Overview

Dataset statistics

Number of variables5
Number of observations10000
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory498.0 KiB
Average record size in memory51.0 B

Variable types

Categorical1
Numeric3
Text1

Dataset

Description부산광역시_시간대_행정동별인구이동건수_20220630
Author부산광역시
URLhttp://data.busan.go.kr/dataSet/detail.nm?contentId=10&publicdatapk=15103328

Alerts

시간대 has 407 (4.1%) zerosZeros

Reproduction

Analysis started2023-12-10 17:06:47.997245
Analysis finished2023-12-10 17:06:51.182247
Duration3.19 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

기준연월
Categorical

Distinct3
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2022-05
3368 
2022-04
3333 
2022-06
3299 

Length

Max length7
Median length7
Mean length7
Min length7

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2022-04
2nd row2022-05
3rd row2022-05
4th row2022-06
5th row2022-06

Common Values

ValueCountFrequency (%)
2022-05 3368
33.7%
2022-04 3333
33.3%
2022-06 3299
33.0%

Length

2023-12-11T02:06:51.291460image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T02:06:51.450536image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2022-05 3368
33.7%
2022-04 3333
33.3%
2022-06 3299
33.0%

시간대
Real number (ℝ)

ZEROS 

Distinct24
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean11.4672
Minimum0
Maximum23
Zeros407
Zeros (%)4.1%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2023-12-11T02:06:51.637489image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile1
Q15
median12
Q317
95-th percentile22
Maximum23
Range23
Interquartile range (IQR)12

Descriptive statistics

Standard deviation6.9174352
Coefficient of variation (CV)0.60323664
Kurtosis-1.2064283
Mean11.4672
Median Absolute Deviation (MAD)6
Skewness0.0078133724
Sum114672
Variance47.850909
MonotonicityNot monotonic
2023-12-11T02:06:51.832082image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=24)
ValueCountFrequency (%)
13 437
 
4.4%
6 435
 
4.3%
18 434
 
4.3%
3 433
 
4.3%
1 432
 
4.3%
5 429
 
4.3%
12 428
 
4.3%
21 427
 
4.3%
8 422
 
4.2%
14 420
 
4.2%
Other values (14) 5703
57.0%
ValueCountFrequency (%)
0 407
4.1%
1 432
4.3%
2 400
4.0%
3 433
4.3%
4 414
4.1%
5 429
4.3%
6 435
4.3%
7 419
4.2%
8 422
4.2%
9 412
4.1%
ValueCountFrequency (%)
23 409
4.1%
22 413
4.1%
21 427
4.3%
20 409
4.1%
19 400
4.0%
18 434
4.3%
17 402
4.0%
16 411
4.1%
15 417
4.2%
14 420
4.2%

행정동코드
Real number (ℝ)

Distinct205
Distinct (%)2.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2.6326971 × 109
Minimum2.611051 × 109
Maximum2.671033 × 109
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2023-12-11T02:06:52.075933image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum2.611051 × 109
5-th percentile2.614052 × 109
Q12.62306 × 109
median2.632055 × 109
Q32.6410635 × 109
95-th percentile2.6530645 × 109
Maximum2.671033 × 109
Range59982000
Interquartile range (IQR)18003500

Descriptive statistics

Standard deviation13185787
Coefficient of variation (CV)0.0050084707
Kurtosis-0.094822025
Mean2.6326971 × 109
Median Absolute Deviation (MAD)9003000
Skewness0.42720225
Sum2.6326971 × 1013
Variance1.7386497 × 1014
MonotonicityNot monotonic
2023-12-11T02:06:52.385014image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
2623056000 59
 
0.6%
2650067000 58
 
0.6%
2620065000 58
 
0.6%
2638056200 58
 
0.6%
2638054000 58
 
0.6%
2647065000 56
 
0.6%
2632051000 56
 
0.6%
2629070000 56
 
0.6%
2641059100 56
 
0.6%
2620058500 56
 
0.6%
Other values (195) 9429
94.3%
ValueCountFrequency (%)
2611051000 45
0.4%
2611052000 50
0.5%
2611053000 39
0.4%
2611054500 50
0.5%
2611056000 39
0.4%
2611057000 51
0.5%
2611058000 50
0.5%
2611059000 48
0.5%
2611060000 46
0.5%
2614051000 55
0.5%
ValueCountFrequency (%)
2671033000 48
0.5%
2671031000 29
0.3%
2671025600 51
0.5%
2671025300 41
0.4%
2671025000 49
0.5%
2653068000 47
0.5%
2653067000 53
0.5%
2653066100 46
0.5%
2653066000 47
0.5%
2653065000 49
0.5%

행정동명
Text

Distinct205
Distinct (%)2.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2023-12-11T02:06:52.917139image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length5
Median length4
Mean length3.7831
Min length3

Characters and Unicode

Total characters37831
Distinct characters108
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

Unique0 ?
Unique (%)0.0%

Sample

1st row부곡1동
2nd row광복동
3rd row화명1동
4th row구포2동
5th row연산6동
ValueCountFrequency (%)
양정1동 59
 
0.6%
하단2동 58
 
0.6%
동삼1동 58
 
0.6%
괴정4동 58
 
0.6%
남천2동 58
 
0.6%
구포1동 56
 
0.6%
만덕1동 56
 
0.6%
문현3동 56
 
0.6%
연산1동 56
 
0.6%
부곡4동 56
 
0.6%
Other values (195) 9429
94.3%
2023-12-11T02:06:53.679314image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
동 10242
27.1%
1 2783
 
7.4%
2 2609
 
6.9%
3 1296
 
3.4%
대 770
 
2.0%
연 675
 
1.8%
천 629
 
1.7%
4 629
 
1.7%
정 606
 
1.6%
부 576
 
1.5%
Other values (98) 17016
45.0%

Most occurring categories

ValueCountFrequency (%)
Other Letter 30078
79.5%
Decimal Number 7753
 
20.5%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
동 10242
34.1%
대 770
 
2.6%
연 675
 
2.2%
천 629
 
2.1%
정 606
 
2.0%
부 576
 
1.9%
산 511
 
1.7%
장 489
 
1.6%
포 465
 
1.5%
신 448
 
1.5%
Other values (90) 14667
48.8%
Decimal Number
ValueCountFrequency (%)
1 2783
35.9%
2 2609
33.7%
3 1296
16.7%
4 629
 
8.1%
5 194
 
2.5%
6 144
 
1.9%
8 50
 
0.6%
9 48
 
0.6%

Most occurring scripts

ValueCountFrequency (%)
Hangul 30078
79.5%
Common 7753
 
20.5%

Most frequent character per script

Hangul
ValueCountFrequency (%)
동 10242
34.1%
대 770
 
2.6%
연 675
 
2.2%
천 629
 
2.1%
정 606
 
2.0%
부 576
 
1.9%
산 511
 
1.7%
장 489
 
1.6%
포 465
 
1.5%
신 448
 
1.5%
Other values (90) 14667
48.8%
Common
ValueCountFrequency (%)
1 2783
35.9%
2 2609
33.7%
3 1296
16.7%
4 629
 
8.1%
5 194
 
2.5%
6 144
 
1.9%
8 50
 
0.6%
9 48
 
0.6%

Most occurring blocks

ValueCountFrequency (%)
Hangul 30078
79.5%
ASCII 7753
 
20.5%

Most frequent character per block

Hangul
ValueCountFrequency (%)
동 10242
34.1%
대 770
 
2.6%
연 675
 
2.2%
천 629
 
2.1%
정 606
 
2.0%
부 576
 
1.9%
산 511
 
1.7%
장 489
 
1.6%
포 465
 
1.5%
신 448
 
1.5%
Other values (90) 14667
48.8%
ASCII
ValueCountFrequency (%)
1 2783
35.9%
2 2609
33.7%
3 1296
16.7%
4 629
 
8.1%
5 194
 
2.5%
6 144
 
1.9%
8 50
 
0.6%
9 48
 
0.6%

이동건수
Real number (ℝ)

Distinct9947
Distinct (%)99.5%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean449688.58
Minimum15392
Maximum2106346
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2023-12-11T02:06:53.928857image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum15392
5-th percentile100967.15
Q1221168.5
median387611.5
Q3599103.5
95-th percentile979886.5
Maximum2106346
Range2090954
Interquartile range (IQR)377935

Descriptive statistics

Standard deviation311055.34
Coefficient of variation (CV)0.69171278
Kurtosis4.6987578
Mean449688.58
Median Absolute Deviation (MAD)182623.5
Skewness1.7147978
Sum4.4968858 × 109
Variance9.6755423 × 1010
MonotonicityNot monotonic
2023-12-11T02:06:54.137024image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
166872 2
 
< 0.1%
331701 2
 
< 0.1%
308911 2
 
< 0.1%
166923 2
 
< 0.1%
188735 2
 
< 0.1%
79800 2
 
< 0.1%
499570 2
 
< 0.1%
143503 2
 
< 0.1%
143387 2
 
< 0.1%
335302 2
 
< 0.1%
Other values (9937) 9980
99.8%
ValueCountFrequency (%)
15392 1
< 0.1%
17882 1
< 0.1%
18877 1
< 0.1%
19366 1
< 0.1%
19615 1
< 0.1%
19825 1
< 0.1%
20541 1
< 0.1%
20660 1
< 0.1%
20709 1
< 0.1%
20968 1
< 0.1%
ValueCountFrequency (%)
2106346 1
< 0.1%
2094631 1
< 0.1%
2084226 1
< 0.1%
2077825 1
< 0.1%
2072407 1
< 0.1%
2072122 1
< 0.1%
2070693 1
< 0.1%
2062806 1
< 0.1%
2062645 1
< 0.1%
2062152 1
< 0.1%

Interactions

2023-12-11T02:06:50.365853image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T02:06:48.757784image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T02:06:49.718424image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T02:06:50.539285image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T02:06:49.320072image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T02:06:49.981824image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T02:06:50.745913image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T02:06:49.507987image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T02:06:50.181913image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-11T02:06:54.279607image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
기준연월시간대행정동코드이동건수
기준연월1.0000.0000.0000.021
시간대0.0001.0000.0000.108
행정동코드0.0000.0001.0000.535
이동건수0.0210.1080.5351.000
2023-12-11T02:06:54.438797image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
시간대행정동코드이동건수기준연월
시간대1.000-0.001-0.0040.000
행정동코드-0.0011.0000.2770.000
이동건수-0.0040.2771.0000.012
기준연월0.0000.0000.0121.000

Missing values

2023-12-11T02:06:50.955303image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-11T02:06:51.108388image/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

기준연월시간대행정동코드행정동명이동건수
35192022-0412641057000부곡1동221659
50502022-05202611057000광복동97265
73152022-0592632054100화명1동607686
121572022-0612632052000구포2동590377
140622022-0692647070000연산6동459203
96322022-05122653066000주례2동842715
32152022-0462638057100신평1동374234
91962022-05162650066000남천1동714392
85792022-0562641063500선두구동74188
74622022-05152632057100만덕1동277853
기준연월시간대행정동코드행정동명이동건수
66442022-05182626058000사직1동548484
84742022-05172641059000부곡3동499018
34392022-04122641052000서2동249949
46952022-0462653065000주례1동423380
21052022-04212629061000용당동243405
39182022-0472644055000가락동149344
113412022-0692623076000개금3동494501
100112022-06232611059000영주1동15392
85502022-0502641061000장전2동885788
76592022-0582635055200좌2동629011