Overview

Dataset statistics

Number of variables5
Number of observations27
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory1.3 KiB
Average record size in memory47.9 B

Variable types

Text1
Numeric3
DateTime1

Dataset

Description서울특별시 송파구의 법정동별 영유아 현황 데이터입니다. 법정동별 영유아(6세미만 미취학 아동) 현황 데이터를 포함하고있습니다.
URLhttps://www.data.go.kr/data/15036280/fileData.do

Alerts

기준일자 has constant value ""Constant
영유아자녀 가구수 is highly overall correlated with 영유아 남아수 and 1 other fieldsHigh correlation
영유아 남아수 is highly overall correlated with 영유아자녀 가구수 and 1 other fieldsHigh correlation
영유아 여아수 is highly overall correlated with 영유아자녀 가구수 and 1 other fieldsHigh correlation
읍면동(법정동) has unique valuesUnique
영유아자녀 가구수 has unique valuesUnique
영유아 여아수 has unique valuesUnique

Reproduction

Analysis started2023-12-12 19:14:05.478572
Analysis finished2023-12-12 19:14:07.073888
Duration1.6 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

읍면동(법정동)
Text

UNIQUE 

Distinct27
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size348.0 B
2023-12-13T04:14:07.244678image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length13
Median length13
Mean length12.925926
Min length12

Characters and Unicode

Total characters349
Distinct characters36
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique27 ?
Unique (%)100.0%

Sample

1st row풍납1동
2nd row풍납2동
3rd row거여1동
4th row거여2동
5th row마천1동
ValueCountFrequency (%)
풍납1동 1
 
3.7%
가락본동 1
 
3.7%
잠실6동 1
 
3.7%
잠실4동 1
 
3.7%
잠실3동 1
 
3.7%
잠실2동 1
 
3.7%
잠실본동 1
 
3.7%
위례동 1
 
3.7%
장지동 1
 
3.7%
문정2동 1
 
3.7%
Other values (17) 17
63.0%
2023-12-13T04:14:07.669903image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
247
70.8%
동 27
 
7.7%
2 8
 
2.3%
1 7
 
2.0%
잠 6
 
1.7%
실 6
 
1.7%
가 3
 
0.9%
락 3
 
0.9%
문 2
 
0.6%
납 2
 
0.6%
Other values (26) 38
 
10.9%

Most occurring categories

ValueCountFrequency (%)
Space Separator 247
70.8%
Other Letter 83
 
23.8%
Decimal Number 19
 
5.4%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
동 27
32.5%
잠 6
 
7.2%
실 6
 
7.2%
가 3
 
3.6%
락 3
 
3.6%
문 2
 
2.4%
납 2
 
2.4%
본 2
 
2.4%
파 2
 
2.4%
송 2
 
2.4%
Other values (19) 28
33.7%
Decimal Number
ValueCountFrequency (%)
2 8
42.1%
1 7
36.8%
6 1
 
5.3%
3 1
 
5.3%
4 1
 
5.3%
7 1
 
5.3%
Space Separator
ValueCountFrequency (%)
247
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 266
76.2%
Hangul 83
 
23.8%

Most frequent character per script

Hangul
ValueCountFrequency (%)
동 27
32.5%
잠 6
 
7.2%
실 6
 
7.2%
가 3
 
3.6%
락 3
 
3.6%
문 2
 
2.4%
납 2
 
2.4%
본 2
 
2.4%
파 2
 
2.4%
송 2
 
2.4%
Other values (19) 28
33.7%
Common
ValueCountFrequency (%)
247
92.9%
2 8
 
3.0%
1 7
 
2.6%
6 1
 
0.4%
3 1
 
0.4%
4 1
 
0.4%
7 1
 
0.4%

Most occurring blocks

ValueCountFrequency (%)
ASCII 266
76.2%
Hangul 83
 
23.8%

Most frequent character per block

ASCII
ValueCountFrequency (%)
247
92.9%
2 8
 
3.0%
1 7
 
2.6%
6 1
 
0.4%
3 1
 
0.4%
4 1
 
0.4%
7 1
 
0.4%
Hangul
ValueCountFrequency (%)
동 27
32.5%
잠 6
 
7.2%
실 6
 
7.2%
가 3
 
3.6%
락 3
 
3.6%
문 2
 
2.4%
납 2
 
2.4%
본 2
 
2.4%
파 2
 
2.4%
송 2
 
2.4%
Other values (19) 28
33.7%

영유아자녀 가구수
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct27
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean905.33333
Minimum259
Maximum2244
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size375.0 B
2023-12-13T04:14:07.827204image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum259
5-th percentile315.2
Q1492
median795
Q31291.5
95-th percentile1622.1
Maximum2244
Range1985
Interquartile range (IQR)799.5

Descriptive statistics

Standard deviation487.48475
Coefficient of variation (CV)0.53845886
Kurtosis0.55645805
Mean905.33333
Median Absolute Deviation (MAD)345
Skewness0.89119028
Sum24444
Variance237641.38
MonotonicityNot monotonic
2023-12-13T04:14:08.279063image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=27)
ValueCountFrequency (%)
395 1
 
3.7%
928 1
 
3.7%
259 1
 
3.7%
620 1
 
3.7%
1432 1
 
3.7%
1440 1
 
3.7%
1674 1
 
3.7%
723 1
 
3.7%
2244 1
 
3.7%
1418 1
 
3.7%
Other values (17) 17
63.0%
ValueCountFrequency (%)
259 1
3.7%
281 1
3.7%
395 1
3.7%
416 1
3.7%
441 1
3.7%
450 1
3.7%
459 1
3.7%
525 1
3.7%
620 1
3.7%
707 1
3.7%
ValueCountFrequency (%)
2244 1
3.7%
1674 1
3.7%
1501 1
3.7%
1440 1
3.7%
1432 1
3.7%
1418 1
3.7%
1386 1
3.7%
1197 1
3.7%
969 1
3.7%
928 1
3.7%

영유아 남아수
Real number (ℝ)

HIGH CORRELATION 

Distinct26
Distinct (%)96.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean740.14815
Minimum211
Maximum1933
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size375.0 B
2023-12-13T04:14:08.424909image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum211
5-th percentile251
Q1414
median634
Q31048.5
95-th percentile1411.8
Maximum1933
Range1722
Interquartile range (IQR)634.5

Descriptive statistics

Standard deviation418.7053
Coefficient of variation (CV)0.56570472
Kurtosis1.0206473
Mean740.14815
Median Absolute Deviation (MAD)236
Skewness1.1101327
Sum19984
Variance175314.13
MonotonicityNot monotonic
2023-12-13T04:14:08.573385image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=26)
ValueCountFrequency (%)
751 2
 
7.4%
321 1
 
3.7%
1117 1
 
3.7%
211 1
 
3.7%
500 1
 
3.7%
1205 1
 
3.7%
1201 1
 
3.7%
1464 1
 
3.7%
554 1
 
3.7%
1933 1
 
3.7%
Other values (16) 16
59.3%
ValueCountFrequency (%)
211 1
3.7%
221 1
3.7%
321 1
3.7%
361 1
3.7%
389 1
3.7%
398 1
3.7%
413 1
3.7%
415 1
3.7%
500 1
3.7%
554 1
3.7%
ValueCountFrequency (%)
1933 1
3.7%
1464 1
3.7%
1290 1
3.7%
1205 1
3.7%
1201 1
3.7%
1132 1
3.7%
1117 1
3.7%
980 1
3.7%
751 2
7.4%
701 1
3.7%

영유아 여아수
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct27
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean695.51852
Minimum196
Maximum1878
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size375.0 B
2023-12-13T04:14:08.689595image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum196
5-th percentile255.4
Q1400
median581
Q3952
95-th percentile1363.5
Maximum1878
Range1682
Interquartile range (IQR)552

Descriptive statistics

Standard deviation402.2991
Coefficient of variation (CV)0.57841609
Kurtosis1.487677
Mean695.51852
Median Absolute Deviation (MAD)209
Skewness1.2481008
Sum18779
Variance161844.57
MonotonicityNot monotonic
2023-12-13T04:14:08.806289image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=27)
ValueCountFrequency (%)
282 1
 
3.7%
680 1
 
3.7%
196 1
 
3.7%
474 1
 
3.7%
1130 1
 
3.7%
1157 1
 
3.7%
1452 1
 
3.7%
497 1
 
3.7%
1878 1
 
3.7%
1077 1
 
3.7%
Other values (17) 17
63.0%
ValueCountFrequency (%)
196 1
3.7%
244 1
3.7%
282 1
3.7%
352 1
3.7%
353 1
3.7%
372 1
3.7%
393 1
3.7%
407 1
3.7%
474 1
3.7%
492 1
3.7%
ValueCountFrequency (%)
1878 1
3.7%
1452 1
3.7%
1157 1
3.7%
1144 1
3.7%
1130 1
3.7%
1077 1
3.7%
1004 1
3.7%
900 1
3.7%
713 1
3.7%
694 1
3.7%

기준일자
Date

CONSTANT 

Distinct1
Distinct (%)3.7%
Missing0
Missing (%)0.0%
Memory size348.0 B
Minimum2023-06-30 00:00:00
Maximum2023-06-30 00:00:00
2023-12-13T04:14:08.912436image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T04:14:09.001431image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=1)

Interactions

2023-12-13T04:14:06.475088image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T04:14:05.642920image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T04:14:06.068931image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T04:14:06.611171image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T04:14:05.806343image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T04:14:06.219394image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T04:14:06.735759image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T04:14:05.945863image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T04:14:06.348654image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-13T04:14:09.064565image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
읍면동(법정동)영유아자녀 가구수영유아 남아수영유아 여아수
읍면동(법정동)1.0001.0001.0001.000
영유아자녀 가구수1.0001.0000.9910.876
영유아 남아수1.0000.9911.0000.868
영유아 여아수1.0000.8760.8681.000
2023-12-13T04:14:09.187294image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
영유아자녀 가구수영유아 남아수영유아 여아수
영유아자녀 가구수1.0000.9930.995
영유아 남아수0.9931.0000.989
영유아 여아수0.9950.9891.000

Missing values

2023-12-13T04:14:06.889387image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-13T04:14:07.011143image/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

읍면동(법정동)영유아자녀 가구수영유아 남아수영유아 여아수기준일자
0풍납1동3953212822023-06-30
1풍납2동9287516802023-06-30
2거여1동2812212442023-06-30
3거여2동5254134072023-06-30
4마천1동4504153932023-06-30
5마천2동4413613722023-06-30
6방이1동4593893532023-06-30
7방이2동7285774942023-06-30
8오륜동4163983522023-06-30
9오금동1501129011442023-06-30
읍면동(법정동)영유아자녀 가구수영유아 남아수영유아 여아수기준일자
17문정1동7075604922023-06-30
18문정2동8606566282023-06-30
19장지동1418113210772023-06-30
20위례동2244193318782023-06-30
21잠실본동7235544972023-06-30
22잠실2동1674146414522023-06-30
23잠실3동1440120111572023-06-30
24잠실4동1432120511302023-06-30
25잠실6동6205004742023-06-30
26잠실7동2592111962023-06-30