Overview

Dataset statistics

Number of variables8
Number of observations93
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory6.5 KiB
Average record size in memory71.4 B

Variable types

Categorical6
Numeric2

Alerts

기준년월일 has constant value ""Constant
시간대구분코드 has constant value ""Constant
장기외국인수 has constant value ""Constant
단기외국인수 has constant value ""Constant
성별구분코드 is highly overall correlated with 연령대구분코드High correlation
연령대구분코드 is highly overall correlated with 성별구분코드High correlation
행정동코드 has unique valuesUnique

Reproduction

Analysis started2023-12-10 06:40:00.339644
Analysis finished2023-12-10 06:40:01.465222
Duration1.13 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

기준년월일
Categorical

CONSTANT 

Distinct1
Distinct (%)1.1%
Missing0
Missing (%)0.0%
Memory size876.0 B
20201022
93 

Length

Max length8
Median length8
Mean length8
Min length8

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row20201022
2nd row20201022
3rd row20201022
4th row20201022
5th row20201022

Common Values

ValueCountFrequency (%)
20201022 93
100.0%

Length

2023-12-10T15:40:01.548666image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T15:40:01.672711image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
20201022 93
100.0%

시간대구분코드
Categorical

CONSTANT 

Distinct1
Distinct (%)1.1%
Missing0
Missing (%)0.0%
Memory size876.0 B
0
93 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 93
100.0%

Length

2023-12-10T15:40:01.810776image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T15:40:01.937568image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 93
100.0%

성별구분코드
Categorical

HIGH CORRELATION 

Distinct2
Distinct (%)2.2%
Missing0
Missing (%)0.0%
Memory size876.0 B
F
65 
M
28 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
F 65
69.9%
M 28
30.1%

Length

2023-12-10T15:40:02.100005image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T15:40:02.246585image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
f 65
69.9%
m 28
30.1%

연령대구분코드
Categorical

HIGH CORRELATION 

Distinct13
Distinct (%)14.0%
Missing0
Missing (%)0.0%
Memory size876.0 B
age_10
13 
age_15
13 
age_70
12 
age_20
11 
age_25
9 
Other values (8)
35 

Length

Max length6
Median length6
Mean length6
Min length6

Unique

Unique1 ?
Unique (%)1.1%

Sample

1st rowage_10
2nd rowage_10
3rd rowage_10
4th rowage_10
5th rowage_10

Common Values

ValueCountFrequency (%)
age_10 13
14.0%
age_15 13
14.0%
age_70 12
12.9%
age_20 11
11.8%
age_25 9
9.7%
age_60 7
7.5%
age_50 6
6.5%
age_55 6
6.5%
age_30 5
 
5.4%
age_35 5
 
5.4%
Other values (3) 6
6.5%

Length

2023-12-10T15:40:02.379293image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
age_10 13
14.0%
age_15 13
14.0%
age_70 12
12.9%
age_20 11
11.8%
age_25 9
9.7%
age_60 7
7.5%
age_50 6
6.5%
age_55 6
6.5%
age_30 5
 
5.4%
age_35 5
 
5.4%
Other values (3) 6
6.5%

행정동코드
Real number (ℝ)

UNIQUE 

Distinct93
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean11463850
Minimum11110690
Maximum11740690
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size969.0 B
2023-12-10T15:40:02.525697image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum11110690
5-th percentile11140676
Q111350570
median11470590
Q311620775
95-th percentile11740544
Maximum11740690
Range630000
Interquartile range (IQR)270205

Descriptive statistics

Standard deviation188035.66
Coefficient of variation (CV)0.016402489
Kurtosis-1.1237389
Mean11463850
Median Absolute Deviation (MAD)150095
Skewness-0.20293358
Sum1.066138 × 109
Variance3.5357411 × 1010
MonotonicityNot monotonic
2023-12-10T15:40:02.741993image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
11200590 1
 
1.1%
11110690 1
 
1.1%
11440700 1
 
1.1%
11350624 1
 
1.1%
11170700 1
 
1.1%
11140670 1
 
1.1%
11740640 1
 
1.1%
11710561 1
 
1.1%
11470640 1
 
1.1%
11410720 1
 
1.1%
Other values (83) 83
89.2%
ValueCountFrequency (%)
11110690 1
1.1%
11140520 1
1.1%
11140570 1
1.1%
11140580 1
1.1%
11140670 1
1.1%
11140680 1
1.1%
11170510 1
1.1%
11170625 1
1.1%
11170700 1
1.1%
11200540 1
1.1%
ValueCountFrequency (%)
11740690 1
1.1%
11740650 1
1.1%
11740640 1
1.1%
11740590 1
1.1%
11740550 1
1.1%
11740540 1
1.1%
11710710 1
1.1%
11710610 1
1.1%
11710600 1
1.1%
11710562 1
1.1%

내국인수
Real number (ℝ)

Distinct78
Distinct (%)83.9%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean204.92473
Minimum8
Maximum567
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size969.0 B
2023-12-10T15:40:03.008963image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum8
5-th percentile37.8
Q1125
median174
Q3274
95-th percentile504
Maximum567
Range559
Interquartile range (IQR)149

Descriptive statistics

Standard deviation131.45186
Coefficient of variation (CV)0.64146412
Kurtosis0.84645809
Mean204.92473
Median Absolute Deviation (MAD)73
Skewness1.0142743
Sum19058
Variance17279.592
MonotonicityNot monotonic
2023-12-10T15:40:03.231183image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
241 3
 
3.2%
140 3
 
3.2%
171 2
 
2.2%
293 2
 
2.2%
217 2
 
2.2%
104 2
 
2.2%
156 2
 
2.2%
248 2
 
2.2%
182 2
 
2.2%
98 2
 
2.2%
Other values (68) 71
76.3%
ValueCountFrequency (%)
8 1
1.1%
10 1
1.1%
14 1
1.1%
15 1
1.1%
36 1
1.1%
39 1
1.1%
40 1
1.1%
43 1
1.1%
46 1
1.1%
53 1
1.1%
ValueCountFrequency (%)
567 1
1.1%
565 1
1.1%
559 1
1.1%
523 1
1.1%
516 1
1.1%
496 1
1.1%
470 1
1.1%
432 1
1.1%
415 1
1.1%
379 1
1.1%

장기외국인수
Categorical

CONSTANT 

Distinct1
Distinct (%)1.1%
Missing0
Missing (%)0.0%
Memory size876.0 B
0
93 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 93
100.0%

Length

2023-12-10T15:40:03.441916image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T15:40:03.602948image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 93
100.0%

단기외국인수
Categorical

CONSTANT 

Distinct1
Distinct (%)1.1%
Missing0
Missing (%)0.0%
Memory size876.0 B
0
93 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 93
100.0%

Length

2023-12-10T15:40:03.776987image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T15:40:03.932010image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 93
100.0%

Interactions

2023-12-10T15:40:00.905926image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T15:40:00.620591image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T15:40:01.055393image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T15:40:00.771515image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-10T15:40:04.007620image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
성별구분코드연령대구분코드행정동코드내국인수
성별구분코드1.0000.6700.1040.000
연령대구분코드0.6701.0000.0000.626
행정동코드0.1040.0001.0000.000
내국인수0.0000.6260.0001.000
2023-12-10T15:40:04.161252image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연령대구분코드성별구분코드
연령대구분코드1.0000.593
성별구분코드0.5931.000
2023-12-10T15:40:04.290012image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
행정동코드내국인수성별구분코드연령대구분코드
행정동코드1.0000.2230.0000.000
내국인수0.2231.0000.0000.311
성별구분코드0.0000.0001.0000.593
연령대구분코드0.0000.3110.5931.000

Missing values

2023-12-10T15:40:01.225788image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-10T15:40:01.396113image/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

기준년월일시간대구분코드성별구분코드연령대구분코드행정동코드내국인수장기외국인수단기외국인수
0202010220Fage_10112005903900
1202010220Fage_10112157103600
2202010220Fage_10112305365300
3202010220Fage_10115006209400
4202010220Fage_10115456305400
5202010220Fage_101156054018000
6202010220Fage_151120054014300
7202010220Fage_151135059519400
8202010220Fage_151135063024100
9202010220Fage_151138062524800
기준년월일시간대구분코드성별구분코드연령대구분코드행정동코드내국인수장기외국인수단기외국인수
83202010220Mage_201156072017000
84202010220Mage_201165065221200
85202010220Mage_201171060024100
86202010220Mage_251114052012500
87202010220Mage_251120072022100
88202010220Mage_251141052017200
89202010220Mage_251159056051600
90202010220Mage_251162077530300
91202010220Mage_251165065155900
92202010220Mage_251168073024500