Overview

Dataset statistics

Number of variables5
Number of observations28
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory1.3 KiB
Average record size in memory48.6 B

Variable types

Numeric4
Text1

Dataset

Description울산광역시 연도별(1960년대, 1970년대, 1980년대, 1990년대, 2000~2022년) 외국인 직접 투자 신고 건수 및 투자 금액(백만달러 단위) 규모 제공
Author울산광역시
URLhttps://www.data.go.kr/data/15065099/fileData.do

Alerts

순번 is highly overall correlated with 투자금액(백만달러) and 1 other fieldsHigh correlation
신고건수 is highly overall correlated with 투자금액(백만달러) and 1 other fieldsHigh correlation
투자금액(백만달러) is highly overall correlated with 순번 and 2 other fieldsHigh correlation
백분율 is highly overall correlated with 순번 and 2 other fieldsHigh correlation
순번 has unique valuesUnique
연도 has unique valuesUnique
투자금액(백만달러) has unique valuesUnique

Reproduction

Analysis started2024-03-14 14:52:31.615919
Analysis finished2024-03-14 14:52:34.529327
Duration2.91 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

순번
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct28
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean14.5
Minimum1
Maximum28
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size380.0 B
2024-03-14T23:52:34.641891image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile2.35
Q17.75
median14.5
Q321.25
95-th percentile26.65
Maximum28
Range27
Interquartile range (IQR)13.5

Descriptive statistics

Standard deviation8.2259751
Coefficient of variation (CV)0.56730863
Kurtosis-1.2
Mean14.5
Median Absolute Deviation (MAD)7
Skewness0
Sum406
Variance67.666667
MonotonicityStrictly increasing
2024-03-14T23:52:34.863702image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=28)
ValueCountFrequency (%)
1 1
 
3.6%
16 1
 
3.6%
28 1
 
3.6%
27 1
 
3.6%
26 1
 
3.6%
25 1
 
3.6%
24 1
 
3.6%
23 1
 
3.6%
22 1
 
3.6%
21 1
 
3.6%
Other values (18) 18
64.3%
ValueCountFrequency (%)
1 1
3.6%
2 1
3.6%
3 1
3.6%
4 1
3.6%
5 1
3.6%
6 1
3.6%
7 1
3.6%
8 1
3.6%
9 1
3.6%
10 1
3.6%
ValueCountFrequency (%)
28 1
3.6%
27 1
3.6%
26 1
3.6%
25 1
3.6%
24 1
3.6%
23 1
3.6%
22 1
3.6%
21 1
3.6%
20 1
3.6%
19 1
3.6%

연도
Text

UNIQUE 

Distinct28
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size352.0 B
2024-03-14T23:52:35.568213image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length6
Median length5
Mean length5.1428571
Min length5

Characters and Unicode

Total characters144
Distinct characters12
Distinct categories2 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique28 ?
Unique (%)100.0%

Sample

1st row1960년대
2nd row1970년대
3rd row1980년대
4th row1990년대
5th row2000년
ValueCountFrequency (%)
1960년대 1
 
3.6%
1970년대 1
 
3.6%
2022년 1
 
3.6%
2021년 1
 
3.6%
2020년 1
 
3.6%
2019년 1
 
3.6%
2018년 1
 
3.6%
2017년 1
 
3.6%
2016년 1
 
3.6%
2015년 1
 
3.6%
Other values (18) 18
64.3%
2024-03-14T23:52:36.752332image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 41
28.5%
2 31
21.5%
28
19.4%
1 17
11.8%
9 7
 
4.9%
4
 
2.8%
6 3
 
2.1%
7 3
 
2.1%
8 3
 
2.1%
3 3
 
2.1%
Other values (2) 4
 
2.8%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 112
77.8%
Other Letter 32
 
22.2%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 41
36.6%
2 31
27.7%
1 17
15.2%
9 7
 
6.2%
6 3
 
2.7%
7 3
 
2.7%
8 3
 
2.7%
3 3
 
2.7%
4 2
 
1.8%
5 2
 
1.8%
Other Letter
ValueCountFrequency (%)
28
87.5%
4
 
12.5%

Most occurring scripts

ValueCountFrequency (%)
Common 112
77.8%
Hangul 32
 
22.2%

Most frequent character per script

Common
ValueCountFrequency (%)
0 41
36.6%
2 31
27.7%
1 17
15.2%
9 7
 
6.2%
6 3
 
2.7%
7 3
 
2.7%
8 3
 
2.7%
3 3
 
2.7%
4 2
 
1.8%
5 2
 
1.8%
Hangul
ValueCountFrequency (%)
28
87.5%
4
 
12.5%

Most occurring blocks

ValueCountFrequency (%)
ASCII 112
77.8%
Hangul 32
 
22.2%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 41
36.6%
2 31
27.7%
1 17
15.2%
9 7
 
6.2%
6 3
 
2.7%
7 3
 
2.7%
8 3
 
2.7%
3 3
 
2.7%
4 2
 
1.8%
5 2
 
1.8%
Hangul
ValueCountFrequency (%)
28
87.5%
4
 
12.5%

신고건수
Real number (ℝ)

HIGH CORRELATION 

Distinct18
Distinct (%)64.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean22.142857
Minimum5
Maximum95
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size380.0 B
2024-03-14T23:52:36.957025image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum5
5-th percentile8.35
Q113
median18.5
Q322
95-th percentile59.3
Maximum95
Range90
Interquartile range (IQR)9

Descriptive statistics

Standard deviation18.729486
Coefficient of variation (CV)0.84584776
Kurtosis8.9461658
Mean22.142857
Median Absolute Deviation (MAD)4.5
Skewness2.8585693
Sum620
Variance350.79365
MonotonicityNot monotonic
2024-03-14T23:52:37.137105image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=18)
ValueCountFrequency (%)
14 4
14.3%
22 3
 
10.7%
13 3
 
10.7%
10 2
 
7.1%
20 2
 
7.1%
19 2
 
7.1%
5 1
 
3.6%
45 1
 
3.6%
21 1
 
3.6%
9 1
 
3.6%
Other values (8) 8
28.6%
ValueCountFrequency (%)
5 1
 
3.6%
8 1
 
3.6%
9 1
 
3.6%
10 2
7.1%
13 3
10.7%
14 4
14.3%
16 1
 
3.6%
18 1
 
3.6%
19 2
7.1%
20 2
7.1%
ValueCountFrequency (%)
95 1
 
3.6%
67 1
 
3.6%
45 1
 
3.6%
30 1
 
3.6%
24 1
 
3.6%
23 1
 
3.6%
22 3
10.7%
21 1
 
3.6%
20 2
7.1%
19 2
7.1%

투자금액(백만달러)
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct28
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean576.07607
Minimum14.8
Maximum3329.21
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size380.0 B
2024-03-14T23:52:37.328665image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum14.8
5-th percentile22.5325
Q163.15
median272.15
Q3693.5125
95-th percentile2123.673
Maximum3329.21
Range3314.41
Interquartile range (IQR)630.3625

Descriptive statistics

Standard deviation785.77258
Coefficient of variation (CV)1.3640084
Kurtosis5.3002391
Mean576.07607
Median Absolute Deviation (MAD)232.16
Skewness2.228764
Sum16130.13
Variance617438.55
MonotonicityNot monotonic
2024-03-14T23:52:37.541436image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=28)
ValueCountFrequency (%)
14.8 1
 
3.6%
655.95 1
 
3.6%
1242.0 1
 
3.6%
3329.21 1
 
3.6%
94.33 1
 
3.6%
175.68 1
 
3.6%
806.2 1
 
3.6%
1568.17 1
 
3.6%
504.06 1
 
3.6%
272.81 1
 
3.6%
Other values (18) 18
64.3%
ValueCountFrequency (%)
14.8 1
3.6%
14.92 1
3.6%
36.67 1
3.6%
39.74 1
3.6%
45.87 1
3.6%
60.68 1
3.6%
61.29 1
3.6%
63.77 1
3.6%
86.11 1
3.6%
91.75 1
3.6%
ValueCountFrequency (%)
3329.21 1
3.6%
2422.79 1
3.6%
1568.17 1
3.6%
1273.86 1
3.6%
1242.0 1
3.6%
975.9 1
3.6%
806.2 1
3.6%
655.95 1
3.6%
514.15 1
3.6%
509.56 1
3.6%

백분율
Real number (ℝ)

HIGH CORRELATION 

Distinct26
Distinct (%)92.9%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean3.5714286
Minimum0.09
Maximum20.64
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size380.0 B
2024-03-14T23:52:38.024184image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0.09
5-th percentile0.139
Q10.395
median1.685
Q34.3025
95-th percentile13.165
Maximum20.64
Range20.55
Interquartile range (IQR)3.9075

Descriptive statistics

Standard deviation4.8715727
Coefficient of variation (CV)1.3640403
Kurtosis5.2997228
Mean3.5714286
Median Absolute Deviation (MAD)1.435
Skewness2.2286188
Sum100
Variance23.73222
MonotonicityNot monotonic
2024-03-14T23:52:38.228675image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=26)
ValueCountFrequency (%)
0.09 2
 
7.1%
0.38 2
 
7.1%
3.19 1
 
3.6%
7.7 1
 
3.6%
20.64 1
 
3.6%
0.58 1
 
3.6%
1.09 1
 
3.6%
5.0 1
 
3.6%
9.72 1
 
3.6%
3.12 1
 
3.6%
Other values (16) 16
57.1%
ValueCountFrequency (%)
0.09 2
7.1%
0.23 1
3.6%
0.25 1
3.6%
0.28 1
3.6%
0.38 2
7.1%
0.4 1
3.6%
0.53 1
3.6%
0.57 1
3.6%
0.58 1
3.6%
1.09 1
3.6%
ValueCountFrequency (%)
20.64 1
3.6%
15.02 1
3.6%
9.72 1
3.6%
7.9 1
3.6%
7.7 1
3.6%
6.05 1
3.6%
5.0 1
3.6%
4.07 1
3.6%
3.19 1
3.6%
3.16 1
3.6%

Interactions

2024-03-14T23:52:33.638205image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T23:52:31.777543image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T23:52:32.465643image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T23:52:32.991717image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T23:52:33.773275image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T23:52:32.017191image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T23:52:32.596142image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T23:52:33.136116image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T23:52:33.895367image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T23:52:32.189945image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T23:52:32.730441image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T23:52:33.351631image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T23:52:34.043324image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T23:52:32.333467image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T23:52:32.866630image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T23:52:33.501414image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-03-14T23:52:38.386916image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
순번연도신고건수투자금액(백만달러)백분율
순번1.0001.0000.3770.2860.286
연도1.0001.0001.0001.0001.000
신고건수0.3771.0001.0000.5990.599
투자금액(백만달러)0.2861.0000.5991.0001.000
백분율0.2861.0000.5991.0001.000
2024-03-14T23:52:38.654066image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
순번신고건수투자금액(백만달러)백분율
순번1.0000.0390.5180.515
신고건수0.0391.0000.5920.593
투자금액(백만달러)0.5180.5921.0001.000
백분율0.5150.5931.0001.000

Missing values

2024-03-14T23:52:34.213403image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-03-14T23:52:34.416106image/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

순번연도신고건수투자금액(백만달러)백분율
011960년대514.80.09
121970년대3063.770.4
231980년대67305.861.9
341990년대951273.867.9
452000년22509.563.16
562001년1339.740.25
672002년1360.680.38
782003년1086.110.53
892004년1014.920.09
9102005년1636.670.23
순번연도신고건수투자금액(백만달러)백분율
18192014년232422.7915.02
19202015년22975.96.05
20212016년9272.811.69
21222017년14504.063.12
22232018년191568.179.72
23242019년14806.25.0
24252020년14175.681.09
25262021년2094.330.58
26272022년213329.2120.64
27282023년451242.07.7