I have the following data (dataset name is 'data' in the code below) and code. So far my code plots one scatterplot at a time; I need to change the company name manually if I am to get a specific scatterplot for a specific company. I am looking to be able to go through the dataset below in one blush such that my prospective code reads the company name and executes the manipulations captured in the existing code below and ultimately produces separate scatterplots (ie subplots) for both companies Company1 and Company2 without one scatterplot overwriting or superimposing on the other. I was thinking I could use a for loop to go through the lines of code that I have below, but I am missing smth. Can someone please provide some insight?
Thanks in advance.
Dataset:
Date Company Cum_FootTraffic
1/1/2015 Company1 450
1/3/2015 Company1 464
1/4/2015 Company1 481
1/5/2015 Company1 500
1/8/2015 Company1 508
………………………………………………………………
6/30/2015 Company1 810
4/2/2015 Company2 203
4/3/2015 Company2 208
4/4/2015 Company2 211
4/5/2015 Company2 218
4/8/2015 Company2 223
4/10/2015 Company2 234
…………………………………………………………………
8/10/2015 Company2 498
Code:
data2=data.loc[data['username']=='Company1']
data2['Cum_FootTraffic_lag']=data2['Cum_FootTraffic'].shift(1)
data2['count']=data2['Cum_FootTraffic']-data2['Cum_FootTraffic_lag']
data2=data2.loc[data2['count']>=0]
data2=data2[['username','Date','Cum_FootTraffic','Cum_FootTraffic_lag','count']]
#Plotting data and manipulating plot size
#Scatterplot
dates = matplotlib.dates.date2num(data2['Date'])
matplotlib.pyplot.scatter(dates, data2['count'])
matplotlib.pyplot.show()
