How to change frequency of date x-axis in Matplotlib and Python.

In this post you can find how to change the date frequency of date x-axis labels in Matplotlib and Python.

We are going to see the default behaviour and the changed date frequency.

So default behaviour of the Matplotlib and bar plot depends highly on the data that you have.

In this example we will use data for Bitcoin price from it's start. You can find the data below:

Symbol	Date	High	Low	Open
BTC	2013-04-29 23:59:59	147.488007	134.000000	134.444000
BTC	2013-04-30 23:59:59	146.929993	134.050003	144.000000
BTC	2013-05-01 23:59:59	139.889999	107.720001	139.000000
BTC	2013-05-02 23:59:59	125.599998	92.281898	116.379997
BTC	2013-05-03 23:59:59	108.127998	79.099998	106.250000

We can plot the price for each date with bar plot by method: plt.bar:

import pandas as pd
import matplotlib.pyplot as plt
import matplotlib.dates as mdates

df = pd.read_csv('../../data/coin_Bitcoin.csv')

df['Date'] = pd.to_datetime(df['Date'])

plt.bar(df['Date'], df['High'])

result:

If you like to get a bigger plot and different x axis frequency you can use the code below. Date interval frequency is set to 120:

plt.figure(figsize=(20,8))
plt.gca().xaxis.set_major_formatter(mdates.DateFormatter('%d-%m-%Y'))
plt.gca().xaxis.set_major_locator(mdates.DayLocator())

plt.gca().xaxis.set_major_locator(mdates.DayLocator(interval=120))
plt.gcf().autofmt_xdate()

plt.bar(df['Date'], df['High'])

plt.xticks(rotation=90)

plt.show()

result:

And testing with frequency 60:

plt.figure(figsize=(20,8))
plt.gca().xaxis.set_major_formatter(mdates.DateFormatter('%d-%m-%Y'))
plt.gca().xaxis.set_major_locator(mdates.DayLocator())

plt.gca().xaxis.set_major_locator(mdates.DayLocator(interval=60))
plt.gcf().autofmt_xdate()

plt.bar(df['Date'], df['High'])

plt.xticks(rotation=90)

plt.show()

this will result in a ticker date labels on the x-axis: