Overview

Dataset statistics

Number of variables10
Number of observations33
Missing cells21
Missing cells (%)6.4%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory3.0 KiB
Average record size in memory94.0 B

Variable types

Numeric4
Categorical6

Dataset

Description금정구 구의회 의안에 대한 현황(합계, 결의안수, 결산안 수, 결의 수, 규칙 수 등)에 대한 정보가 있으며 회기가 있을 때마다 업데이트
Author부산광역시 금정구
URLhttps://www.data.go.kr/data/15037970/fileData.do

Alerts

규칙 is highly overall correlated with 결산안High correlation
결산안 is highly overall correlated with 구분 and 7 other fieldsHigh correlation
건의 is highly overall correlated with 결산안 and 1 other fieldsHigh correlation
예산안 is highly overall correlated with 조례안 and 2 other fieldsHigh correlation
결의 is highly overall correlated with 결산안High correlation
구분 is highly overall correlated with 승인-동의 and 2 other fieldsHigh correlation
기타 is highly overall correlated with 결산안 and 1 other fieldsHigh correlation
승인-동의 is highly overall correlated with 구분 and 2 other fieldsHigh correlation
조례안 is highly overall correlated with 구분 and 3 other fieldsHigh correlation
청원 is highly overall correlated with 기타High correlation
기타 has 5 (15.2%) missing valuesMissing
승인-동의 has 15 (45.5%) missing valuesMissing
조례안 has 1 (3.0%) missing valuesMissing
구분 has unique valuesUnique

Reproduction

Analysis started2023-12-12 14:08:59.507792
Analysis finished2023-12-12 14:09:02.209750
Duration2.7 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

구분
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct33
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2007
Minimum1991
Maximum2023
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size429.0 B
2023-12-12T23:09:02.266918image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1991
5-th percentile1992.6
Q11999
median2007
Q32015
95-th percentile2021.4
Maximum2023
Range32
Interquartile range (IQR)16

Descriptive statistics

Standard deviation9.6695398
Coefficient of variation (CV)0.0048179072
Kurtosis-1.2
Mean2007
Median Absolute Deviation (MAD)8
Skewness0
Sum66231
Variance93.5
MonotonicityStrictly decreasing
2023-12-12T23:09:02.389805image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=33)
ValueCountFrequency (%)
2023 1
 
3.0%
1998 1
 
3.0%
2004 1
 
3.0%
2003 1
 
3.0%
2002 1
 
3.0%
2001 1
 
3.0%
2000 1
 
3.0%
1999 1
 
3.0%
1997 1
 
3.0%
2022 1
 
3.0%
Other values (23) 23
69.7%
ValueCountFrequency (%)
1991 1
3.0%
1992 1
3.0%
1993 1
3.0%
1994 1
3.0%
1995 1
3.0%
1996 1
3.0%
1997 1
3.0%
1998 1
3.0%
1999 1
3.0%
2000 1
3.0%
ValueCountFrequency (%)
2023 1
3.0%
2022 1
3.0%
2021 1
3.0%
2020 1
3.0%
2019 1
3.0%
2018 1
3.0%
2017 1
3.0%
2016 1
3.0%
2015 1
3.0%
2014 1
3.0%

건의
Categorical

HIGH CORRELATION 

Distinct4
Distinct (%)12.1%
Missing0
Missing (%)0.0%
Memory size396.0 B
<NA>
21 
1
9 
2
 
2
4
 
1

Length

Max length4
Median length4
Mean length2.9090909
Min length1

Unique

Unique1 ?
Unique (%)3.0%

Sample

1st row<NA>
2nd row<NA>
3rd row<NA>
4th row<NA>
5th row1

Common Values

ValueCountFrequency (%)
<NA> 21
63.6%
1 9
27.3%
2 2
 
6.1%
4 1
 
3.0%

Length

2023-12-12T23:09:02.531295image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T23:09:02.647170image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 21
63.6%
1 9
27.3%
2 2
 
6.1%
4 1
 
3.0%

결산안
Categorical

HIGH CORRELATION 

Distinct2
Distinct (%)6.1%
Missing0
Missing (%)0.0%
Memory size396.0 B
<NA>
23 
1
10 

Length

Max length4
Median length4
Mean length3.0909091
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 23
69.7%
1 10
30.3%

Length

2023-12-12T23:09:02.766735image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T23:09:02.878346image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 23
69.7%
1 10
30.3%

결의
Categorical

HIGH CORRELATION 

Distinct4
Distinct (%)12.1%
Missing0
Missing (%)0.0%
Memory size396.0 B
<NA>
14 
1
11 
2
6 
3
2 

Length

Max length4
Median length1
Mean length2.2727273
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row<NA>
2nd row<NA>
3rd row3
4th row2
5th row1

Common Values

ValueCountFrequency (%)
<NA> 14
42.4%
1 11
33.3%
2 6
18.2%
3 2
 
6.1%

Length

2023-12-12T23:09:03.002543image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T23:09:03.105315image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 14
42.4%
1 11
33.3%
2 6
18.2%
3 2
 
6.1%

규칙
Categorical

HIGH CORRELATION 

Distinct6
Distinct (%)18.2%
Missing0
Missing (%)0.0%
Memory size396.0 B
<NA>
16 
1
10 
2
3 
3
2 
12
 
1

Length

Max length4
Median length2
Mean length2.4848485
Min length1

Unique

Unique2 ?
Unique (%)6.1%

Sample

1st row1
2nd row12
3rd row2
4th row1
5th row1

Common Values

ValueCountFrequency (%)
<NA> 16
48.5%
1 10
30.3%
2 3
 
9.1%
3 2
 
6.1%
12 1
 
3.0%
4 1
 
3.0%

Length

2023-12-12T23:09:03.212512image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T23:09:03.311608image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 16
48.5%
1 10
30.3%
2 3
 
9.1%
3 2
 
6.1%
12 1
 
3.0%
4 1
 
3.0%

기타
Real number (ℝ)

HIGH CORRELATION  MISSING 

Distinct20
Distinct (%)71.4%
Missing5
Missing (%)15.2%
Infinite0
Infinite (%)0.0%
Mean12.785714
Minimum1
Maximum27
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size429.0 B
2023-12-12T23:09:03.427887image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q17.5
median13
Q318.25
95-th percentile24.65
Maximum27
Range26
Interquartile range (IQR)10.75

Descriptive statistics

Standard deviation7.6708063
Coefficient of variation (CV)0.59995133
Kurtosis-0.92627422
Mean12.785714
Median Absolute Deviation (MAD)5.5
Skewness0.012865744
Sum358
Variance58.84127
MonotonicityNot monotonic
2023-12-12T23:09:03.539047image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=20)
ValueCountFrequency (%)
1 3
 
9.1%
10 3
 
9.1%
17 2
 
6.1%
15 2
 
6.1%
19 2
 
6.1%
13 2
 
6.1%
27 1
 
3.0%
16 1
 
3.0%
25 1
 
3.0%
21 1
 
3.0%
Other values (10) 10
30.3%
(Missing) 5
15.2%
ValueCountFrequency (%)
1 3
9.1%
2 1
 
3.0%
3 1
 
3.0%
5 1
 
3.0%
6 1
 
3.0%
8 1
 
3.0%
9 1
 
3.0%
10 3
9.1%
11 1
 
3.0%
13 2
6.1%
ValueCountFrequency (%)
27 1
3.0%
25 1
3.0%
24 1
3.0%
22 1
3.0%
21 1
3.0%
19 2
6.1%
18 1
3.0%
17 2
6.1%
16 1
3.0%
15 2
6.1%

승인-동의
Real number (ℝ)

HIGH CORRELATION  MISSING 

Distinct11
Distinct (%)61.1%
Missing15
Missing (%)45.5%
Infinite0
Infinite (%)0.0%
Mean7.7777778
Minimum1
Maximum18
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size429.0 B
2023-12-12T23:09:03.647468image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q12
median8.5
Q312.25
95-th percentile16.3
Maximum18
Range17
Interquartile range (IQR)10.25

Descriptive statistics

Standard deviation5.9759868
Coefficient of variation (CV)0.76834116
Kurtosis-1.3794134
Mean7.7777778
Median Absolute Deviation (MAD)6.5
Skewness0.3252555
Sum140
Variance35.712418
MonotonicityNot monotonic
2023-12-12T23:09:03.751270image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=11)
ValueCountFrequency (%)
1 3
 
9.1%
2 3
 
9.1%
10 2
 
6.1%
16 2
 
6.1%
9 2
 
6.1%
4 1
 
3.0%
18 1
 
3.0%
15 1
 
3.0%
13 1
 
3.0%
8 1
 
3.0%
(Missing) 15
45.5%
ValueCountFrequency (%)
1 3
9.1%
2 3
9.1%
3 1
 
3.0%
4 1
 
3.0%
8 1
 
3.0%
9 2
6.1%
10 2
6.1%
13 1
 
3.0%
15 1
 
3.0%
16 2
6.1%
ValueCountFrequency (%)
18 1
 
3.0%
16 2
6.1%
15 1
 
3.0%
13 1
 
3.0%
10 2
6.1%
9 2
6.1%
8 1
 
3.0%
4 1
 
3.0%
3 1
 
3.0%
2 3
9.1%

예산안
Categorical

HIGH CORRELATION 

Distinct5
Distinct (%)15.2%
Missing0
Missing (%)0.0%
Memory size396.0 B
<NA>
23 
3
6 
4
 
2
1
 
1
2
 
1

Length

Max length4
Median length4
Mean length3.0909091
Min length1

Unique

Unique2 ?
Unique (%)6.1%

Sample

1st row1
2nd row2
3rd row3
4th row4
5th row4

Common Values

ValueCountFrequency (%)
<NA> 23
69.7%
3 6
 
18.2%
4 2
 
6.1%
1 1
 
3.0%
2 1
 
3.0%

Length

2023-12-12T23:09:03.871103image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T23:09:04.038975image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 23
69.7%
3 6
 
18.2%
4 2
 
6.1%
1 1
 
3.0%
2 1
 
3.0%

조례안
Real number (ℝ)

HIGH CORRELATION  MISSING 

Distinct21
Distinct (%)65.6%
Missing1
Missing (%)3.0%
Infinite0
Infinite (%)0.0%
Mean20.0625
Minimum1
Maximum64
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size429.0 B
2023-12-12T23:09:04.140773image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1.55
Q12
median7
Q341.25
95-th percentile59.35
Maximum64
Range63
Interquartile range (IQR)39.25

Descriptive statistics

Standard deviation22.527313
Coefficient of variation (CV)1.1228567
Kurtosis-1.0340845
Mean20.0625
Median Absolute Deviation (MAD)5
Skewness0.85208356
Sum642
Variance507.47984
MonotonicityNot monotonic
2023-12-12T23:09:04.260336image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=21)
ValueCountFrequency (%)
2 7
21.2%
5 3
 
9.1%
7 3
 
9.1%
1 2
 
6.1%
39 1
 
3.0%
4 1
 
3.0%
3 1
 
3.0%
58 1
 
3.0%
11 1
 
3.0%
16 1
 
3.0%
Other values (11) 11
33.3%
ValueCountFrequency (%)
1 2
 
6.1%
2 7
21.2%
3 1
 
3.0%
4 1
 
3.0%
5 3
9.1%
6 1
 
3.0%
7 3
9.1%
8 1
 
3.0%
11 1
 
3.0%
16 1
 
3.0%
ValueCountFrequency (%)
64 1
3.0%
61 1
3.0%
58 1
3.0%
54 1
3.0%
53 1
3.0%
51 1
3.0%
49 1
3.0%
48 1
3.0%
39 1
3.0%
35 1
3.0%

청원
Categorical

HIGH CORRELATION 

Distinct4
Distinct (%)12.1%
Missing0
Missing (%)0.0%
Memory size396.0 B
<NA>
26 
1
4 
2
 
2
4
 
1

Length

Max length4
Median length4
Mean length3.3636364
Min length1

Unique

Unique1 ?
Unique (%)3.0%

Sample

1st row<NA>
2nd row<NA>
3rd row<NA>
4th row<NA>
5th row<NA>

Common Values

ValueCountFrequency (%)
<NA> 26
78.8%
1 4
 
12.1%
2 2
 
6.1%
4 1
 
3.0%

Length

2023-12-12T23:09:04.393097image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T23:09:04.512167image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 26
78.8%
1 4
 
12.1%
2 2
 
6.1%
4 1
 
3.0%

Interactions

2023-12-12T23:09:01.315508image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T23:09:00.117456image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T23:09:00.517493image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T23:09:00.912385image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T23:09:01.422654image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T23:09:00.217425image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T23:09:00.600367image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T23:09:01.019891image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T23:09:01.508185image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T23:09:00.316523image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T23:09:00.704215image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T23:09:01.114845image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T23:09:01.600363image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T23:09:00.419979image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T23:09:00.799388image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T23:09:01.213885image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-12T23:09:04.607296image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
구분건의결의규칙기타승인-동의예산안조례안청원
구분1.0000.3010.6760.0000.0940.3680.0000.3690.000
건의0.3011.0000.0000.0000.0000.000NaN0.0000.827
결의0.6760.0001.0000.0000.6910.7220.0000.5530.346
규칙0.0000.0000.0001.0000.1800.6480.5980.4970.000
기타0.0940.0000.6910.1801.0000.5700.7370.0001.000
승인-동의0.3680.0000.7220.6480.5701.0000.7270.6410.000
예산안0.000NaN0.0000.5980.7370.7271.0001.000NaN
조례안0.3690.0000.5530.4970.0000.6411.0001.0000.000
청원0.0000.8270.3460.0001.0000.000NaN0.0001.000
2023-12-12T23:09:04.777957image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
규칙청원결산안건의예산안결의
규칙1.0000.0001.0000.0000.3820.000
청원0.0001.000NaN0.000NaN0.333
결산안1.000NaN1.0001.0001.0001.000
건의0.0000.0001.0001.0001.0000.000
예산안0.382NaN1.0001.0001.0000.000
결의0.0000.3331.0000.0000.0001.000
2023-12-12T23:09:04.990584image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
구분기타승인-동의조례안건의결산안결의규칙예산안청원
구분1.000-0.3120.7890.5820.0001.0000.3000.0000.0000.000
기타-0.3121.000-0.030-0.2280.0001.0000.2320.0000.3541.000
승인-동의0.789-0.0301.0000.8540.0001.0000.2300.3640.3910.000
조례안0.582-0.2280.8541.0000.0001.0000.2120.2130.8160.000
건의0.0000.0000.0000.0001.0001.0000.0000.0001.0000.000
결산안1.0001.0001.0001.0001.0001.0001.0001.0001.000NaN
결의0.3000.2320.2300.2120.0001.0001.0000.0000.0000.333
규칙0.0000.0000.3640.2130.0001.0000.0001.0000.3820.000
예산안0.0000.3540.3910.8161.0001.0000.0000.3821.000NaN
청원0.0001.0000.0000.0000.000NaN0.3330.000NaN1.000

Missing values

2023-12-12T23:09:01.757282image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-12T23:09:01.930591image/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.
2023-12-12T23:09:02.094609image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
The correlation heatmap measures nullity correlation: how strongly the presence or absence of one variable affects the presence of another.

Sample

구분건의결산안결의규칙기타승인-동의예산안조례안청원
02023<NA>1<NA>11010135<NA>
12022<NA>1<NA>12154239<NA>
22021<NA>1322416354<NA>
32020<NA>1212716464<NA>
420191111918461<NA>
52018<NA>1<NA><NA>815351<NA>
62017<NA>12<NA>6133491
7201611<NA>1510348<NA>
82015111<NA>19353<NA>
920141<NA><NA><NA>19330<NA>
구분건의결산안결의규칙기타승인-동의예산안조례안청원
2320002<NA><NA><NA>15<NA><NA>5<NA>
241999<NA><NA><NA>111<NA><NA><NA><NA>
251998<NA><NA>2118<NA><NA>11<NA>
261997<NA><NA><NA>117<NA><NA>58<NA>
271996<NA><NA>3<NA>193<NA>3<NA>
2819951<NA>1<NA>212<NA>22
2919942<NA>11132<NA>52
3019931<NA>2<NA>252<NA>24
3119921<NA>1316<NA><NA>7<NA>
3219914<NA>1<NA>101<NA>41