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主にクロス表(分割表)分析をしようかなと思いはじめましたが、あまりクロス表の分析はできず。R言語の練習ブログになっています。

Data_Analysis

OECD Business confidence Index(BCI) data analysis 3 - Time-Series Regression using R - static model

Photo by Elena Louca on Unsplash www.crosshyou.info This post is following of above post. Let's do time-series regression.Firstly, let's make a static time series model In time-series regression, we have to care about serial correlation of…

OECD Business confidence Index(BCI) data analysis 3 - time-series chart using ggplot() + geom_line()

Photo by NASA on Unsplash www.crosshyou.info This post is following of above post. Let's see time-series for bci average. Let's see time-series for good average. average bci and average good are both very volatile. what is the correlation …

OECD Business confidence Index(BCI) data analysis 2 - BCI average by region are the same but...

Photo by T S on Unsplash www.crosshyou.info This post is following of above post. I have another CSV flile like below. I read this file too. Let' merge this dataframe and previous dataframe. I convert region and sub.region to factor class.…

OECD Business confidence Index(BCI) data analysis 1 - read CSV file data using R language read_csv() function

Photo by William Olivieri on Unsplash In this post, I will analyze OECD Business confidence index(BCI) using R. From the OECD web site, I download below CSV file. Firstly, I load tidyverse package. Then, I use read_csv() finction to read t…

OECD NEET Data Analysis 7 - Panel Data Analysis with FD(First Differenced) Estimator

Photo by Jonas Allert on Unsplash www.crosshyou.info This post is following of the above post.In this post I will try panel data analysis, FD(First Differenced) estimator.I refere to "Using R for Introductory Econometrics" by Florian Heisi…

OECD NEET Data Analysis 6- Heteroskedasticity-Robust Inference using R

Photo by Gabriel Garcia Marengo on Unsplash www.crosshyou.info This post is following of the above post. Hello. In this post, I will do Heteroskedasiticity test usung R. In te previous post, I meade regression model using R. Let's plot fit…

OECD NEET Data Analysis 5 - Regression analysis using R - NEET percentage and per capita GDP & GDP amount

Photo by JD Rincs on Unsplash www.crosshyou.info This post is gollowing of the above post. In this post, I will do regression analysis using R. I will check if GDP, per capita GDP are statistically significant factor to NEET percentage. Fi…

OECD NEET Data Analysis 4 - NEET percentage and per capita GDP has negative correlation

Photo by Stephanie LeBlanc on Unsplash www.crosshyou.info This post is following of the above post. Let's check how many observations each country has. Max observations is 24. Many country has more than 20 observations.So, let's see averag…

OECD NEET Data Analysis 3 - correlation between MEN_15_29 and WOMEN_15_29. It is positive correlation.

Photo by Michael D Beckwith on Unsplash www.crosshyou.info This post is following of above post. Let's see time-series distribution for 15_29_MEN and 15_29_WOMEN It is a bit difficult to see trends.So, I divided before 2010 and after 2011 …

OECD NEET Data Analysis 2 - 15_29_WOMEN NEET percentage is higher than MEN.

Photo by Chris Briggs on Unsplash www.crosshyou.info This post is following of above post. There are many SUBJECTs, so let's focus 15_29 first. It is NEET percentage among 15_29 old young people. Firstly, let's see a histogram. There is a …

OECD NEET Data Analysis 1 - read CSV file using R read_csv function.

Photo by 懒 羊羊 on Unsplash In this BLOG series, I will investigae NEET data. Firstly, I get data from OECD web site. CSV file is like below. Let's load this data into R.Firstly, I load tidyverse package and will use read_csv function. Al…

OECD Meat Consumption Data Analysis 8 - Serial Correlation Robust Inference using R

Photo by T o T on Unsplash www.crosshyou.info This post is following of above post. In this post, I will check if there is serial correlation in the previous regression model. First, I make residual with resid() function. Then, let's make …

OECD Meat Consumption Data Analysis 7 - Time Series Regression using R dynlm() function.

Photo by Ashutosh Saraswat on Unsplash www.crosshyou.info This post is following of aabove post.In this post, I will do some time-series regression with R. First, I made JPN only dataframe. Let's see df_jpn. Then, I make ts object form df_…

OECD Meat Consumption Data Analysis 6 - POULTRY Consumption is positively correlated with GDP

Photo by corina ardeleanu on Unsplash www.crosshyou.info This post is following of above post. I have GDP data like below CSV file. So, let's combine this GDP data and Meat Consumption data. Next, I use inner_join() function to combine df2…

OECD Meat Consumption Data Analysis 5 - scatter plot using R ggplot2::geom_point()

Photo by Casey Horner on Unsplash www.crosshyou.info This post is following of above post.In this post, let's draw scatter plots using R ggplot2::geom_point.First of all, let's see correlations about 4 KG_CAPs. bekg: BEEF KG_CAP and pokg: …

OECD Meat Consumption Data Analysis 4 - USA is the most meat consumption country.

Photo by Claiton Conto on Unsplash www.crosshyou.info This post is following of above post.Let's see KG_CAP data as country average. Firstly, bekg: BEEK KG_CAP ARG is the highest beef consumption country. IND is the lowest. How about pikg:…

OECD Meat Consumption Data Analysis 3 - PIG and POULTRY are on up trend while BEEF and SHEEP are on down trend.

Photo by Nathan Anderson on Unsplash www.crosshyou.info This post is following of above post. Let's see coun: country. We see all country have 40 observations. Let's see year We see all year have 38 observations.So, df2 data frame is 40 co…

OECD Meat Consumption Data Analysis 2 - PIG is the most popular meat.

Photo by boris misevic on Unsplash www.crosshyou.info This post is following above post.Now, we now there are 4 sunjects and 2 measures. 4 subjects are BEEG, PIG, POULTRY and SHEEP. 2 measures are KG_CAP and THND_TONNE.So, we have 8 combin…

OECD Meat Consumption Data Analysis 1 - Using R to read CSV data with read_csv() function.

Photo by Wolfgang Hasselmann on Unsplash Hello! This post, I will anaysis OECD Meat Consumption data using R. I got a CSV file like below from OECD web site(Agricultural output - Meat consumption - OECD Data) Firstly, I load tidyverse pack…

OECD Gender wage gap data analysis 5 - Serial Correlation Test using R

Photo by BP Miller on Unsplash www.crosshyou.info This post is following of the above psot. In this post, let's test if there is serial correlation. Firdt of all, load lmtest package. All right, let's start with model1. p-value of lag resi…

OECD Gender wage gap data analysis 4 - Time Series Data Regression with lag and trend using R

Photo by Masako Ishida on Unsplash www.crosshyou.info This post is following of the above post. Which chountry has many observations? NZL has 22 observations. AUT, BEL, DNK, FIN, NOR and SWE have 16 observations. Let's see NZL data. We see…

OECD Gender wage gap data analysis 3 - using facet_grid() and facet_wrap() in R.

Photo by Damien TUPINIER on Unsplash www.crosshyou.info This post is following of above post.Let's see which year has many observations. Okay, 2014, 2010, 2006 and 2018 have over 20 observations. Let's see those years more. First, emp dens…

OECD Gender wage gap data analysis 2 - Data Visualization using R ggplot() + geom_histogram(), geom_points(), geom_line()

Photo by Luca Bravo on Unsplash www.crosshyou.info This post is following of above post. I will makse some graphs for data visualization using R. Fist, let's see how our data are distributed. I use ggplot() + geom_histogram() First, emp(em…

OECD Gender wage gap data analysis 1 - Load CSV file data into R

Photo by Trevor McKinnon on Unsplash In this post, I will analyze OECD Gender wage gap data. From the OECD web site, I downloaded the CSV data file like below. I will use R to analyze this data. First, I load tidyverse packages Then, I use…

OECD Household disposable income data analysis 7 - Bootstrap using R

Photo by Toni Lluch on Unsplash www.crosshyou.info This post is following of above post.In this post I will do Bootstrap and make confidence inerval of regression. First, let's check coefficients for static regression model again. Intercep…

OECD Household disposable income data analysis 6 - Time-Series Data Regression using R

Photo by Jeremy Bishop on Unsplash www.crosshyou.info This post is following of above post.In this post, I will do time-series data regression using R. Firstly, I converted avg_gr_us in 10000 value. Then, I converted df_year2 data frame to…

OECD Household disposable income data analysis 5 - simple linear regression analysis using R

Photo by V Srinivasan on Unsplash www.crosshyou.info This post is following of the above post. In this post, let's do simple linaer regression anaysis using R. First, I use df_country data frame. Coefficients of avg_gr_us is -1.002e-04, it…

OECD Household disposable income data analysis 4 - make a data frame by country and by year using R.

Photo by Olga Tsai on Unsplash www.crosshyou.info This post is following of above post. In this post, let's make average value data frame by country and by year. First, I make a data frame for average value by country using group_by() func…

OECD Household disposable income data analysis 3 - making some graphs using R.

Photo by Lorena Schmidt on Unsplash www.crosshyou.info This post is following of above post. In this post, let's make some graphs to understand data distributions, data relationship. Fisrt, a histgram of gr_us. ecdf plot of gr_us. boxplot …

OECD Household disposable income data analysis 2 - using filter(), select(), inner_join() functions to make a date frame more analyzable.

Photo by CHUTTERSNAP on Unsplash www.crosshyou.info This post is following of above post. In the previous post, we made a dafa frame called a "df". We see there are two values in subject, GROSSADJ and NET, two values in measure, AGRWTH and…