Overview

Dataset statistics

Number of variables7
Number of observations24
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory1.5 KiB
Average record size in memory65.5 B

Variable types

DateTime1
Text1
Categorical1
Numeric4

Alerts

집계년월 has constant value ""Constant
동력척수(척) is highly overall correlated with 동력톤수 and 1 other fieldsHigh correlation
동력톤수 is highly overall correlated with 동력척수(척) and 1 other fieldsHigh correlation
무동력척수(척) is highly overall correlated with 무동력톤수High correlation
무동력톤수 is highly overall correlated with 무동력척수(척)High correlation
해면내수면구분명 is highly overall correlated with 동력척수(척) and 1 other fieldsHigh correlation
동력척수(척) has 3 (12.5%) zerosZeros
동력톤수 has 4 (16.7%) zerosZeros
무동력척수(척) has 7 (29.2%) zerosZeros
무동력톤수 has 10 (41.7%) zerosZeros

Reproduction

Analysis started2023-12-10 22:36:48.270269
Analysis finished2023-12-10 22:36:49.983419
Duration1.71 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

집계년월
Date

CONSTANT 

Distinct1
Distinct (%)4.2%
Missing0
Missing (%)0.0%
Memory size324.0 B
Minimum2021-12-01 00:00:00
Maximum2021-12-01 00:00:00
2023-12-11T07:36:50.017183image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:36:50.091465image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=1)

시군명
Text

Distinct20
Distinct (%)83.3%
Missing0
Missing (%)0.0%
Memory size324.0 B
2023-12-11T07:36:50.231478image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length4
Median length3
Mean length3.0416667
Min length3

Characters and Unicode

Total characters73
Distinct characters25
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique16 ?
Unique (%)66.7%

Sample

1st row가평군
2nd row고양시
3rd row광주시
4th row군포시
5th row김포시
ValueCountFrequency (%)
화성시 2
 
8.3%
시흥시 2
 
8.3%
평택시 2
 
8.3%
김포시 2
 
8.3%
가평군 1
 
4.2%
여주시 1
 
4.2%
포천시 1
 
4.2%
파주시 1
 
4.2%
이천시 1
 
4.2%
용인시 1
 
4.2%
Other values (10) 10
41.7%
2023-12-11T07:36:50.480512image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
시 23
31.5%
주 5
 
6.8%
군 4
 
5.5%
포 4
 
5.5%
평 4
 
5.5%
양 4
 
5.5%
천 3
 
4.1%
성 3
 
4.1%
산 2
 
2.7%
안 2
 
2.7%
Other values (15) 19
26.0%

Most occurring categories

ValueCountFrequency (%)
Other Letter 73
100.0%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
시 23
31.5%
주 5
 
6.8%
군 4
 
5.5%
포 4
 
5.5%
평 4
 
5.5%
양 4
 
5.5%
천 3
 
4.1%
성 3
 
4.1%
산 2
 
2.7%
안 2
 
2.7%
Other values (15) 19
26.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 73
100.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
시 23
31.5%
주 5
 
6.8%
군 4
 
5.5%
포 4
 
5.5%
평 4
 
5.5%
양 4
 
5.5%
천 3
 
4.1%
성 3
 
4.1%
산 2
 
2.7%
안 2
 
2.7%
Other values (15) 19
26.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 73
100.0%

Most frequent character per block

Hangul
ValueCountFrequency (%)
시 23
31.5%
주 5
 
6.8%
군 4
 
5.5%
포 4
 
5.5%
평 4
 
5.5%
양 4
 
5.5%
천 3
 
4.1%
성 3
 
4.1%
산 2
 
2.7%
안 2
 
2.7%
Other values (15) 19
26.0%

해면내수면구분명
Categorical

HIGH CORRELATION 

Distinct2
Distinct (%)8.3%
Missing0
Missing (%)0.0%
Memory size324.0 B
내수면
19 
해면
5 

Length

Max length3
Median length3
Mean length2.7916667
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row내수면
2nd row내수면
3rd row내수면
4th row내수면
5th row해면

Common Values

ValueCountFrequency (%)
내수면 19
79.2%
해면 5
 
20.8%

Length

2023-12-11T07:36:50.594384image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T07:36:50.680530image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
내수면 19
79.2%
해면 5
 
20.8%

동력척수(척)
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct21
Distinct (%)87.5%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean71.583333
Minimum0
Maximum559
Zeros3
Zeros (%)12.5%
Negative0
Negative (%)0.0%
Memory size348.0 B
2023-12-11T07:36:50.754473image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q17.75
median36.5
Q386.5
95-th percentile204.2
Maximum559
Range559
Interquartile range (IQR)78.75

Descriptive statistics

Standard deviation115.71063
Coefficient of variation (CV)1.6164465
Kurtosis14.558864
Mean71.583333
Median Absolute Deviation (MAD)36
Skewness3.5643961
Sum1718
Variance13388.949
MonotonicityNot monotonic
2023-12-11T07:36:50.847281image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=21)
ValueCountFrequency (%)
0 3
 
12.5%
75 2
 
8.3%
52 1
 
4.2%
32 1
 
4.2%
29 1
 
4.2%
559 1
 
4.2%
9 1
 
4.2%
27 1
 
4.2%
89 1
 
4.2%
3 1
 
4.2%
Other values (11) 11
45.8%
ValueCountFrequency (%)
0 3
12.5%
1 1
 
4.2%
3 1
 
4.2%
4 1
 
4.2%
9 1
 
4.2%
23 1
 
4.2%
25 1
 
4.2%
27 1
 
4.2%
29 1
 
4.2%
32 1
 
4.2%
ValueCountFrequency (%)
559 1
4.2%
221 1
4.2%
109 1
4.2%
104 1
4.2%
89 1
4.2%
88 1
4.2%
86 1
4.2%
75 2
8.3%
66 1
4.2%
52 1
4.2%

동력톤수
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct19
Distinct (%)79.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean187.875
Minimum0
Maximum2065
Zeros4
Zeros (%)16.7%
Negative0
Negative (%)0.0%
Memory size348.0 B
2023-12-11T07:36:50.943118image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q13.5
median24
Q376.75
95-th percentile899.1
Maximum2065
Range2065
Interquartile range (IQR)73.25

Descriptive statistics

Standard deviation458.11023
Coefficient of variation (CV)2.4383778
Kurtosis12.976459
Mean187.875
Median Absolute Deviation (MAD)24
Skewness3.4748563
Sum4509
Variance209864.98
MonotonicityNot monotonic
2023-12-11T07:36:51.039090image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=19)
ValueCountFrequency (%)
0 4
16.7%
18 3
 
12.5%
30 1
 
4.2%
51 1
 
4.2%
2065 1
 
4.2%
4 1
 
4.2%
39 1
 
4.2%
111 1
 
4.2%
54 1
 
4.2%
2 1
 
4.2%
Other values (9) 9
37.5%
ValueCountFrequency (%)
0 4
16.7%
1 1
 
4.2%
2 1
 
4.2%
4 1
 
4.2%
7 1
 
4.2%
14 1
 
4.2%
18 3
12.5%
30 1
 
4.2%
37 1
 
4.2%
39 1
 
4.2%
ValueCountFrequency (%)
2065 1
4.2%
951 1
4.2%
605 1
4.2%
321 1
4.2%
111 1
4.2%
91 1
4.2%
72 1
4.2%
54 1
4.2%
51 1
4.2%
39 1
4.2%

무동력척수(척)
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct11
Distinct (%)45.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean6.7083333
Minimum0
Maximum33
Zeros7
Zeros (%)29.2%
Negative0
Negative (%)0.0%
Memory size348.0 B
2023-12-11T07:36:51.129117image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median3.5
Q37.25
95-th percentile31.8
Maximum33
Range33
Interquartile range (IQR)7.25

Descriptive statistics

Standard deviation10.032465
Coefficient of variation (CV)1.4955228
Kurtosis2.6639842
Mean6.7083333
Median Absolute Deviation (MAD)3.5
Skewness1.8957457
Sum161
Variance100.65036
MonotonicityNot monotonic
2023-12-11T07:36:51.220487image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=11)
ValueCountFrequency (%)
0 7
29.2%
4 4
16.7%
1 4
16.7%
33 2
 
8.3%
8 1
 
4.2%
5 1
 
4.2%
11 1
 
4.2%
16 1
 
4.2%
3 1
 
4.2%
7 1
 
4.2%
ValueCountFrequency (%)
0 7
29.2%
1 4
16.7%
3 1
 
4.2%
4 4
16.7%
5 1
 
4.2%
7 1
 
4.2%
8 1
 
4.2%
11 1
 
4.2%
16 1
 
4.2%
25 1
 
4.2%
ValueCountFrequency (%)
33 2
8.3%
25 1
 
4.2%
16 1
 
4.2%
11 1
 
4.2%
8 1
 
4.2%
7 1
 
4.2%
5 1
 
4.2%
4 4
16.7%
3 1
 
4.2%
1 4
16.7%

무동력톤수
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct8
Distinct (%)33.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2.125
Minimum0
Maximum9
Zeros10
Zeros (%)41.7%
Negative0
Negative (%)0.0%
Memory size348.0 B
2023-12-11T07:36:51.320996image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median1
Q34.25
95-th percentile7.7
Maximum9
Range9
Interquartile range (IQR)4.25

Descriptive statistics

Standard deviation2.7711636
Coefficient of variation (CV)1.304077
Kurtosis0.47155383
Mean2.125
Median Absolute Deviation (MAD)1
Skewness1.2497389
Sum51
Variance7.6793478
MonotonicityNot monotonic
2023-12-11T07:36:51.408592image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=8)
ValueCountFrequency (%)
0 10
41.7%
1 5
20.8%
5 3
 
12.5%
2 2
 
8.3%
9 1
 
4.2%
6 1
 
4.2%
4 1
 
4.2%
8 1
 
4.2%
ValueCountFrequency (%)
0 10
41.7%
1 5
20.8%
2 2
 
8.3%
4 1
 
4.2%
5 3
 
12.5%
6 1
 
4.2%
8 1
 
4.2%
9 1
 
4.2%
ValueCountFrequency (%)
9 1
 
4.2%
8 1
 
4.2%
6 1
 
4.2%
5 3
 
12.5%
4 1
 
4.2%
2 2
 
8.3%
1 5
20.8%
0 10
41.7%

Interactions

2023-12-11T07:36:49.565588image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:36:48.654274image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:36:48.990402image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:36:49.303009image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:36:49.639270image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:36:48.751063image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:36:49.086840image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:36:49.370840image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:36:49.698167image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:36:48.827549image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:36:49.163998image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:36:49.434139image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:36:49.763517image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:36:48.910132image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:36:49.242613image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:36:49.502005image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-11T07:36:51.476165image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
시군명해면내수면구분명동력척수(척)동력톤수무동력척수(척)무동력톤수
시군명1.0000.0000.0000.0000.9260.939
해면내수면구분명0.0001.0000.7550.7090.0000.153
동력척수(척)0.0000.7551.0000.8430.0000.000
동력톤수0.0000.7090.8431.0000.0000.000
무동력척수(척)0.9260.0000.0000.0001.0000.943
무동력톤수0.9390.1530.0000.0000.9431.000
2023-12-11T07:36:51.565307image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
동력척수(척)동력톤수무동력척수(척)무동력톤수해면내수면구분명
동력척수(척)1.0000.921-0.268-0.1020.517
동력톤수0.9211.000-0.371-0.1630.783
무동력척수(척)-0.268-0.3711.0000.9200.000
무동력톤수-0.102-0.1630.9201.0000.000
해면내수면구분명0.5170.7830.0000.0001.000

Missing values

2023-12-11T07:36:49.851175image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-11T07:36:49.947316image/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

집계년월시군명해면내수면구분명동력척수(척)동력톤수무동력척수(척)무동력톤수
02021-12가평군내수면523000
12021-12고양시내수면413700
22021-12광주시내수면0082
32021-12군포시내수면0000
42021-12김포시해면10960500
52021-12김포시내수면759100
62021-12남양주시내수면2518339
72021-12시흥시해면8632100
82021-12시흥시내수면4151
92021-12안산시해면22195145
집계년월시군명해면내수면구분명동력척수(척)동력톤수무동력척수(척)무동력톤수
142021-12연천군내수면321411
152021-12오산시내수면1041
162021-12용인시내수면661810
172021-12이천시내수면3241
182021-12파주시내수면895431
192021-12평택시해면2711100
202021-12평택시내수면753972
212021-12포천시내수면94258
222021-12화성시해면559206545
232021-12화성시내수면291810