Python – Line plot with data points in pandas

matplotlibpandaspython

Using pandas I can easily make a line plot:

import pandas as pd
import numpy as np
%matplotlib inline # to use it in jupyter notebooks

df = pd.DataFrame(np.random.randn(50, 4), 
        index=pd.date_range('1/1/2000', periods=50), columns=list('ABCD'))
df = df.cumsum()
df.plot();

But I can't figure out how to also plot the data as points over the lines, as in this example:

This matplotlib example seems to suggest the direction, but I can't find how to do it using pandas plotting capabilities. And I am specially interested in learning how to do it with pandas because I am always working with dataframes.

Any clues?

Best Answer

You can use the style kwarg to the df.plot command. From the docs:

style : list or dict

matplotlib line style per column

So, you could either just set one linestyle for all the lines, or a different one for each line.

e.g. this does something similar to what you asked for:

df.plot(style='.-')

To define a different marker and linestyle for each line, you can use a list:

df.plot(style=['+-','o-','.--','s:'])

You can also pass the markevery kwarg onto matplotlib's plot command, to only draw markers at a given interval

df.plot(style='.-', markevery=5)

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figure tells you the call signature:

from matplotlib.pyplot import figure

figure(figsize=(8, 6), dpi=80)

figure(figsize=(1,1)) would create an inch-by-inch image, which would be 80-by-80 pixels unless you also give a different dpi argument.

Python – Limiting floats to two decimal points

You are running into the old problem with floating point numbers that not all numbers can be represented exactly. The command line is just showing you the full floating point form from memory.

With floating point representation, your rounded version is the same number. Since computers are binary, they store floating point numbers as an integer and then divide it by a power of two so 13.95 will be represented in a similar fashion to 125650429603636838/(2**53).

Double precision numbers have 53 bits (16 digits) of precision and regular floats have 24 bits (8 digits) of precision. The floating point type in Python uses double precision to store the values.

For example,

>>> 125650429603636838/(2**53)
13.949999999999999

>>> 234042163/(2**24)
13.949999988079071

>>> a = 13.946
>>> print(a)
13.946
>>> print("%.2f" % a)
13.95
>>> round(a,2)
13.949999999999999
>>> print("%.2f" % round(a, 2))
13.95
>>> print("{:.2f}".format(a))
13.95
>>> print("{:.2f}".format(round(a, 2)))
13.95
>>> print("{:.15f}".format(round(a, 2)))
13.949999999999999

If you are after only two decimal places (to display a currency value, for example), then you have a couple of better choices:

Use integers and store values in cents, not dollars and then divide by 100 to convert to dollars.
Or use a fixed point number like decimal.

Best Answer

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