Parsing Csv File Using Panda

I have been using matplotlib for quite some time now and it is great however, I want to switch to panda and my first attempt at it didn't go so well. My data set looks like this: s

Solution 1:

You can read a csv without headers:

data=pd.read_csv(filepath, header=None)

Columns will be numbered starting from 0. Selecting and filtering:

all_summers = data[data[0]=='summer']

If you want to do some operations grouping by the first column, it will look like this:

data.groupby(0).sum()
data.groupby(0).count()
...

Selecting a row after grouping:

sums = data.groupby(0).sum()
sums.loc['sam']

Plotting example:

 sums.plot()
 import matplotlib.pyplotas plt
 plt.show()

For more details about plotting, see: http://pandas.pydata.org/pandas-docs/version/0.18.1/visualization.html

Solution 2:

df = pd.read_csv(filepath, header=None)
mike = df[df[0]=='mike'].values.tolist()
winter = df[df[0]=='winter'].values.tolist()

Then you can plot those list as you wanted to above

fig1 = plt.figure(figsize= (10,10))

ax = fig1.add_subplot(211)

ax.plot(mike, winter, label='Mike vs Winter speed', color = 'red')