This post is floowing of the above post.
Let's explore gdp dataframe.
gdp dataframe has more LOCATION than researcher dataframe.
gdp dataframe INDICATOR has only one calue, GDP. So I can remove it.
gdp SUBJECT has only one value, TOT, so I can remove it.
gdp MEASURE has two value: USD_CAP and NLN_USD, so I cannot remove it.
gdp FREQUENCY has only one value: A. I can remove it.
gdp TIME starts at 1960 and ends at 2021.
So far, I can remove INDICATOR, SUBJECT and FREQUENCY from gdp dataframe.
Let's see new dataframe.
Next, I merge the two dataframes, before doing that, I convert to dataframe into wide format.
Let's see this new wide format dataframe.
I see AUT 1998 has 5.107570 for TOT_1000EMPLOYED, 18.79060 for WOMEN_PC_RESEARCHER, 5901 for WOMEN_HEADCOUNT and 31404 for TOT_HEADACOUNT.
Let's convert gdp_v2 to wide format too.
Let's see it.
AUS 1960 has 25073.26 for MLN_USD and 2412.765 for USD_CAP.
Finally, I can merge the two wide format dataframe.
Let's see it.
Then, I convert LOCATION to factor type from character.
Let's see summary statistics with summary() frunction.
I see all numeric variables are greater than zero, so I will make natural logarithm variables.
Let's see log variables summary statistics.
Let's call it a day. Thank you!
The next post is
To read from the 1st post,
