Overview

Dataset statistics

Number of variables8
Number of observations100
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory6.7 KiB
Average record size in memory68.3 B

Variable types

Categorical6
Numeric2

Alerts

시도명 has constant value ""Constant
시군구명 has constant value ""Constant
행정동코드 is highly overall correlated with 기준일자 and 1 other fieldsHigh correlation
행정동명 is highly overall correlated with 기준일자 and 1 other fieldsHigh correlation
기준일자 is highly overall correlated with 행정동코드 and 2 other fieldsHigh correlation
성별 is highly overall correlated with 기준일자 and 1 other fieldsHigh correlation
연령대 is highly overall correlated with 성별High correlation
행정동코드 is highly imbalanced (53.1%)Imbalance
행정동명 is highly imbalanced (53.1%)Imbalance

Reproduction

Analysis started2023-12-10 13:15:59.544038
Analysis finished2023-12-10 13:16:01.119472
Duration1.58 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

행정동코드
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct2
Distinct (%)2.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
1111061500
90 
1111053000
10 

Length

Max length10
Median length10
Mean length10
Min length10

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row1111053000
2nd row1111053000
3rd row1111053000
4th row1111053000
5th row1111053000

Common Values

ValueCountFrequency (%)
1111061500 90
90.0%
1111053000 10
 
10.0%

Length

2023-12-10T22:16:01.266277image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T22:16:01.534178image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
1111061500 90
90.0%
1111053000 10
 
10.0%

시도명
Categorical

CONSTANT 

Distinct1
Distinct (%)1.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
서울특별시
100 

Length

Max length5
Median length5
Mean length5
Min length5

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
서울특별시 100
100.0%

Length

2023-12-10T22:16:01.730016image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T22:16:01.936359image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
서울특별시 100
100.0%

시군구명
Categorical

CONSTANT 

Distinct1
Distinct (%)1.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
종로구
100 

Length

Max length3
Median length3
Mean length3
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
종로구 100
100.0%

Length

2023-12-10T22:16:02.169061image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T22:16:02.310874image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
종로구 100
100.0%

행정동명
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct2
Distinct (%)2.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
종로1.2.3.4가동
90 
사직동
10 

Length

Max length11
Median length11
Mean length10.2
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
종로1.2.3.4가동 90
90.0%
사직동 10
 
10.0%

Length

2023-12-10T22:16:02.470804image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T22:16:02.638288image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
종로1.2.3.4가동 90
90.0%
사직동 10
 
10.0%

기준일자
Real number (ℝ)

HIGH CORRELATION 

Distinct18
Distinct (%)18.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean20201008
Minimum20200804
Maximum20201028
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.0 KiB
2023-12-10T22:16:02.799131image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum20200804
5-th percentile20200812
Q120201020
median20201023
Q320201025
95-th percentile20201027
Maximum20201028
Range224
Interquartile range (IQR)4.75

Descriptive statistics

Standard deviation54.852662
Coefficient of variation (CV)2.7153429 × 10-6
Kurtosis9.8332881
Mean20201008
Median Absolute Deviation (MAD)2
Skewness-3.4028321
Sum2.0201008 × 109
Variance3008.8145
MonotonicityNot monotonic
2023-12-10T22:16:03.030376image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=18)
ValueCountFrequency (%)
20201017 15
15.0%
20201024 15
15.0%
20201022 15
15.0%
20201023 13
13.0%
20201025 9
9.0%
20201027 9
9.0%
20201026 7
7.0%
20201021 6
 
6.0%
20200807 2
 
2.0%
20201018 1
 
1.0%
Other values (8) 8
8.0%
ValueCountFrequency (%)
20200804 1
 
1.0%
20200807 2
 
2.0%
20200808 1
 
1.0%
20200811 1
 
1.0%
20200812 1
 
1.0%
20200814 1
 
1.0%
20201013 1
 
1.0%
20201014 1
 
1.0%
20201017 15
15.0%
20201018 1
 
1.0%
ValueCountFrequency (%)
20201028 1
 
1.0%
20201027 9
9.0%
20201026 7
7.0%
20201025 9
9.0%
20201024 15
15.0%
20201023 13
13.0%
20201022 15
15.0%
20201021 6
 
6.0%
20201018 1
 
1.0%
20201017 15
15.0%

성별
Categorical

HIGH CORRELATION 

Distinct3
Distinct (%)3.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
M
73 
F
17 
X
10 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowM
2nd rowM
3rd rowM
4th rowX
5th rowX

Common Values

ValueCountFrequency (%)
M 73
73.0%
F 17
 
17.0%
X 10
 
10.0%

Length

2023-12-10T22:16:03.232805image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T22:16:03.398329image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
m 73
73.0%
f 17
 
17.0%
x 10
 
10.0%

연령대
Categorical

HIGH CORRELATION 

Distinct12
Distinct (%)12.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
30
12 
25
12 
35
10 
xx
10 
60
10 
Other values (7)
46 

Length

Max length2
Median length2
Mean length2
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row40
2nd row35
3rd row50
4th rowxx
5th rowxx

Common Values

ValueCountFrequency (%)
30 12
12.0%
25 12
12.0%
35 10
10.0%
xx 10
10.0%
60 10
10.0%
40 9
9.0%
55 8
8.0%
20 8
8.0%
50 7
7.0%
45 7
7.0%
Other values (2) 7
7.0%

Length

2023-12-10T22:16:03.569784image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
30 12
12.0%
25 12
12.0%
35 10
10.0%
xx 10
10.0%
60 10
10.0%
40 9
9.0%
55 8
8.0%
20 8
8.0%
50 7
7.0%
45 7
7.0%
Other values (2) 7
7.0%

소비인구(명)
Real number (ℝ)

Distinct23
Distinct (%)23.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean62.79157
Minimum22.479082
Maximum329.69321
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.0 KiB
2023-12-10T22:16:03.808290image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum22.479082
5-th percentile22.479082
Q129.97211
median44.958165
Q374.930275
95-th percentile172.71428
Maximum329.69321
Range307.21413
Interquartile range (IQR)44.958165

Descriptive statistics

Standard deviation55.837339
Coefficient of variation (CV)0.88924897
Kurtosis8.6043228
Mean62.79157
Median Absolute Deviation (MAD)22.479082
Skewness2.684951
Sum6279.157
Variance3117.8085
MonotonicityNot monotonic
2023-12-10T22:16:04.035650image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=23)
ValueCountFrequency (%)
22.479082395 18
18.0%
29.97210986 17
17.0%
37.465137325 13
13.0%
44.95816479 11
11.0%
52.451192255 6
 
6.0%
74.93027465 6
 
6.0%
89.91632958 4
 
4.0%
67.437247185 4
 
4.0%
82.423302115 4
 
4.0%
134.87449437 2
 
2.0%
Other values (13) 15
15.0%
ValueCountFrequency (%)
22.479082395 18
18.0%
29.97210986 17
17.0%
37.465137325 13
13.0%
44.95816479 11
11.0%
52.451192255 6
 
6.0%
59.94421972 2
 
2.0%
67.437247185 4
 
4.0%
74.93027465 6
 
6.0%
82.423302115 4
 
4.0%
89.91632958 4
 
4.0%
ValueCountFrequency (%)
329.69320846 1
1.0%
307.21412607 1
1.0%
239.77687888 1
1.0%
202.31174156 1
1.0%
179.83265916 1
1.0%
172.3396317 1
1.0%
149.8605493 1
1.0%
142.36752184 1
1.0%
134.87449437 2
2.0%
127.38146691 1
1.0%

Interactions

2023-12-10T22:16:00.263881image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T22:15:59.971363image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T22:16:00.413884image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T22:16:00.126520image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-10T22:16:04.204738image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
행정동코드행정동명기준일자성별연령대소비인구(명)
행정동코드1.0000.9960.9090.2670.4650.000
행정동명0.9961.0000.9090.2670.4650.000
기준일자0.9090.9091.0000.3070.5800.000
성별0.2670.2670.3071.0000.9400.000
연령대0.4650.4650.5800.9401.0000.000
소비인구(명)0.0000.0000.0000.0000.0001.000
2023-12-10T22:16:04.386691image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
행정동코드성별연령대행정동명
행정동코드1.0000.4320.3410.944
성별0.4321.0000.6890.432
연령대0.3410.6891.0000.341
행정동명0.9440.4320.3411.000
2023-12-10T22:16:04.548998image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
기준일자소비인구(명)행정동코드행정동명성별연령대
기준일자1.0000.0310.7550.7550.5480.487
소비인구(명)0.0311.0000.0000.0000.0000.000
행정동코드0.7550.0001.0000.9440.4320.341
행정동명0.7550.0000.9441.0000.4320.341
성별0.5480.0000.4320.4321.0000.689
연령대0.4870.0000.3410.3410.6891.000

Missing values

2023-12-10T22:16:00.783780image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-10T22:16:01.043696image/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

행정동코드시도명시군구명행정동명기준일자성별연령대소비인구(명)
01111053000서울특별시종로구사직동20201014M4029.97211
11111053000서울특별시종로구사직동20201028M3522.479082
21111053000서울특별시종로구사직동20200807M5022.479082
31111053000서울특별시종로구사직동20200804Xxx29.97211
41111053000서울특별시종로구사직동20200808Xxx22.479082
51111053000서울특별시종로구사직동20200807Xxx22.479082
61111053000서울특별시종로구사직동20200812Xxx29.97211
71111053000서울특별시종로구사직동20200814Xxx22.479082
81111053000서울특별시종로구사직동20201013M3029.97211
91111053000서울특별시종로구사직동20200811M6022.479082
행정동코드시도명시군구명행정동명기준일자성별연령대소비인구(명)
901111061500서울특별시종로구종로1.2.3.4가동20201022M3097.409357
911111061500서울특별시종로구종로1.2.3.4가동20201022M2582.423302
921111061500서울특별시종로구종로1.2.3.4가동20201022F3029.97211
931111061500서울특별시종로구종로1.2.3.4가동20201022F2537.465137
941111061500서울특별시종로구종로1.2.3.4가동20201026M2574.930275
951111061500서울특별시종로구종로1.2.3.4가동20201021M4529.97211
961111061500서울특별시종로구종로1.2.3.4가동20201021M3544.958165
971111061500서울특별시종로구종로1.2.3.4가동20201018F2044.958165
981111061500서울특별시종로구종로1.2.3.4가동20201025M5582.423302
991111061500서울특별시종로구종로1.2.3.4가동20201025M6067.437247