Plotting in Python

#from pandas import *
import pandas as pd
from ggplot import *

import pandas

def lineplot(hr_year_csv):
    # A csv file will be passed in as an argument which
    # contains two columns -- 'HR' (the number of homerun hits)
    # and 'yearID' (the year in which the homeruns were hit).
    #
    # Fill out the body of this function, lineplot, to use the
    # passed-in csv file, hr_year.csv, and create a
    # chart with points connected by lines, both colored 'red',
    # showing the number of HR by year.
    #
    # You will want to first load the csv file into a pandas dataframe
    # and use the pandas dataframe along with ggplot to create your visualization
    #
    # You can check out the data in the csv file at the link below:
    # https://www.dropbox.com/s/awgdal71hc1u06d/hr_year.csv
    #
    # You can read more about ggplot at the following link:
    # https://github.com/yhat/ggplot/
    
    data = pd.read_csv(hr_year_csv)
    gg = ggplot(data, aes('yearID','HR')) + geom_point(color = 'red') + geom_line(color='red') \
            + ggtitle('Home Runs by Year') + xlab('Year') + ylab('Home Runs')
    return gg

hr_year_csv = './data/hr_year.csv'
%matplotlib inline
lineplot(hr_year_csv)

<ggplot: (14749300)>

Plotting Line Charts

import pandas as pd

from ggplot import *


def lineplot_compare(hr_by_team_year_sf_la_csv):
    # Write a function, lineplot_compare, that will read a csv file
    # called hr_by_team_year_sf_la.csv and plot it using pandas and ggplot.
    #
    # This csv file has three columns: yearID, HR, and teamID. The data in the
    # file gives the total number of home runs hit each year by the SF Giants 
    # (teamID == 'SFN') and the LA Dodgers (teamID == "LAN"). Produce a 
    # visualization comparing the total home runs by year of the two teams. 
    # 
    # You can see the data in hr_by_team_year_sf_la_csv
    # at the link below:
    # https://www.dropbox.com/s/wn43cngo2wdle2b/hr_by_team_year_sf_la.csv
    #
    # Note that to differentiate between multiple categories on the 
    # same plot in ggplot, we can pass color in with the other arguments
    # to aes, rather than in our geometry functions. For example, 
    # ggplot(data, aes(xvar, yvar, color=category_var)). This should help you 
    # in this exercise.
    
    data = pd.read_csv(hr_by_team_year_sf_la_csv)
    gg = ggplot(data, aes('yearID', 'HR', color='teamID')) + geom_point() + geom_line() \
        + ggtitle('Home Runs by Year') + xlab('Year') + ylab('Home Runs')
    return gg

hr_by_team_year_sf_la_csv = './data/hr_by_team_year_sf_la.csv'
%matplotlib inline
lineplot_compare(hr_by_team_year_sf_la_csv)

<ggplot: (12132773)>