Overview

Dataset statistics

Number of variables5
Number of observations31
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory1.5 KiB
Average record size in memory48.3 B

Variable types

DateTime1
Numeric4

Dataset

Description인천광역시 수출입 통관실적_현황 자료2020~2022년 연간 누계 및 2022년까지의 월별 데이터를 제공합니다.
Author인천광역시
URLhttps://data.incheon.go.kr/findData/publicDataDetail?dataId=15055187&srcSe=7661IVAWM27C61E190

Alerts

총액_천달러 is highly overall correlated with 수출_천달러 and 2 other fieldsHigh correlation
수출_천달러 is highly overall correlated with 총액_천달러 and 2 other fieldsHigh correlation
수입_천달러 is highly overall correlated with 총액_천달러 and 2 other fieldsHigh correlation
수출입초과_천달러 is highly overall correlated with 총액_천달러 and 2 other fieldsHigh correlation
연도별 has unique valuesUnique
총액_천달러 has unique valuesUnique
수출_천달러 has unique valuesUnique
수입_천달러 has unique valuesUnique
수출입초과_천달러 has unique valuesUnique

Reproduction

Analysis started2024-01-28 12:30:30.586860
Analysis finished2024-01-28 12:30:32.210006
Duration1.62 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

연도별
Date

UNIQUE 

Distinct31
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size380.0 B
Minimum2020-01-01 00:00:00
Maximum2022-07-01 00:00:00
2024-01-28T21:30:32.262867image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-28T21:30:32.376022image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=31)

총액_천달러
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct31
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean7969545.4
Minimum5385631
Maximum11307455
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size411.0 B
2024-01-28T21:30:32.481834image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum5385631
5-th percentile5665506.5
Q16689561.5
median7370782
Q39204849.5
95-th percentile11047376
Maximum11307455
Range5921824
Interquartile range (IQR)2515288

Descriptive statistics

Standard deviation1763001.3
Coefficient of variation (CV)0.2212173
Kurtosis-0.91939588
Mean7969545.4
Median Absolute Deviation (MAD)1308042
Skewness0.44445272
Sum2.4705591 × 108
Variance3.1081736 × 1012
MonotonicityNot monotonic
2024-01-28T21:30:32.589655image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=31)
ValueCountFrequency (%)
6758672 1
 
3.2%
6632023 1
 
3.2%
11103116 1
 
3.2%
10254881 1
 
3.2%
9816526 1
 
3.2%
9256872 1
 
3.2%
11307455 1
 
3.2%
8634128 1
 
3.2%
10991637 1
 
3.2%
10759770 1
 
3.2%
Other values (21) 21
67.7%
ValueCountFrequency (%)
5385631 1
3.2%
5643009 1
3.2%
5688004 1
3.2%
5894448 1
3.2%
6004279 1
3.2%
6428105 1
3.2%
6434623 1
3.2%
6632023 1
3.2%
6747100 1
3.2%
6758672 1
3.2%
ValueCountFrequency (%)
11307455 1
3.2%
11103116 1
3.2%
10991637 1
3.2%
10759770 1
3.2%
10254881 1
3.2%
9816526 1
3.2%
9401412 1
3.2%
9256872 1
3.2%
9152827 1
3.2%
8854531 1
3.2%

수출_천달러
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct31
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean3708492.7
Minimum2670253
Maximum5093913
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size411.0 B
2024-01-28T21:30:32.704410image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum2670253
5-th percentile2789162
Q13206920.5
median3682944
Q34210933.5
95-th percentile4829301
Maximum5093913
Range2423660
Interquartile range (IQR)1004013

Descriptive statistics

Standard deviation662053.52
Coefficient of variation (CV)0.17852361
Kurtosis-0.76093871
Mean3708492.7
Median Absolute Deviation (MAD)493926
Skewness0.32213094
Sum1.1496327 × 108
Variance4.3831486 × 1011
MonotonicityNot monotonic
2024-01-28T21:30:33.163305image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=31)
ValueCountFrequency (%)
3085773 1
 
3.2%
3227442 1
 
3.2%
5093913 1
 
3.2%
4732476 1
 
3.2%
4244997 1
 
3.2%
4069095 1
 
3.2%
4926126 1
 
3.2%
3954805 1
 
3.2%
4292632 1
 
3.2%
4606028 1
 
3.2%
Other values (21) 21
67.7%
ValueCountFrequency (%)
2670253 1
3.2%
2777588 1
3.2%
2800736 1
3.2%
2932714 1
3.2%
2933011 1
3.2%
3040359 1
3.2%
3085773 1
3.2%
3189961 1
3.2%
3223880 1
3.2%
3227442 1
3.2%
ValueCountFrequency (%)
5093913 1
3.2%
4926126 1
3.2%
4732476 1
3.2%
4606028 1
3.2%
4342552 1
3.2%
4297438 1
3.2%
4292632 1
3.2%
4244997 1
3.2%
4176870 1
3.2%
4069095 1
3.2%

수입_천달러
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct31
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean4261052.7
Minimum2715378
Maximum6699005
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size411.0 B
2024-01-28T21:30:33.268898image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum2715378
5-th percentile2876344.5
Q13399422.5
median3858370
Q34985361
95-th percentile6267535.5
Maximum6699005
Range3983627
Interquartile range (IQR)1585938.5

Descriptive statistics

Standard deviation1136757.1
Coefficient of variation (CV)0.26677847
Kurtosis-0.7129233
Mean4261052.7
Median Absolute Deviation (MAD)820953
Skewness0.59318304
Sum1.3209263 × 108
Variance1.2922168 × 1012
MonotonicityNot monotonic
2024-01-28T21:30:33.382743image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=31)
ValueCountFrequency (%)
3672899 1
 
3.2%
3404581 1
 
3.2%
6009203 1
 
3.2%
5522405 1
 
3.2%
5571529 1
 
3.2%
5187777 1
 
3.2%
6381329 1
 
3.2%
4679323 1
 
3.2%
6699005 1
 
3.2%
6153742 1
 
3.2%
Other values (21) 21
67.7%
ValueCountFrequency (%)
2715378 1
3.2%
2865421 1
3.2%
2887268 1
3.2%
2961734 1
3.2%
3071268 1
3.2%
3204225 1
3.2%
3265472 1
3.2%
3394264 1
3.2%
3404581 1
3.2%
3416292 1
3.2%
ValueCountFrequency (%)
6699005 1
3.2%
6381329 1
3.2%
6153742 1
3.2%
6009203 1
3.2%
5571529 1
3.2%
5522405 1
3.2%
5187777 1
3.2%
5058860 1
3.2%
4911862 1
3.2%
4855389 1
3.2%

수출입초과_천달러
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct31
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean-552560.03
Minimum-2406373
Maximum428196
Zeros0
Zeros (%)0.0%
Negative28
Negative (%)90.3%
Memory size411.0 B
2024-01-28T21:30:33.498602image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum-2406373
5-th percentile-1501458.5
Q1-776057
median-446857
Q3-113045
95-th percentile117905.5
Maximum428196
Range2834569
Interquartile range (IQR)663012

Descriptive statistics

Standard deviation594045.17
Coefficient of variation (CV)-1.0750781
Kurtosis1.8652652
Mean-552560.03
Median Absolute Deviation (MAD)343072
Skewness-1.1367654
Sum-17129361
Variance3.5288967 × 1011
MonotonicityNot monotonic
2024-01-28T21:30:33.634279image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=31)
ValueCountFrequency (%)
-587126 1
 
3.2%
-177139 1
 
3.2%
-915290 1
 
3.2%
-789929 1
 
3.2%
-1326532 1
 
3.2%
-1118682 1
 
3.2%
-1455203 1
 
3.2%
-724518 1
 
3.2%
-2406373 1
 
3.2%
-1547714 1
 
3.2%
Other values (21) 21
67.7%
ValueCountFrequency (%)
-2406373 1
3.2%
-1547714 1
3.2%
-1455203 1
3.2%
-1326532 1
3.2%
-1198434 1
3.2%
-1118682 1
3.2%
-915290 1
3.2%
-789929 1
3.2%
-762185 1
3.2%
-724518 1
3.2%
ValueCountFrequency (%)
428196 1
3.2%
216156 1
3.2%
19655 1
3.2%
-29020 1
3.2%
-45125 1
3.2%
-48891 1
3.2%
-86532 1
3.2%
-87833 1
3.2%
-138257 1
3.2%
-168902 1
3.2%

Interactions

2024-01-28T21:30:31.717521image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-28T21:30:30.706878image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-28T21:30:31.039262image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-28T21:30:31.345431image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-28T21:30:31.810725image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-28T21:30:30.783116image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-28T21:30:31.119967image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-28T21:30:31.431554image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-28T21:30:31.881234image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-28T21:30:30.857929image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-28T21:30:31.187809image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-28T21:30:31.507098image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-28T21:30:31.973635image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-28T21:30:30.942499image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-28T21:30:31.268516image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-28T21:30:31.599970image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-01-28T21:30:33.717758image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연도별총액_천달러수출_천달러수입_천달러수출입초과_천달러
연도별1.0001.0001.0001.0001.000
총액_천달러1.0001.0000.8950.8620.599
수출_천달러1.0000.8951.0000.6730.444
수입_천달러1.0000.8620.6731.0000.712
수출입초과_천달러1.0000.5990.4440.7121.000
2024-01-28T21:30:33.806311image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
총액_천달러수출_천달러수입_천달러수출입초과_천달러
총액_천달러1.0000.9740.983-0.819
수출_천달러0.9741.0000.930-0.706
수입_천달러0.9830.9301.000-0.894
수출입초과_천달러-0.819-0.706-0.8941.000

Missing values

2024-01-28T21:30:32.073479image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-01-28T21:30:32.171227image/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

연도별총액_천달러수출_천달러수입_천달러수출입초과_천달러
02020-01675867230857733672899-587126
12020-02663202332274423404581-177139
22020-03726078038444883416292428196
32020-04589444829327142961734-29020
42020-05538563126702532715378-45125
52020-06568800428007362887268-86532
62020-07600427929330113071268-138257
72020-08564300927775882865421-87833
82020-09674710034816283265472216156
92020-10643462330403593394264-353905
연도별총액_천달러수출_천달러수입_천달러수출입초과_천달러
212021-10940141243425525058860-716308
222021-11915282742974384855389-557951
232021-121075977046060286153742-1547714
242022-011099163742926326699005-2406373
252022-02863412839548054679323-724518
262022-031130745549261266381329-1455203
272022-04925687240690955187777-1118682
282022-05981652642449975571529-1326532
292022-061025488147324765522405-789929
302022-071110311650939136009203-915290