Overview

Dataset statistics

Number of variables8
Number of observations62
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory4.3 KiB
Average record size in memory71.1 B

Variable types

Numeric4
Categorical3
Text1

Alerts

기준년도 has constant value ""Constant
기본키아이디 is highly overall correlated with 집계구역코드High correlation
전년도총인구수 is highly overall correlated with 당해년도총인구건수 and 1 other fieldsHigh correlation
당해년도총인구건수 is highly overall correlated with 전년도총인구수 and 1 other fieldsHigh correlation
집계구역코드 is highly overall correlated with 기본키아이디 and 2 other fieldsHigh correlation
기본키아이디 has unique valuesUnique

Reproduction

Analysis started2023-12-10 12:08:04.142325
Analysis finished2023-12-10 12:08:06.632942
Duration2.49 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

기본키아이디
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct62
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean31.5
Minimum1
Maximum62
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size690.0 B
2023-12-10T21:08:06.715717image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile4.05
Q116.25
median31.5
Q346.75
95-th percentile58.95
Maximum62
Range61
Interquartile range (IQR)30.5

Descriptive statistics

Standard deviation18.041619
Coefficient of variation (CV)0.5727498
Kurtosis-1.2
Mean31.5
Median Absolute Deviation (MAD)15.5
Skewness0
Sum1953
Variance325.5
MonotonicityStrictly increasing
2023-12-10T21:08:06.917433image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 1
 
1.6%
48 1
 
1.6%
35 1
 
1.6%
36 1
 
1.6%
37 1
 
1.6%
38 1
 
1.6%
39 1
 
1.6%
40 1
 
1.6%
41 1
 
1.6%
42 1
 
1.6%
Other values (52) 52
83.9%
ValueCountFrequency (%)
1 1
1.6%
2 1
1.6%
3 1
1.6%
4 1
1.6%
5 1
1.6%
6 1
1.6%
7 1
1.6%
8 1
1.6%
9 1
1.6%
10 1
1.6%
ValueCountFrequency (%)
62 1
1.6%
61 1
1.6%
60 1
1.6%
59 1
1.6%
58 1
1.6%
57 1
1.6%
56 1
1.6%
55 1
1.6%
54 1
1.6%
53 1
1.6%

기준년도
Categorical

CONSTANT 

Distinct1
Distinct (%)1.6%
Missing0
Missing (%)0.0%
Memory size628.0 B
2019
62 

Length

Max length4
Median length4
Mean length4
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2019
2nd row2019
3rd row2019
4th row2019
5th row2019

Common Values

ValueCountFrequency (%)
2019 62
100.0%

Length

2023-12-10T21:08:07.098402image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T21:08:07.214218image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2019 62
100.0%

지점id
Text

Distinct31
Distinct (%)50.0%
Missing0
Missing (%)0.0%
Memory size628.0 B
2023-12-10T21:08:07.411325image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length14
Median length14
Mean length14
Min length14

Characters and Unicode

Total characters868
Distinct characters14
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowA-0010-0391S-6
2nd rowA-0010-0391S-6
3rd rowA-0010-0728S-6
4th rowA-0010-0728S-6
5th rowA-0010-2583E-7
ValueCountFrequency (%)
a-0010-0391s-6 2
 
3.2%
a-0160-0058e-4 2
 
3.2%
a-0600-0636s-4 2
 
3.2%
a-0600-0547s-4 2
 
3.2%
a-0550-1837s-4 2
 
3.2%
a-0550-1490e-4 2
 
3.2%
a-0500-0701e-8 2
 
3.2%
a-0450-1129e-4 2
 
3.2%
a-0450-0703e-4 2
 
3.2%
a-0450-0557e-4 2
 
3.2%
Other values (21) 42
67.7%
2023-12-10T21:08:07.808691image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 202
23.3%
- 186
21.4%
A 62
 
7.1%
1 58
 
6.7%
4 56
 
6.5%
6 50
 
5.8%
5 50
 
5.8%
2 48
 
5.5%
E 40
 
4.6%
7 30
 
3.5%
Other values (4) 86
9.9%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 558
64.3%
Dash Punctuation 186
 
21.4%
Uppercase Letter 124
 
14.3%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 202
36.2%
1 58
 
10.4%
4 56
 
10.0%
6 50
 
9.0%
5 50
 
9.0%
2 48
 
8.6%
7 30
 
5.4%
8 28
 
5.0%
3 18
 
3.2%
9 18
 
3.2%
Uppercase Letter
ValueCountFrequency (%)
A 62
50.0%
E 40
32.3%
S 22
 
17.7%
Dash Punctuation
ValueCountFrequency (%)
- 186
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 744
85.7%
Latin 124
 
14.3%

Most frequent character per script

Common
ValueCountFrequency (%)
0 202
27.2%
- 186
25.0%
1 58
 
7.8%
4 56
 
7.5%
6 50
 
6.7%
5 50
 
6.7%
2 48
 
6.5%
7 30
 
4.0%
8 28
 
3.8%
3 18
 
2.4%
Latin
ValueCountFrequency (%)
A 62
50.0%
E 40
32.3%
S 22
 
17.7%

Most occurring blocks

ValueCountFrequency (%)
ASCII 868
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 202
23.3%
- 186
21.4%
A 62
 
7.1%
1 58
 
6.7%
4 56
 
6.5%
6 50
 
5.8%
5 50
 
5.8%
2 48
 
5.5%
E 40
 
4.6%
7 30
 
3.5%
Other values (4) 86
9.9%

집계구역코드
Categorical

HIGH CORRELATION 

Distinct30
Distinct (%)48.4%
Missing0
Missing (%)0.0%
Memory size628.0 B
경상남도 진주시 정촌면
 
4
울산광역시 울주군 삼남면
 
2
충청북도 옥천군 옥천읍
 
2
충청북도 옥천군 군북면
 
2
경상남도 사천시 축동면
 
2
Other values (25)
50 

Length

Max length14
Median length12
Mean length12
Min length11

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row울산광역시 울주군 삼남면
2nd row울산광역시 울주군 삼남면
3rd row경상북도 경주시 건천읍
4th row경상북도 경주시 건천읍
5th row충청북도 옥천군 옥천읍

Common Values

ValueCountFrequency (%)
경상남도 진주시 정촌면 4
 
6.5%
울산광역시 울주군 삼남면 2
 
3.2%
충청북도 옥천군 옥천읍 2
 
3.2%
충청북도 옥천군 군북면 2
 
3.2%
경상남도 사천시 축동면 2
 
3.2%
전라남도 담양군 고서면 2
 
3.2%
전라남도 담양군 봉산면 2
 
3.2%
경상남도 함양군 함양읍 2
 
3.2%
경상남도 거창군 남상면 2
 
3.2%
경상북도 고령군 성산면 2
 
3.2%
Other values (20) 40
64.5%

Length

2023-12-10T21:08:07.994285image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
경상북도 14
 
7.5%
경상남도 10
 
5.4%
충청북도 8
 
4.3%
전라북도 6
 
3.2%
전라남도 6
 
3.2%
남원시 6
 
3.2%
충청남도 4
 
2.2%
울산광역시 4
 
2.2%
정촌면 4
 
2.2%
옥천군 4
 
2.2%
Other values (53) 120
64.5%

성별
Categorical

Distinct2
Distinct (%)3.2%
Missing0
Missing (%)0.0%
Memory size628.0 B
남자
31 
여자
31 

Length

Max length2
Median length2
Mean length2
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row남자
2nd row여자
3rd row남자
4th row여자
5th row남자

Common Values

ValueCountFrequency (%)
남자 31
50.0%
여자 31
50.0%

Length

2023-12-10T21:08:08.154804image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T21:08:08.273683image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
남자 31
50.0%
여자 31
50.0%

전년도총인구수
Real number (ℝ)

HIGH CORRELATION 

Distinct59
Distinct (%)95.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2034.1935
Minimum264
Maximum8820
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size690.0 B
2023-12-10T21:08:08.394322image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum264
5-th percentile284.1
Q1498
median1291
Q32621
95-th percentile7325.2
Maximum8820
Range8556
Interquartile range (IQR)2123

Descriptive statistics

Standard deviation2194.6292
Coefficient of variation (CV)1.0788694
Kurtosis2.3716038
Mean2034.1935
Median Absolute Deviation (MAD)846
Skewness1.7300908
Sum126120
Variance4816397.5
MonotonicityNot monotonic
2023-12-10T21:08:08.569927image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1326 2
 
3.2%
1440 2
 
3.2%
622 2
 
3.2%
1908 1
 
1.6%
3826 1
 
1.6%
280 1
 
1.6%
264 1
 
1.6%
1484 1
 
1.6%
1550 1
 
1.6%
3648 1
 
1.6%
Other values (49) 49
79.0%
ValueCountFrequency (%)
264 1
1.6%
274 1
1.6%
280 1
1.6%
284 1
1.6%
286 1
1.6%
296 1
1.6%
320 1
1.6%
344 1
1.6%
366 1
1.6%
394 1
1.6%
ValueCountFrequency (%)
8820 1
1.6%
8754 1
1.6%
8004 1
1.6%
7374 1
1.6%
6398 1
1.6%
4912 1
1.6%
4904 1
1.6%
4786 1
1.6%
4602 1
1.6%
4594 1
1.6%

당해년도총인구건수
Real number (ℝ)

HIGH CORRELATION 

Distinct59
Distinct (%)95.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1903.1613
Minimum256
Maximum8710
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size690.0 B
2023-12-10T21:08:08.753196image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum256
5-th percentile288.1
Q1484.5
median1230
Q32271
95-th percentile6874.7
Maximum8710
Range8454
Interquartile range (IQR)1786.5

Descriptive statistics

Standard deviation2066.033
Coefficient of variation (CV)1.0855796
Kurtosis2.9803425
Mean1903.1613
Median Absolute Deviation (MAD)809
Skewness1.8331525
Sum117996
Variance4268492.3
MonotonicityNot monotonic
2023-12-10T21:08:08.907887image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1230 2
 
3.2%
1248 2
 
3.2%
352 2
 
3.2%
1742 1
 
1.6%
3686 1
 
1.6%
290 1
 
1.6%
1500 1
 
1.6%
1572 1
 
1.6%
2940 1
 
1.6%
2316 1
 
1.6%
Other values (49) 49
79.0%
ValueCountFrequency (%)
256 1
1.6%
278 1
1.6%
284 1
1.6%
288 1
1.6%
290 1
1.6%
298 1
1.6%
300 1
1.6%
352 2
3.2%
358 1
1.6%
400 1
1.6%
ValueCountFrequency (%)
8710 1
1.6%
8578 1
1.6%
7396 1
1.6%
6954 1
1.6%
5368 1
1.6%
4436 1
1.6%
4378 1
1.6%
4376 1
1.6%
4374 1
1.6%
4282 1
1.6%

전년대비 변경율
Real number (ℝ)

Distinct59
Distinct (%)95.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean-2.9803226
Minimum-30.25
Maximum4.76
Zeros0
Zeros (%)0.0%
Negative51
Negative (%)82.3%
Memory size690.0 B
2023-12-10T21:08:09.094586image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum-30.25
5-th percentile-9.126
Q1-4.85
median-2.015
Q3-0.955
95-th percentile3.0365
Maximum4.76
Range35.01
Interquartile range (IQR)3.895

Descriptive statistics

Standard deviation4.9126825
Coefficient of variation (CV)-1.6483727
Kurtosis14.827287
Mean-2.9803226
Median Absolute Deviation (MAD)1.95
Skewness-2.8457755
Sum-184.78
Variance24.134449
MonotonicityNot monotonic
2023-12-10T21:08:09.283318image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
-2.54 2
 
3.2%
-7.14 2
 
3.2%
-3.76 2
 
3.2%
-4.55 1
 
1.6%
-5.71 1
 
1.6%
-1.13 1
 
1.6%
1.0 1
 
1.6%
-0.97 1
 
1.6%
-1.47 1
 
1.6%
-9.14 1
 
1.6%
Other values (49) 49
79.0%
ValueCountFrequency (%)
-30.25 1
1.6%
-10.75 1
1.6%
-10.65 1
1.6%
-9.14 1
1.6%
-8.86 1
1.6%
-8.75 1
1.6%
-7.14 2
3.2%
-6.77 1
1.6%
-5.75 1
1.6%
-5.71 1
1.6%
ValueCountFrequency (%)
4.76 1
1.6%
4.69 1
1.6%
4.53 1
1.6%
3.11 1
1.6%
1.64 1
1.6%
1.46 1
1.6%
1.41 1
1.6%
1.33 1
1.6%
1.0 1
1.6%
0.7 1
1.6%

Interactions

2023-12-10T21:08:05.944603image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T21:08:04.446415image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T21:08:05.120499image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T21:08:05.499602image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T21:08:06.041356image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T21:08:04.835144image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T21:08:05.218337image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T21:08:05.640776image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T21:08:06.130945image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T21:08:04.927596image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T21:08:05.309483image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T21:08:05.763835image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T21:08:06.220877image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T21:08:05.020265image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T21:08:05.393068image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T21:08:05.851410image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-10T21:08:09.426358image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
기본키아이디지점id집계구역코드성별전년도총인구수당해년도총인구건수전년대비 변경율
기본키아이디1.0000.9730.9870.0000.5370.5140.264
지점id0.9731.0001.0000.0000.9380.9260.717
집계구역코드0.9871.0001.0000.0000.9430.9320.780
성별0.0000.0000.0001.0000.0000.0000.000
전년도총인구수0.5370.9380.9430.0001.0000.9970.464
당해년도총인구건수0.5140.9260.9320.0000.9971.0000.426
전년대비 변경율0.2640.7170.7800.0000.4640.4261.000
2023-12-10T21:08:09.565853image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
집계구역코드성별
집계구역코드1.0000.000
성별0.0001.000
2023-12-10T21:08:09.671029image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
기본키아이디전년도총인구수당해년도총인구건수전년대비 변경율집계구역코드성별
기본키아이디1.000-0.120-0.1260.0490.6420.000
전년도총인구수-0.1201.0000.993-0.2490.5660.000
당해년도총인구건수-0.1260.9931.000-0.1830.5400.000
전년대비 변경율0.049-0.249-0.1831.0000.3240.000
집계구역코드0.6420.5660.5400.3241.0000.000
성별0.0000.0000.0000.0000.0001.000

Missing values

2023-12-10T21:08:06.378271image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-10T21:08:06.567908image/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

기본키아이디기준년도지점id집계구역코드성별전년도총인구수당해년도총인구건수전년대비 변경율
012019A-0010-0391S-6울산광역시 울주군 삼남면남자19081742-4.55
122019A-0010-0391S-6울산광역시 울주군 삼남면여자20141810-5.33
232019A-0010-0728S-6경상북도 경주시 건천읍남자46024374-2.54
342019A-0010-0728S-6경상북도 경주시 건천읍여자45944376-2.43
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