Overview

Dataset statistics

Number of variables11
Number of observations258
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory23.6 KiB
Average record size in memory93.5 B

Variable types

Numeric5
Categorical6

Dataset

Description충청북도 청주시 치매의료이용율 데이터로 대상연도, 구, 행정읍면동, 의료보험가입자 구분, 보험료 분위, 성별, 연령, 비표준화지표분자, 비표준화지표분모, 비표준화지표, 표준화지표를 제공합니다.
Author충청북도 청주시
URLhttps://www.data.go.kr/data/15110865/fileData.do

Alerts

가입자구분 has constant value ""Constant
보험료분위 has constant value ""Constant
성별 has constant value ""Constant
연령 has constant value ""Constant
구 is highly overall correlated with 행정읍면동High correlation
행정읍면동 is highly overall correlated with 비표준화지표분모 and 1 other fieldsHigh correlation
대상연도 is highly overall correlated with 표준화지표High correlation
비표준화지표분자 is highly overall correlated with 비표준화지표분모 and 1 other fieldsHigh correlation
비표준화지표분모 is highly overall correlated with 비표준화지표분자 and 2 other fieldsHigh correlation
비표준화지표 is highly overall correlated with 비표준화지표분모High correlation
표준화지표 is highly overall correlated with 대상연도 and 1 other fieldsHigh correlation

Reproduction

Analysis started2023-12-12 02:48:07.517197
Analysis finished2023-12-12 02:48:11.202306
Duration3.69 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

대상연도
Real number (ℝ)

HIGH CORRELATION 

Distinct6
Distinct (%)2.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2017.5
Minimum2015
Maximum2020
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size2.4 KiB
2023-12-12T11:48:11.271196image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum2015
5-th percentile2015
Q12016
median2017.5
Q32019
95-th percentile2020
Maximum2020
Range5
Interquartile range (IQR)3

Descriptive statistics

Standard deviation1.7111445
Coefficient of variation (CV)0.00084815094
Kurtosis-1.2698824
Mean2017.5
Median Absolute Deviation (MAD)1.5
Skewness0
Sum520515
Variance2.9280156
MonotonicityIncreasing
2023-12-12T11:48:11.427580image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=6)
ValueCountFrequency (%)
2015 43
16.7%
2016 43
16.7%
2017 43
16.7%
2018 43
16.7%
2019 43
16.7%
2020 43
16.7%
ValueCountFrequency (%)
2015 43
16.7%
2016 43
16.7%
2017 43
16.7%
2018 43
16.7%
2019 43
16.7%
2020 43
16.7%
ValueCountFrequency (%)
2020 43
16.7%
2019 43
16.7%
2018 43
16.7%
2017 43
16.7%
2016 43
16.7%
2015 43
16.7%

구
Categorical

HIGH CORRELATION 

Distinct4
Distinct (%)1.6%
Missing0
Missing (%)0.0%
Memory size2.1 KiB
상당구
78 
서원구
66 
흥덕구
66 
청원구
48 

Length

Max length3
Median length3
Mean length3
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
상당구 78
30.2%
서원구 66
25.6%
흥덕구 66
25.6%
청원구 48
18.6%

Length

2023-12-12T11:48:11.578926image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T11:48:11.712899image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
상당구 78
30.2%
서원구 66
25.6%
흥덕구 66
25.6%
청원구 48
18.6%

행정읍면동
Categorical

HIGH CORRELATION 

Distinct43
Distinct (%)16.7%
Missing0
Missing (%)0.0%
Memory size2.1 KiB
가덕면
 
6
중앙동
 
6
남일면
 
6
낭성면
 
6
문의면
 
6
Other values (38)
228 

Length

Max length9
Median length3
Mean length3.9302326
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row가덕면
2nd row금천동
3rd row남일면
4th row낭성면
5th row문의면

Common Values

ValueCountFrequency (%)
가덕면 6
 
2.3%
중앙동 6
 
2.3%
남일면 6
 
2.3%
낭성면 6
 
2.3%
문의면 6
 
2.3%
미원면 6
 
2.3%
성안동 6
 
2.3%
영운동 6
 
2.3%
용담.명암.산성동 6
 
2.3%
용암1동 6
 
2.3%
Other values (33) 198
76.7%

Length

2023-12-12T11:48:11.874738image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
가덕면 6
 
2.3%
수곡2동 6
 
2.3%
내덕1동 6
 
2.3%
내덕2동 6
 
2.3%
내수읍 6
 
2.3%
북이면 6
 
2.3%
오근장동 6
 
2.3%
오창읍 6
 
2.3%
우암동 6
 
2.3%
율량.사천동 6
 
2.3%
Other values (33) 198
76.7%

가입자구분
Categorical

CONSTANT 

Distinct1
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size2.1 KiB
전체
258 

Length

Max length2
Median length2
Mean length2
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
전체 258
100.0%

Length

2023-12-12T11:48:12.024860image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T11:48:12.153262image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
전체 258
100.0%

보험료분위
Categorical

CONSTANT 

Distinct1
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size2.1 KiB
전체
258 

Length

Max length2
Median length2
Mean length2
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
전체 258
100.0%

Length

2023-12-12T11:48:12.262454image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T11:48:12.383316image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
전체 258
100.0%

성별
Categorical

CONSTANT 

Distinct1
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size2.1 KiB
전체
258 

Length

Max length2
Median length2
Mean length2
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
전체 258
100.0%

Length

2023-12-12T11:48:12.525544image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T11:48:12.643132image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
전체 258
100.0%

연령
Categorical

CONSTANT 

Distinct1
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size2.1 KiB
전체
258 

Length

Max length2
Median length2
Mean length2
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
전체 258
100.0%

Length

2023-12-12T11:48:12.794289image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T11:48:12.914594image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
전체 258
100.0%

비표준화지표분자
Real number (ℝ)

HIGH CORRELATION 

Distinct177
Distinct (%)68.6%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean213.51163
Minimum48
Maximum561
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size2.4 KiB
2023-12-12T11:48:13.037327image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum48
5-th percentile94
Q1143
median191.5
Q3259
95-th percentile423.75
Maximum561
Range513
Interquartile range (IQR)116

Descriptive statistics

Standard deviation98.613826
Coefficient of variation (CV)0.4618663
Kurtosis0.98420112
Mean213.51163
Median Absolute Deviation (MAD)55
Skewness1.0916574
Sum55086
Variance9724.6866
MonotonicityNot monotonic
2023-12-12T11:48:13.209388image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
189 7
 
2.7%
199 6
 
2.3%
146 4
 
1.6%
183 4
 
1.6%
172 3
 
1.2%
99 3
 
1.2%
324 3
 
1.2%
139 3
 
1.2%
193 3
 
1.2%
201 3
 
1.2%
Other values (167) 219
84.9%
ValueCountFrequency (%)
48 1
 
0.4%
62 1
 
0.4%
66 1
 
0.4%
67 1
 
0.4%
71 1
 
0.4%
75 1
 
0.4%
79 1
 
0.4%
81 1
 
0.4%
89 3
1.2%
94 3
1.2%
ValueCountFrequency (%)
561 1
0.4%
527 1
0.4%
517 1
0.4%
499 1
0.4%
489 1
0.4%
482 1
0.4%
469 1
0.4%
462 1
0.4%
451 1
0.4%
440 1
0.4%

비표준화지표분모
Real number (ℝ)

HIGH CORRELATION 

Distinct255
Distinct (%)98.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean9697.6202
Minimum1751
Maximum27084
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size2.4 KiB
2023-12-12T11:48:13.362703image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1751
5-th percentile2875.35
Q15567.75
median7895.5
Q311797
95-th percentile23280.05
Maximum27084
Range25333
Interquartile range (IQR)6229.25

Descriptive statistics

Standard deviation6390.4529
Coefficient of variation (CV)0.65897125
Kurtosis0.30515168
Mean9697.6202
Median Absolute Deviation (MAD)3429
Skewness1.1197996
Sum2501986
Variance40837888
MonotonicityNot monotonic
2023-12-12T11:48:13.519399image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1795 2
 
0.8%
6190 2
 
0.8%
6112 2
 
0.8%
3146 1
 
0.4%
4064 1
 
0.4%
1792 1
 
0.4%
8232 1
 
0.4%
23279 1
 
0.4%
7140 1
 
0.4%
6113 1
 
0.4%
Other values (245) 245
95.0%
ValueCountFrequency (%)
1751 1
0.4%
1773 1
0.4%
1780 1
0.4%
1792 1
0.4%
1795 2
0.8%
1820 1
0.4%
1885 1
0.4%
1929 1
0.4%
1995 1
0.4%
2755 1
0.4%
ValueCountFrequency (%)
27084 1
0.4%
26615 1
0.4%
25747 1
0.4%
25676 1
0.4%
25578 1
0.4%
25511 1
0.4%
25321 1
0.4%
25151 1
0.4%
24101 1
0.4%
23921 1
0.4%

비표준화지표
Real number (ℝ)

HIGH CORRELATION 

Distinct181
Distinct (%)70.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2.6516279
Minimum1.05
Maximum7.31
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size2.4 KiB
2023-12-12T11:48:13.697078image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1.05
5-th percentile1.377
Q11.85
median2.355
Q33.1175
95-th percentile5.1775
Maximum7.31
Range6.26
Interquartile range (IQR)1.2675

Descriptive statistics

Standard deviation1.1361487
Coefficient of variation (CV)0.42847215
Kurtosis2.5709061
Mean2.6516279
Median Absolute Deviation (MAD)0.585
Skewness1.4936131
Sum684.12
Variance1.2908339
MonotonicityNot monotonic
2023-12-12T11:48:13.868719image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1.84 5
 
1.9%
2.53 4
 
1.6%
2.48 3
 
1.2%
3.17 3
 
1.2%
1.66 3
 
1.2%
1.85 3
 
1.2%
3.04 3
 
1.2%
2.72 3
 
1.2%
1.91 3
 
1.2%
1.5 3
 
1.2%
Other values (171) 225
87.2%
ValueCountFrequency (%)
1.05 1
0.4%
1.1 1
0.4%
1.15 1
0.4%
1.16 1
0.4%
1.22 1
0.4%
1.28 1
0.4%
1.31 2
0.8%
1.32 1
0.4%
1.33 1
0.4%
1.35 1
0.4%
ValueCountFrequency (%)
7.31 1
0.4%
7.01 1
0.4%
6.99 1
0.4%
6.04 1
0.4%
6.01 1
0.4%
5.9 1
0.4%
5.79 1
0.4%
5.52 2
0.8%
5.27 1
0.4%
5.26 1
0.4%

표준화지표
Real number (ℝ)

HIGH CORRELATION 

Distinct102
Distinct (%)39.5%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1.7848837
Minimum1.08
Maximum2.89
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size2.4 KiB
2023-12-12T11:48:14.050133image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1.08
5-th percentile1.317
Q11.5875
median1.76
Q31.98
95-th percentile2.243
Maximum2.89
Range1.81
Interquartile range (IQR)0.3925

Descriptive statistics

Standard deviation0.30315235
Coefficient of variation (CV)0.16984431
Kurtosis0.68789026
Mean1.7848837
Median Absolute Deviation (MAD)0.195
Skewness0.40604792
Sum460.5
Variance0.091901348
MonotonicityNot monotonic
2023-12-12T11:48:14.236362image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1.69 9
 
3.5%
1.81 7
 
2.7%
1.74 7
 
2.7%
1.71 6
 
2.3%
1.52 6
 
2.3%
1.85 5
 
1.9%
2.11 5
 
1.9%
1.95 5
 
1.9%
1.7 5
 
1.9%
1.77 5
 
1.9%
Other values (92) 198
76.7%
ValueCountFrequency (%)
1.08 1
0.4%
1.15 2
0.8%
1.17 1
0.4%
1.18 2
0.8%
1.22 1
0.4%
1.23 1
0.4%
1.27 2
0.8%
1.29 1
0.4%
1.3 2
0.8%
1.32 1
0.4%
ValueCountFrequency (%)
2.89 1
 
0.4%
2.86 1
 
0.4%
2.75 1
 
0.4%
2.43 3
1.2%
2.41 1
 
0.4%
2.4 1
 
0.4%
2.38 1
 
0.4%
2.32 1
 
0.4%
2.27 1
 
0.4%
2.26 2
0.8%

Interactions

2023-12-12T11:48:10.002847image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T11:48:07.913144image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T11:48:08.352323image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T11:48:08.821944image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T11:48:09.476977image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T11:48:10.112353image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T11:48:07.995764image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T11:48:08.436949image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T11:48:08.918976image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T11:48:09.574021image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T11:48:10.219282image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T11:48:08.080649image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T11:48:08.514036image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T11:48:09.021182image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T11:48:09.668745image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T11:48:10.330259image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T11:48:08.171149image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T11:48:08.602583image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T11:48:09.108172image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T11:48:09.771682image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T11:48:10.450122image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T11:48:08.260973image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T11:48:08.724779image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T11:48:09.316659image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T11:48:09.891981image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-12T11:48:14.349239image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
대상연도구행정읍면동비표준화지표분자비표준화지표분모비표준화지표표준화지표
대상연도1.0000.0000.0000.2310.0000.1530.498
구0.0001.0001.0000.3130.6180.2530.243
행정읍면동0.0001.0001.0000.7150.8880.7100.610
비표준화지표분자0.2310.3130.7151.0000.8060.2190.419
비표준화지표분모0.0000.6180.8880.8061.0000.5500.236
비표준화지표0.1530.2530.7100.2190.5501.0000.825
표준화지표0.4980.2430.6100.4190.2360.8251.000
2023-12-12T11:48:14.482083image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
구행정읍면동
구1.0000.920
행정읍면동0.9201.000
2023-12-12T11:48:14.571461image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
대상연도비표준화지표분자비표준화지표분모비표준화지표표준화지표구행정읍면동
대상연도1.0000.3920.0480.3850.6720.0000.000
비표준화지표분자0.3921.0000.802-0.2240.5040.1890.314
비표준화지표분모0.0480.8021.000-0.7290.0940.4170.525
비표준화지표0.385-0.224-0.7291.0000.4080.1620.322
표준화지표0.6720.5040.0940.4081.0000.1560.250
구0.0000.1890.4170.1620.1561.0000.920
행정읍면동0.0000.3140.5250.3220.2500.9201.000

Missing values

2023-12-12T11:48:10.623020image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-12T11:48:11.126605image/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

대상연도구행정읍면동가입자구분보험료분위성별연령비표준화지표분자비표준화지표분모비표준화지표표준화지표
02015상당구가덕면전체전체전체전체8930392.931.38
12015상당구금천동전체전체전체전체212162171.311.32
22015상당구남일면전체전체전체전체10741552.581.4
32015상당구낭성면전체전체전체전체4817732.711.15
42015상당구문의면전체전체전체전체9432092.931.22
52015상당구미원면전체전체전체전체13339543.361.36
62015상당구성안동전체전체전체전체9443352.171.15
72015상당구영운동전체전체전체전체12564911.931.44
82015상당구용담.명암.산성동전체전체전체전체7957151.381.3
92015상당구용암1동전체전체전체전체323208011.551.74
대상연도구행정읍면동가입자구분보험료분위성별연령비표준화지표분자비표준화지표분모비표준화지표표준화지표
2482020흥덕구강서제1동전체전체전체전체364136102.672.23
2492020흥덕구강서제2동전체전체전체전체10543782.42.01
2502020청원구내수읍전체전체전체전체375111843.352.09
2512020청원구오창읍전체전체전체전체469270841.731.85
2522020청원구북이면전체전체전체전체22036636.012.4
2532020청원구우암동전체전체전체전체31177144.032.12
2542020청원구내덕1동전체전체전체전체21758263.722.01
2552020청원구내덕2동전체전체전체전체21569983.071.85
2562020청원구율량.사천동전체전체전체전체527237322.222.15
2572020청원구오근장동전체전체전체전체19385092.271.98