In initial rounds of data prep, my objective was to eliminate some columns not relevant to my analysis (such as information regarding daily opening and closing prices of these coins). Then, I choose to look only at trends of coins when they showed above average market cap and above average trade volume. I also produced a new iteration of the dataset everytime I made a change (such as Bitcoin, Bitcoin2, Bitcoin3, etc). My latest round of data prep involved using tidyverse and an if else statement to not have to create multiple iterations of the original document everytime I ran the code. The final dataset has columns for Trade Volume, Market Cap, Date, and Days since ICO (initial coin offering) so as to make it easier for the code to run the graphs, because Days since ICO is basically written as integers.
hraman1
commented
1 year ago
In initial rounds of data prep, my objective was to eliminate some columns not relevant to my analysis (such as information regarding daily opening and closing prices of these coins). Then, I choose to look only at trends of coins when they showed above average market cap and above average trade volume. I also produced a new iteration of the dataset everytime I made a change (such as Bitcoin, Bitcoin2, Bitcoin3, etc). My latest round of data prep involved using tidyverse and an if else statement to not have to create multiple iterations of the original document everytime I ran the code. The final dataset has columns for Trade Volume, Market Cap, Date, and Days since ICO (initial coin offering) so as to make it easier for the code to run the graphs, because Days since ICO is basically written as integers.