plot pandas dataframe two columns

Question

i have a pandas dataframe which has dates as indexes and some columns: I would like to plot a line chart with 2 lines (let's say 'ISP.MI' and 'Ctrv'); on the x axis I need the 'Date'

Ticker       ISP.MI  Daily returns        Ctrv  Inv_Am  Giac_Media
Date                                                                 
2016-01-01  2.90117            NaN  100.000000     100       100.0   
2016-01-04  2.80159      -0.034927  196.507301     200       150.0   
2016-01-05  2.85608       0.019263  300.292610     300       200.0   
2016-01-06  2.77904      -0.027345  392.081255     400       250.0   
2016-01-07  2.73206      -0.017050  485.396411     500       300.0   
2016-01-08  2.72267      -0.003443  583.725246     600       350.0   

Answer 1

I think the simpliest is select columns by subset and then DataFrame.plot:

df[['ISP.MI','Ctrv']].plot()

Answer 2

if you dont care about axis scale:

plt.figure()

x = df['Date']
y1 = df['ISP.MI']
y2 = df['Ctrv']

plt.plot(x,y1)
plt.plot(x,y2)

if you do care about it:

fig, ax1 = plt.subplots()

x = df['Date']
y1 = df['ISP.MI']
y2 = df['Ctrv']

ax2 = ax1.twinx()

ax1.plot(x, y1, 'g-')
ax2.plot(x, y2, 'b-')

Answer 3

import numpy as np
import pandas as pd
import matplotlib.pyplot as plt

d = {'x' : [1,2,3,4,5,6,7,8,9,10],
     'y_one' : np.random.rand(10),
     'y_two' : np.random.rand(10)}

df = pd.DataFrame(d)

df.plot('x',y=['y_one','y_two'])
plt.show()

Answer 4

So, here is the code that from scratch creates a dataframe that looks like yours and generates the plot you asked for:

import pandas as pd
import datetime
import numpy as np
from matplotlib import pyplot as plt

# The following two lines are not mandatory for the code to work
import matplotlib.style as style
style.use('dark_background')

def create_datetime_range(numdays=10):
    """Creates the timestamp range"""
    base = datetime.datetime.today()
    datelist = pd.date_range(base, periods=numdays).to_pydatetime()
    return datelist
def convert_to_date(datetime_list):
    """Converts a timestamp array into a date array"""
    return [x.date() for x in datetime_list]



a = pd.DataFrame(
    {
        'ISP.MI': np.random.normal(2,1,10),
        'Ctrv' : np.random.normal(200,150,10)
    }, 
    index=convert_to_date(create_date_range())
)
a.plot()

However, I believe that your dataframe is different in two ways:

1. It seems that there are two levels in the index (the Date title seems on a second row to the Ticker title). I imagine this could be because you used something like .groupby() or .unstack() or other aggregation/pivoting method. I suggest you to look in the reset_index() method.

2.Your dataframe has more columns that you need. As suggested by @jezrael, you should first select only these. You can do it with something like:

df[['ISP.MI','Ctrv']]

and then using the .plot() method on the smaller dataframe and let pandas handle the rest.