Overview

Dataset statistics

Number of variables8
Number of observations22
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory1.7 KiB
Average record size in memory77.0 B

Variable types

Text1
Categorical5
Numeric2

Dataset

Description인천광역시 부평구 어린이집 현황 데이터는 부평구 동별 어린이집 구분(국공립, 사회복지법인, 민간, 가정, 직장 등) 정보를 제공하고 있습니다.
Author인천광역시 부평구
URLhttps://data.incheon.go.kr/findData/publicDataDetail?dataId=15118085&srcSe=7661IVAWM27C61E190

Alerts

법인_단체 등 is highly imbalanced (73.3%)Imbalance
협동 is highly imbalanced (56.1%)Imbalance
동별 has unique valuesUnique
민간 has 1 (4.5%) zerosZeros
가정 has 2 (9.1%) zerosZeros

Reproduction

Analysis started2024-01-28 08:18:37.403031
Analysis finished2024-01-28 08:18:38.167915
Duration0.76 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

동별
Text

UNIQUE 

Distinct22
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size308.0 B
2024-01-28T17:18:38.217333image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length6
Median length6
Mean length5.9545455
Min length5

Characters and Unicode

Total characters131
Distinct characters21
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

Unique22 ?
Unique (%)100.0%

Sample

1st row부평 1 동
2nd row부평 2 동
3rd row부평 3 동
4th row부평 4 동
5th row부평 5 동
ValueCountFrequency (%)
동 22
33.3%
1 7
 
10.6%
2 7
 
10.6%
부평 6
 
9.1%
산곡 4
 
6.1%
3 3
 
4.5%
부개 3
 
4.5%
4 2
 
3.0%
청천 2
 
3.0%
갈산 2
 
3.0%
Other values (6) 8
 
12.1%
2024-01-28T17:18:38.443952image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
44
33.6%
동 22
16.8%
부 9
 
6.9%
산 8
 
6.1%
1 7
 
5.3%
2 7
 
5.3%
평 6
 
4.6%
곡 4
 
3.1%
3 3
 
2.3%
개 3
 
2.3%
Other values (11) 18
13.7%

Most occurring categories

ValueCountFrequency (%)
Other Letter 66
50.4%
Space Separator 44
33.6%
Decimal Number 21
 
16.0%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
동 22
33.3%
부 9
13.6%
산 8
 
12.1%
평 6
 
9.1%
곡 4
 
6.1%
개 3
 
4.5%
갈 2
 
3.0%
십 2
 
3.0%
삼 2
 
3.0%
청 2
 
3.0%
Other values (4) 6
 
9.1%
Decimal Number
ValueCountFrequency (%)
1 7
33.3%
2 7
33.3%
3 3
14.3%
4 2
 
9.5%
6 1
 
4.8%
5 1
 
4.8%
Space Separator
ValueCountFrequency (%)
44
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 66
50.4%
Common 65
49.6%

Most frequent character per script

Hangul
ValueCountFrequency (%)
동 22
33.3%
부 9
13.6%
산 8
 
12.1%
평 6
 
9.1%
곡 4
 
6.1%
개 3
 
4.5%
갈 2
 
3.0%
십 2
 
3.0%
삼 2
 
3.0%
청 2
 
3.0%
Other values (4) 6
 
9.1%
Common
ValueCountFrequency (%)
44
67.7%
1 7
 
10.8%
2 7
 
10.8%
3 3
 
4.6%
4 2
 
3.1%
6 1
 
1.5%
5 1
 
1.5%

Most occurring blocks

ValueCountFrequency (%)
Hangul 66
50.4%
ASCII 65
49.6%

Most frequent character per block

ASCII
ValueCountFrequency (%)
44
67.7%
1 7
 
10.8%
2 7
 
10.8%
3 3
 
4.6%
4 2
 
3.1%
6 1
 
1.5%
5 1
 
1.5%
Hangul
ValueCountFrequency (%)
동 22
33.3%
부 9
13.6%
산 8
 
12.1%
평 6
 
9.1%
곡 4
 
6.1%
개 3
 
4.5%
갈 2
 
3.0%
십 2
 
3.0%
삼 2
 
3.0%
청 2
 
3.0%
Other values (4) 6
 
9.1%

국공립
Categorical

Distinct4
Distinct (%)18.2%
Missing0
Missing (%)0.0%
Memory size308.0 B
1
9 
0
5 
2
4 
3
4 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row1
4th row2
5th row0

Common Values

ValueCountFrequency (%)
1 9
40.9%
0 5
22.7%
2 4
18.2%
3 4
18.2%

Length

2024-01-28T17:18:38.553527image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-01-28T17:18:38.643501image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
1 9
40.9%
0 5
22.7%
2 4
18.2%
3 4
18.2%

사회복지법인
Categorical

Distinct2
Distinct (%)9.1%
Missing0
Missing (%)0.0%
Memory size308.0 B
0
18 
1
4 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row1
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 18
81.8%
1 4
 
18.2%

Length

2024-01-28T17:18:38.735730image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-01-28T17:18:38.824188image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 18
81.8%
1 4
 
18.2%

법인_단체 등
Categorical

IMBALANCE 

Distinct2
Distinct (%)9.1%
Missing0
Missing (%)0.0%
Memory size308.0 B
0
21 
2
 
1

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique1 ?
Unique (%)4.5%

Sample

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

Common Values

ValueCountFrequency (%)
0 21
95.5%
2 1
 
4.5%

Length

2024-01-28T17:18:38.908170image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-01-28T17:18:38.994741image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 21
95.5%
2 1
 
4.5%

민간
Real number (ℝ)

ZEROS 

Distinct8
Distinct (%)36.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean4.8181818
Minimum0
Maximum10
Zeros1
Zeros (%)4.5%
Negative0
Negative (%)0.0%
Memory size330.0 B
2024-01-28T17:18:39.066300image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile2
Q12.25
median4
Q37
95-th percentile9
Maximum10
Range10
Interquartile range (IQR)4.75

Descriptive statistics

Standard deviation2.8889999
Coefficient of variation (CV)0.59960375
Kurtosis-1.1047509
Mean4.8181818
Median Absolute Deviation (MAD)2
Skewness0.31658934
Sum106
Variance8.3463203
MonotonicityNot monotonic
2024-01-28T17:18:39.155464image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=8)
ValueCountFrequency (%)
2 5
22.7%
3 4
18.2%
6 3
13.6%
9 3
13.6%
7 3
13.6%
4 2
 
9.1%
0 1
 
4.5%
10 1
 
4.5%
ValueCountFrequency (%)
0 1
 
4.5%
2 5
22.7%
3 4
18.2%
4 2
 
9.1%
6 3
13.6%
7 3
13.6%
9 3
13.6%
10 1
 
4.5%
ValueCountFrequency (%)
10 1
 
4.5%
9 3
13.6%
7 3
13.6%
6 3
13.6%
4 2
 
9.1%
3 4
18.2%
2 5
22.7%
0 1
 
4.5%

협동
Categorical

IMBALANCE 

Distinct2
Distinct (%)9.1%
Missing0
Missing (%)0.0%
Memory size308.0 B
0
20 
1
 
2

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row1
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 20
90.9%
1 2
 
9.1%

Length

2024-01-28T17:18:39.251133image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-01-28T17:18:39.332080image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 20
90.9%
1 2
 
9.1%

직장
Categorical

Distinct3
Distinct (%)13.6%
Missing0
Missing (%)0.0%
Memory size308.0 B
0
14 
1
7 
3
 
1

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique1 ?
Unique (%)4.5%

Sample

1st row0
2nd row0
3rd row0
4th row1
5th row1

Common Values

ValueCountFrequency (%)
0 14
63.6%
1 7
31.8%
3 1
 
4.5%

Length

2024-01-28T17:18:39.429593image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-01-28T17:18:39.525918image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 14
63.6%
1 7
31.8%
3 1
 
4.5%

가정
Real number (ℝ)

ZEROS 

Distinct13
Distinct (%)59.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean6.1363636
Minimum0
Maximum15
Zeros2
Zeros (%)9.1%
Negative0
Negative (%)0.0%
Memory size330.0 B
2024-01-28T17:18:39.616789image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0.05
Q12
median5
Q310.75
95-th percentile13.95
Maximum15
Range15
Interquartile range (IQR)8.75

Descriptive statistics

Standard deviation5.0643051
Coefficient of variation (CV)0.82529416
Kurtosis-1.3346348
Mean6.1363636
Median Absolute Deviation (MAD)4
Skewness0.45192764
Sum135
Variance25.647186
MonotonicityNot monotonic
2024-01-28T17:18:39.709305image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=13)
ValueCountFrequency (%)
1 3
13.6%
5 3
13.6%
3 3
13.6%
2 2
9.1%
0 2
9.1%
13 2
9.1%
14 1
 
4.5%
12 1
 
4.5%
9 1
 
4.5%
11 1
 
4.5%
Other values (3) 3
13.6%
ValueCountFrequency (%)
0 2
9.1%
1 3
13.6%
2 2
9.1%
3 3
13.6%
5 3
13.6%
7 1
 
4.5%
9 1
 
4.5%
10 1
 
4.5%
11 1
 
4.5%
12 1
 
4.5%
ValueCountFrequency (%)
15 1
 
4.5%
14 1
 
4.5%
13 2
9.1%
12 1
 
4.5%
11 1
 
4.5%
10 1
 
4.5%
9 1
 
4.5%
7 1
 
4.5%
5 3
13.6%
3 3
13.6%

Interactions

2024-01-28T17:18:37.845692image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-28T17:18:37.701092image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-28T17:18:37.924467image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-28T17:18:37.775931image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-01-28T17:18:39.786407image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
동별국공립사회복지법인법인_단체 등민간협동직장가정
동별1.0001.0001.0001.0001.0001.0001.0001.000
국공립1.0001.0000.0000.4460.0000.1460.1240.365
사회복지법인1.0000.0001.0000.0000.4720.0000.0000.236
법인_단체 등1.0000.4460.0001.0000.0000.0000.0000.000
민간1.0000.0000.4720.0001.0000.7720.2530.448
협동1.0000.1460.0000.0000.7721.0000.0000.000
직장1.0000.1240.0000.0000.2530.0001.0000.000
가정1.0000.3650.2360.0000.4480.0000.0001.000
2024-01-28T17:18:39.883002image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
법인_단체 등국공립협동사회복지법인직장
법인_단체 등1.0000.2740.0000.0000.000
국공립0.2741.0000.0410.0000.077
협동0.0000.0411.0000.0000.000
사회복지법인0.0000.0000.0001.0000.000
직장0.0000.0770.0000.0001.000
2024-01-28T17:18:39.962373image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
민간가정국공립사회복지법인법인_단체 등협동직장
민간1.0000.0880.0000.2730.0000.4880.063
가정0.0881.0000.0000.1380.0000.0000.202
국공립0.0000.0001.0000.0000.2740.0410.077
사회복지법인0.2730.1380.0001.0000.0000.0000.000
법인_단체 등0.0000.0000.2740.0001.0000.0000.000
협동0.4880.0000.0410.0000.0001.0000.000
직장0.0630.2020.0770.0000.0000.0001.000

Missing values

2024-01-28T17:18:38.037476image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-01-28T17:18:38.130101image/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

동별국공립사회복지법인법인_단체 등민간협동직장가정
0부평 1 동01020014
1부평 2 동0006001
2부평 3 동1002101
3부평 4 동2006015
4부평 5 동0009011
5부평 6 동2004012
6산곡 1 동2103000
7산곡 2 동10070112
8산곡 3 동1102005
9산곡 4 동0002009
동별국공립사회복지법인법인_단체 등민간협동직장가정
12갈산 1 동1003002
13갈산 2 동10001113
14삼산 1 동30090011
15삼산 2 동00070110
16부개 1 동2003003
17부개 2 동3004007
18부개 3 동10090015
19일 신 동1102015
20십정 1 동3026003
21십정 2 동10010003