Reducing the time frequency of x-axis for time series data

Question

I am plotting the stock price of a particular company of 10 years data. But x-axis is filled with a lot of data that is not readable. I tried many solutions to reduce the x-axis frequency. I don't want to floaded the x-axis rather I would be happy to show only the ticks on semi-annual basis. Below is my code. Please help me in getting the desired plot.

plt.figure(figsize=(25,5))
plt.plot(amd_df['date'][:train_seq],amd_df['close'][:train_seq],color='b',label = 'Train Data')
plt.plot(amd_df['date'][train_seq:],amd_df['close'][train_seq:],color='r',label = 'Test Data')
plt.title('AMD Stock Price')
plt.xlabel('Date')
plt.ylabel('Stock Price')
plt.xticks( rotation=25 )
plt.legend()
plt.show()

We have about 2683 data points in this plot. Please see below. Thank you

Answer 1

No data was provided, so we responded by creating sample data with random numbers. The point is to set MOnthLocator(interval=6) and set it to Dateformatter() . See the official reference .

import pandas as pd
import numpy as np

date_rng = pd.date_range('2010-01-01','2020-01-01', freq='B')
val = np.random.randint(0,100,(2609))
amd_df = pd.DataFrame({'date':date_rng,'close':val})
amd_df['date'] = pd.to_datetime(amd_df['date'])
train_seq = 2500
import matplotlib.pyplot as plt
import matplotlib.dates as mdates

fig = plt.figure(figsize=(25,5))
ax = fig.add_subplot(111)

ax.plot(amd_df['date'][:train_seq],amd_df['close'][:train_seq],color='b',label = 'Train Data')
ax.plot(amd_df['date'][train_seq:],amd_df['close'][train_seq:],color='r',label = 'Test Data')
ax.set_title('AMD Stock Price')
ax.set_xlabel('Date')
ax.set_ylabel('Stock Price')

months = mdates.MonthLocator(interval=6)
months_fmt = mdates.DateFormatter('%y-%m')
ax.xaxis.set_major_locator(months)
ax.xaxis.set_major_formatter(months_fmt)

ax.legend()
plt.show()