Overview

Dataset statistics

Number of variables7
Number of observations36
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory2.2 KiB
Average record size in memory63.7 B

Variable types

DateTime1
Numeric4
Categorical2

Dataset

Description제주특별자치도 제주연구원에서 조사 및 제공하는 제주지역 금융 및 부동산 관련 구분별(가계대출 / 주택매매 / 주택전세 / 토지) 연도별 동향 정보를 제공합니다. (기준 2020.01=100)
Author제주특별자치도
URLhttps://www.data.go.kr/data/15051468/fileData.do

Alerts

자료 has constant value ""Constant
데이터기준일자 has constant value ""Constant
주택매매가격지수 is highly overall correlated with 주택전세가격지수 and 2 other fieldsHigh correlation
주택전세가격지수 is highly overall correlated with 주택매매가격지수 and 2 other fieldsHigh correlation
토지가격지수 is highly overall correlated with 주택매매가격지수 and 1 other fieldsHigh correlation
가계대출(억원_누적) is highly overall correlated with 주택매매가격지수 and 1 other fieldsHigh correlation
해당연월 has unique valuesUnique
가계대출(억원_누적) has unique valuesUnique

Reproduction

Analysis started2023-12-12 20:43:34.755851
Analysis finished2023-12-12 20:43:37.282491
Duration2.53 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

해당연월
Date

UNIQUE 

Distinct36
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size420.0 B
Minimum2020-01-01 00:00:00
Maximum2022-12-01 00:00:00
2023-12-13T05:43:37.401416image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T05:43:37.571554image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=36)

주택매매가격지수
Real number (ℝ)

HIGH CORRELATION 

Distinct28
Distinct (%)77.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean96.447222
Minimum90.7
Maximum101.4
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size456.0 B
2023-12-13T05:43:37.697972image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum90.7
5-th percentile90.7
Q191.775
median96.3
Q3100.45
95-th percentile101.3
Maximum101.4
Range10.7
Interquartile range (IQR)8.675

Descriptive statistics

Standard deviation4.0336078
Coefficient of variation (CV)0.041821918
Kurtosis-1.554718
Mean96.447222
Median Absolute Deviation (MAD)4.4
Skewness-0.16036885
Sum3472.1
Variance16.269992
MonotonicityNot monotonic
2023-12-13T05:43:37.816846image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=28)
ValueCountFrequency (%)
90.7 4
 
11.1%
101.3 3
 
8.3%
101.2 3
 
8.3%
94.8 2
 
5.6%
91.8 1
 
2.8%
98.1 1
 
2.8%
101.4 1
 
2.8%
100.9 1
 
2.8%
100.6 1
 
2.8%
100.4 1
 
2.8%
Other values (18) 18
50.0%
ValueCountFrequency (%)
90.7 4
11.1%
91.0 1
 
2.8%
91.4 1
 
2.8%
91.5 1
 
2.8%
91.6 1
 
2.8%
91.7 1
 
2.8%
91.8 1
 
2.8%
93.7 1
 
2.8%
94.8 2
5.6%
94.9 1
 
2.8%
ValueCountFrequency (%)
101.4 1
 
2.8%
101.3 3
8.3%
101.2 3
8.3%
100.9 1
 
2.8%
100.6 1
 
2.8%
100.4 1
 
2.8%
100.3 1
 
2.8%
100.0 1
 
2.8%
99.7 1
 
2.8%
99.4 1
 
2.8%

주택전세가격지수
Real number (ℝ)

HIGH CORRELATION 

Distinct23
Distinct (%)63.9%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean97.180556
Minimum92.4
Maximum100.9
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size456.0 B
2023-12-13T05:43:37.956238image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum92.4
5-th percentile92.475
Q192.7
median97.75
Q3100.125
95-th percentile100.725
Maximum100.9
Range8.5
Interquartile range (IQR)7.425

Descriptive statistics

Standard deviation3.232851
Coefficient of variation (CV)0.033266438
Kurtosis-1.4078737
Mean97.180556
Median Absolute Deviation (MAD)2.5
Skewness-0.45349048
Sum3498.5
Variance10.451325
MonotonicityNot monotonic
2023-12-13T05:43:38.116837image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=23)
ValueCountFrequency (%)
92.7 5
 
13.9%
100.4 3
 
8.3%
92.5 3
 
8.3%
92.4 2
 
5.6%
96.4 2
 
5.6%
96.5 2
 
5.6%
100.7 2
 
5.6%
100.1 2
 
5.6%
99.9 1
 
2.8%
100.8 1
 
2.8%
Other values (13) 13
36.1%
ValueCountFrequency (%)
92.4 2
 
5.6%
92.5 3
8.3%
92.7 5
13.9%
96.3 1
 
2.8%
96.4 2
 
5.6%
96.5 2
 
5.6%
96.6 1
 
2.8%
97.2 1
 
2.8%
97.6 1
 
2.8%
97.9 1
 
2.8%
ValueCountFrequency (%)
100.9 1
 
2.8%
100.8 1
 
2.8%
100.7 2
5.6%
100.4 3
8.3%
100.3 1
 
2.8%
100.2 1
 
2.8%
100.1 2
5.6%
100.0 1
 
2.8%
99.9 1
 
2.8%
99.7 1
 
2.8%

토지가격지수
Real number (ℝ)

HIGH CORRELATION 

Distinct22
Distinct (%)61.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean98.122222
Minimum96.7
Maximum100.5
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size456.0 B
2023-12-13T05:43:38.262433image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum96.7
5-th percentile96.7
Q196.9
median97.75
Q399.175
95-th percentile100.425
Maximum100.5
Range3.8
Interquartile range (IQR)2.275

Descriptive statistics

Standard deviation1.3648885
Coefficient of variation (CV)0.013910086
Kurtosis-1.1176892
Mean98.122222
Median Absolute Deviation (MAD)0.95
Skewness0.60120156
Sum3532.4
Variance1.8629206
MonotonicityNot monotonic
2023-12-13T05:43:38.402109image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=22)
ValueCountFrequency (%)
96.7 6
16.7%
100.4 3
 
8.3%
96.9 3
 
8.3%
98.3 2
 
5.6%
100.5 2
 
5.6%
97.2 2
 
5.6%
96.8 2
 
5.6%
98.0 2
 
5.6%
98.9 1
 
2.8%
100.1 1
 
2.8%
Other values (12) 12
33.3%
ValueCountFrequency (%)
96.7 6
16.7%
96.8 2
 
5.6%
96.9 3
8.3%
97.0 1
 
2.8%
97.1 1
 
2.8%
97.2 2
 
5.6%
97.4 1
 
2.8%
97.5 1
 
2.8%
97.7 1
 
2.8%
97.8 1
 
2.8%
ValueCountFrequency (%)
100.5 2
5.6%
100.4 3
8.3%
100.1 1
 
2.8%
99.9 1
 
2.8%
99.6 1
 
2.8%
99.4 1
 
2.8%
99.1 1
 
2.8%
98.9 1
 
2.8%
98.7 1
 
2.8%
98.5 1
 
2.8%

가계대출(억원_누적)
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct36
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean169975.44
Minimum162503
Maximum176634
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size456.0 B
2023-12-13T05:43:38.546197image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum162503
5-th percentile162693.5
Q1166377.25
median170516
Q3173240
95-th percentile176271
Maximum176634
Range14131
Interquartile range (IQR)6862.75

Descriptive statistics

Standard deviation4581.4368
Coefficient of variation (CV)0.026953522
Kurtosis-1.0498293
Mean169975.44
Median Absolute Deviation (MAD)3483
Skewness-0.36279117
Sum6119116
Variance20989564
MonotonicityNot monotonic
2023-12-13T05:43:38.723310image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=36)
ValueCountFrequency (%)
163019 1
 
2.8%
174927 1
 
2.8%
175375 1
 
2.8%
175959 1
 
2.8%
176634 1
 
2.8%
176256 1
 
2.8%
175153 1
 
2.8%
173927 1
 
2.8%
173011 1
 
2.8%
172639 1
 
2.8%
Other values (26) 26
72.2%
ValueCountFrequency (%)
162503 1
2.8%
162566 1
2.8%
162736 1
2.8%
162779 1
2.8%
162861 1
2.8%
163019 1
2.8%
163487 1
2.8%
164696 1
2.8%
165643 1
2.8%
166622 1
2.8%
ValueCountFrequency (%)
176634 1
2.8%
176316 1
2.8%
176256 1
2.8%
175959 1
2.8%
175375 1
2.8%
175153 1
2.8%
174927 1
2.8%
174071 1
2.8%
173927 1
2.8%
173011 1
2.8%

자료
Categorical

CONSTANT 

Distinct1
Distinct (%)2.8%
Missing0
Missing (%)0.0%
Memory size420.0 B
제주연구원 제주경제동향
36 

Length

Max length12
Median length12
Mean length12
Min length12

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row제주연구원 제주경제동향
2nd row제주연구원 제주경제동향
3rd row제주연구원 제주경제동향
4th row제주연구원 제주경제동향
5th row제주연구원 제주경제동향

Common Values

ValueCountFrequency (%)
제주연구원 제주경제동향 36
100.0%

Length

2023-12-13T05:43:38.883578image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T05:43:39.021288image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
제주연구원 36
50.0%
제주경제동향 36
50.0%

데이터기준일자
Categorical

CONSTANT 

Distinct1
Distinct (%)2.8%
Missing0
Missing (%)0.0%
Memory size420.0 B
2023-01-02
36 

Length

Max length10
Median length10
Mean length10
Min length10

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2023-01-02
2nd row2023-01-02
3rd row2023-01-02
4th row2023-01-02
5th row2023-01-02

Common Values

ValueCountFrequency (%)
2023-01-02 36
100.0%

Length

2023-12-13T05:43:39.183956image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T05:43:39.326968image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2023-01-02 36
100.0%

Interactions

2023-12-13T05:43:36.251923image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T05:43:34.938931image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T05:43:35.386838image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T05:43:35.791863image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T05:43:36.683142image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T05:43:35.053974image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T05:43:35.485095image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T05:43:35.905474image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T05:43:36.790214image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T05:43:35.139011image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T05:43:35.577393image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T05:43:36.016074image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T05:43:36.901820image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T05:43:35.252455image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T05:43:35.692868image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T05:43:36.141206image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-13T05:43:39.410863image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
해당연월주택매매가격지수주택전세가격지수토지가격지수가계대출(억원_누적)
해당연월1.0001.0001.0001.0001.000
주택매매가격지수1.0001.0000.9520.8270.676
주택전세가격지수1.0000.9521.0000.6260.766
토지가격지수1.0000.8270.6261.0000.503
가계대출(억원_누적)1.0000.6760.7660.5031.000
2023-12-13T05:43:39.545620image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
주택매매가격지수주택전세가격지수토지가격지수가계대출(억원_누적)
주택매매가격지수1.0000.9910.7830.572
주택전세가격지수0.9911.0000.7780.561
토지가격지수0.7830.7781.0000.200
가계대출(억원_누적)0.5720.5610.2001.000

Missing values

2023-12-13T05:43:37.043842image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-13T05:43:37.215514image/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

해당연월주택매매가격지수주택전세가격지수토지가격지수가계대출(억원_누적)자료데이터기준일자
02020-0191.892.798.3163019제주연구원 제주경제동향2023-01-02
12020-0291.792.798.0162736제주연구원 제주경제동향2023-01-02
22020-0391.692.797.7162779제주연구원 제주경제동향2023-01-02
32020-0491.592.797.4162503제주연구원 제주경제동향2023-01-02
42020-0591.492.797.2162566제주연구원 제주경제동향2023-01-02
52020-0691.092.597.1162861제주연구원 제주경제동향2023-01-02
62020-0790.792.497.0163487제주연구원 제주경제동향2023-01-02
72020-0890.792.496.9164696제주연구원 제주경제동향2023-01-02
82020-0990.792.596.9165643제주연구원 제주경제동향2023-01-02
92020-1090.792.596.8166622제주연구원 제주경제동향2023-01-02
해당연월주택매매가격지수주택전세가격지수토지가격지수가계대출(억원_누적)자료데이터기준일자
262022-03100.4100.199.1173927제주연구원 제주경제동향2023-01-02
272022-04100.6100.299.4173011제주연구원 제주경제동향2023-01-02
282022-05100.9100.399.6172639제주연구원 제주경제동향2023-01-02
292022-06101.2100.499.9172016제주연구원 제주경제동향2023-01-02
302022-07101.3100.4100.1170887제주연구원 제주경제동향2023-01-02
312022-08101.3100.4100.4170387제주연구원 제주경제동향2023-01-02
322022-09101.4100.7100.5170403제주연구원 제주경제동향2023-01-02
332022-10101.2100.7100.5169757제주연구원 제주경제동향2023-01-02
342022-11101.3100.9100.4169064제주연구원 제주경제동향2023-01-02
352022-12101.2100.8100.4168647제주연구원 제주경제동향2023-01-02