Overview

Dataset statistics

Number of variables4
Number of observations27
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory1.1 KiB
Average record size in memory40.9 B

Variable types

Numeric4

Dataset

Description1997부터 2023년까지 국내 조선산업 수출액, 수입액, 무역수지에 대한 정보제공(2023년 12월 31일 기준 통계)
Author산업통상자원부
URLhttps://www.data.go.kr/data/15051113/fileData.do

Alerts

연도 is highly overall correlated with 무역수지(억불) and 2 other fieldsHigh correlation
무역수지(억불) is highly overall correlated with 연도 and 2 other fieldsHigh correlation
수출(억불) is highly overall correlated with 연도 and 2 other fieldsHigh correlation
수입(억불) is highly overall correlated with 연도 and 2 other fieldsHigh correlation
연도 has unique valuesUnique
수출(억불) has unique valuesUnique

Reproduction

Analysis started2024-03-30 01:44:42.243903
Analysis finished2024-03-30 01:44:46.651499
Duration4.41 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

연도
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct27
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2010
Minimum1997
Maximum2023
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size375.0 B
2024-03-30T01:44:46.856837image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1997
5-th percentile1998.3
Q12003.5
median2010
Q32016.5
95-th percentile2021.7
Maximum2023
Range26
Interquartile range (IQR)13

Descriptive statistics

Standard deviation7.9372539
Coefficient of variation (CV)0.0039488826
Kurtosis-1.2
Mean2010
Median Absolute Deviation (MAD)7
Skewness0
Sum54270
Variance63
MonotonicityStrictly increasing
2024-03-30T01:44:47.288209image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=27)
ValueCountFrequency (%)
1997 1
 
3.7%
1998 1
 
3.7%
2023 1
 
3.7%
2022 1
 
3.7%
2021 1
 
3.7%
2020 1
 
3.7%
2019 1
 
3.7%
2018 1
 
3.7%
2017 1
 
3.7%
2016 1
 
3.7%
Other values (17) 17
63.0%
ValueCountFrequency (%)
1997 1
3.7%
1998 1
3.7%
1999 1
3.7%
2000 1
3.7%
2001 1
3.7%
2002 1
3.7%
2003 1
3.7%
2004 1
3.7%
2005 1
3.7%
2006 1
3.7%
ValueCountFrequency (%)
2023 1
3.7%
2022 1
3.7%
2021 1
3.7%
2020 1
3.7%
2019 1
3.7%
2018 1
3.7%
2017 1
3.7%
2016 1
3.7%
2015 1
3.7%
2014 1
3.7%

무역수지(억불)
Real number (ℝ)

HIGH CORRELATION 

Distinct26
Distinct (%)96.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean230.83704
Minimum54.8
Maximum522.3
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size375.0 B
2024-03-30T01:44:47.648746image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum54.8
5-th percentile71.12
Q1122.05
median193.4
Q3354.95
95-th percentile428.08
Maximum522.3
Range467.5
Interquartile range (IQR)232.9

Descriptive statistics

Standard deviation133.50784
Coefficient of variation (CV)0.57836402
Kurtosis-0.93439076
Mean230.83704
Median Absolute Deviation (MAD)115.6
Skewness0.48267892
Sum6232.6
Variance17824.342
MonotonicityNot monotonic
2024-03-30T01:44:48.049902image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=26)
ValueCountFrequency (%)
193.4 2
 
7.4%
54.8 1
 
3.7%
522.3 1
 
3.7%
150.1 1
 
3.7%
163.1 1
 
3.7%
177.8 1
 
3.7%
186.4 1
 
3.7%
397.1 1
 
3.7%
310.1 1
 
3.7%
357.1 1
 
3.7%
Other values (16) 16
59.3%
ValueCountFrequency (%)
54.8 1
3.7%
70.1 1
3.7%
73.5 1
3.7%
77.8 1
3.7%
90.0 1
3.7%
98.6 1
3.7%
103.4 1
3.7%
140.7 1
3.7%
150.1 1
3.7%
158.3 1
3.7%
ValueCountFrequency (%)
522.3 1
3.7%
439.0 1
3.7%
402.6 1
3.7%
397.1 1
3.7%
378.3 1
3.7%
359.2 1
3.7%
357.1 1
3.7%
352.8 1
3.7%
335.3 1
3.7%
310.1 1
3.7%

수출(억불)
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct27
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean258.45185
Minimum66.5
Maximum565.9
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size375.0 B
2024-03-30T01:44:48.443104image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum66.5
5-th percentile77.97
Q1134.95
median218.4
Q3398.2
95-th percentile479.16
Maximum565.9
Range499.4
Interquartile range (IQR)263.25

Descriptive statistics

Standard deviation146.55436
Coefficient of variation (CV)0.56704707
Kurtosis-1.0248085
Mean258.45185
Median Absolute Deviation (MAD)124.3
Skewness0.41843082
Sum6978.2
Variance21478.182
MonotonicityNot monotonic
2024-03-30T01:44:48.838888image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=27)
ValueCountFrequency (%)
66.5 1
 
3.7%
81.4 1
 
3.7%
218.4 1
 
3.7%
181.8 1
 
3.7%
229.9 1
 
3.7%
197.5 1
 
3.7%
201.6 1
 
3.7%
212.8 1
 
3.7%
421.8 1
 
3.7%
342.7 1
 
3.7%
Other values (17) 17
63.0%
ValueCountFrequency (%)
66.5 1
3.7%
76.5 1
3.7%
81.4 1
3.7%
84.2 1
3.7%
99.1 1
3.7%
108.7 1
3.7%
113.3 1
3.7%
156.6 1
3.7%
177.3 1
3.7%
181.8 1
3.7%
ValueCountFrequency (%)
565.9 1
3.7%
491.1 1
3.7%
451.3 1
3.7%
431.6 1
3.7%
421.8 1
3.7%
401.1 1
3.7%
398.9 1
3.7%
397.5 1
3.7%
371.7 1
3.7%
342.7 1
3.7%

수입(억불)
Real number (ℝ)

HIGH CORRELATION 

Distinct26
Distinct (%)96.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean27.614815
Minimum6.4
Maximum53.3
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size375.0 B
2024-03-30T01:44:49.202414image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum6.4
5-th percentile6.85
Q113.8
median26.4
Q338.1
95-th percentile51.08
Maximum53.3
Range46.9
Interquartile range (IQR)24.3

Descriptive statistics

Standard deviation14.84452
Coefficient of variation (CV)0.53755638
Kurtosis-1.1744356
Mean27.614815
Median Absolute Deviation (MAD)13.3
Skewness0.093171202
Sum745.6
Variance220.35977
MonotonicityNot monotonic
2024-03-30T01:44:49.643259image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=26)
ValueCountFrequency (%)
6.4 2
 
7.4%
11.7 1
 
3.7%
44.7 1
 
3.7%
25.0 1
 
3.7%
31.7 1
 
3.7%
36.5 1
 
3.7%
34.4 1
 
3.7%
23.8 1
 
3.7%
26.4 1
 
3.7%
24.7 1
 
3.7%
Other values (16) 16
59.3%
ValueCountFrequency (%)
6.4 2
7.4%
7.9 1
3.7%
9.1 1
3.7%
9.9 1
3.7%
10.1 1
3.7%
11.7 1
3.7%
15.9 1
3.7%
19.0 1
3.7%
20.1 1
3.7%
23.8 1
3.7%
ValueCountFrequency (%)
53.3 1
3.7%
52.1 1
3.7%
48.7 1
3.7%
44.7 1
3.7%
44.0 1
3.7%
43.6 1
3.7%
39.7 1
3.7%
36.5 1
3.7%
36.4 1
3.7%
34.4 1
3.7%

Interactions

2024-03-30T01:44:45.194581image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T01:44:42.489496image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T01:44:43.384409image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T01:44:44.185783image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T01:44:45.482444image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T01:44:42.730507image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T01:44:43.594474image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T01:44:44.494389image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T01:44:45.715266image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T01:44:42.951529image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T01:44:43.804932image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T01:44:44.725057image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T01:44:45.969155image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T01:44:43.160774image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T01:44:43.978029image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T01:44:44.963760image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-03-30T01:44:49.912006image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연도무역수지(억불)수출(억불)수입(억불)
연도1.0000.9350.9220.729
무역수지(억불)0.9351.0000.9920.648
수출(억불)0.9220.9921.0000.820
수입(억불)0.7290.6480.8201.000
2024-03-30T01:44:50.222504image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연도무역수지(억불)수출(억불)수입(억불)
연도1.0000.5090.5230.580
무역수지(억불)0.5091.0000.9970.869
수출(억불)0.5230.9971.0000.892
수입(억불)0.5800.8690.8921.000

Missing values

2024-03-30T01:44:46.248443image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-03-30T01:44:46.527455image/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

연도무역수지(억불)수출(억불)수입(억불)
0199754.866.511.7
1199873.581.47.9
2199970.176.56.4
3200077.884.26.4
4200190.099.19.1
5200298.6108.710.1
62003103.4113.39.9
72004140.7156.615.9
82005158.3177.319.0
92006201.1221.220.1
연도무역수지(억불)수출(억불)수입(억불)
172014359.2398.939.7
182015357.1401.144.0
192016310.1342.732.6
202017397.1421.824.7
212018186.4212.826.4
222019177.8201.623.8
232020163.1197.534.4
242021193.4229.936.5
252022150.1181.831.7
262023193.4218.425.0