00:49:28	Jim Cooley:	A question when you get a chance: what resources besides this can students learn Python whether at UND or not?
01:02:14	Raihan Quader:	I can't log in yet
01:06:58	Christopher Scott:	I had PyCharm downloaded onto my laptop
01:07:27	Mariia Goriacheva (Morrell):	Spyder and PyCharm for Windows
01:18:19	Christian Nairy:	Instructions to dowload Sypder if interested: https://docs.spyder-ide.org/current/installation.html
01:19:21	Jim Cooley:	Spyder looks similar to RStudio, which I'm familiar with. And, you can run Python code in RStudio. So i'm going to research the pros/cons of learning Spyder versus, adapting Python in RStudio...
01:19:34	Jim Cooley:	Thanks for showing us that Christian.
01:21:15	Christian Nairy:	No problem!
01:44:18	David Delene:	Let know up.
02:14:17	David Delene:	data_europe = pd.read_csv('data/gapminder_gdp_europe.csv', index_col='country')
02:14:25	David Delene:	Write an expression to find the Per Capita GDP of Serbia in 2007.
03:01:49	David Delene:	first = pd.read_csv('data/gapminder_all.csv', index_col='country')
second = first[first['continent'] == 'Americas']
third = second.drop('Puerto Rico')
fourth = third.drop('continent', axis = 1)
fourth.to_csv('result.csv')
03:17:26	David Delene:	data_europe = pd.read_csv('data/gapminder_gdp_europe.csv', index_col='country')
data_europe.____.plot(label='min')
data_europe.____
plt.legend(loc='best')
plt.xticks(rotation=90)
03:22:01	David Delene:	Fill in the blanks above to plot the minimum GDP per capita over time for all the countries in Europe. Modify it again to plot the maximum GDP per capita over time for Europe.