081522 × 108
Maximum4.6920774 × 108
Range1.4276776 × 108
Interquartile range (IQR)50203688

Descriptive statistics

Standard deviation36509098
Coefficient of variation (CV)0.092503703
Kurtosis-0.65300828
Mean3.9467716 × 108
Median Absolute Deviation (MAD)27691578
Skewness0.18348221
Sum4.9729322 × 1010
Variance1.3329143 × 1015
MonotonicityNot monotonic
2023-12-12T16:35:45.075497image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
421453923 1
 
0.8%
375166658 1
 
0.8%
368113633 1
 
0.8%
369600626 1
 
0.8%
368463398 1
 
0.8%
367961865 1
 
0.8%
367293330 1
 
0.8%
365758112 1
 
0.8%
369839889 1
 
0.8%
372481509 1
 
0.8%
Other values (116) 116
92.1%
ValueCountFrequency (%)
326439981 1
0.8%
327395341 1
0.8%
327408423 1
0.8%
328095419 1
0.8%
328799477 1
0.8%
328910278 1
0.8%
329709314 1
0.8%
331093643 1
0.8%
336921772 1
0.8%
343225517 1
0.8%
ValueCountFrequency (%)
469207742 1
0.8%
463972259 1
0.8%
463933550 1
0.8%
463907617 1
0.8%
463118362 1
0.8%
461766293 1
0.8%
461526656 1
0.8%
458680900 1
0.8%
457810337 1
0.8%
456458881 1
0.8%

Interactions

2023-12-12T16:35:44.314573image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Missing values

2023-12-12T16:35:44.423345image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-12T16:35:44.498139image/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

날짜외환보유액(단위_천달러)
02023-06-01421453923
12023-05-01420983378
22023-04-01426683640
32023-03-01426069328
42023-02-01425286150
52023-01-01429967671
62022-12-01423163664
72022-11-01416104905
82022-10-01414005699
92022-09-01416766652
날짜외환보유액(단위_천달러)
1162013-10-01343225517
1172013-09-01336921772
1182013-08-01331093643
1192013-07-01329709314
1202013-06-01326439981
1212013-05-01328095419
1222013-04-01328799477
1232013-03-01327408423
1242013-02-01327395341
1252013-01-01328910278