How do I control the number of x-axis ticks?

Question

I have pulled in a dataset that I want to use, with columns named Date and Adjusted . Adjusted is just the adjusted percentage growth on the base month.

The code I currently have is:

x = data['Date']
y = data['Adjusted']

fig = plt.figure(dpi=128, figsize=(7,3))
plt.plot(x,y)

plt.title("FTSE 100 Growth", fontsize=25)
plt.xlabel("Date", fontsize=14)
plt.ylabel("Adjusted %", fontsize=14)
plt.show()

However, when I run it I get essentially a solid black line across the bottom where all of the dates are covering each other up. It is trying to show every single date, when obviously I only want to show major ones. That dates are in the format Apr-19, and the data runs from Oct-03 to May-20.

How do I limit the number of date ticks and labels to one per year, or any amount I choose? If you do have a solution, if you could respond with the edits made to the code itself that would be great. I've tried other solutions I've found on here but I haven't been able to get it to work.

Answer 1

dates module of matplotlib will do the job. You can control the interval by modifying the MonthLocator (It's currently set to 6 months). Here's how:

import pandas as pd
from datetime import date, datetime, timedelta
import matplotlib.pyplot as plt
import matplotlib.dates as md
import numpy as np
import matplotlib.ticker as ticker

x = data['Date']
y = data['Adjusted']
#converts differently formatted date to a datetime object
def convert_date(df):
    return datetime.strptime(df['Date'], '%b-%y')
data['Formatted_Date'] = data.apply(convert_date, axis=1)


# plot
fig, ax = plt.subplots(1, 1)
ax.plot(data['Formatted_Date'], y,'ok')

## Set time format and the interval of ticks (every 6 months)
xformatter = md.DateFormatter('%Y-%m') # format as year, month
xlocator = md.MonthLocator(interval = 6)

## Set xtick labels to appear every 6 months
ax.xaxis.set_major_locator(xlocator)

## Format xtick labels as YYYY:mm
plt.gcf().axes[0].xaxis.set_major_formatter(xformatter)
plt.title("FTSE 100 Growth", fontsize=25)
plt.xlabel("Date", fontsize=14)
plt.ylabel("Adjusted %", fontsize=14)
plt.show()

Example output: