Change X ticks for axes subplot

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I am trying to set the x ticks of my axes subplot but it is not working for me. Right now I have the following data frame:

Data Frame

I am using the following code to plot this:

ax=predictions.plot(y=['Actual','add_add','add_mul','mul_add','mul_mul','Philips'],figsize=(5,4), 
                 legend=True,color=['b','r','g','m','y','black'],ylabel='Quantity',xlabel='Date')
ax

And the result is as follows:

Plot

As you can see the month of August is written as Aug 2021. I would like to be able to change all the x ticks to either only the month or the month with the year (e.g keep Jul or set Jul 2021)

I have been trying using ax.set_xticks , but it hasn't work for me so far.

Thanks in advance!

xticks plot python
1 Answers

Don't save the predictions.plot() output into ax. You will simply get a list of lines. After implementing the solution below, you can view the output using plt.show().

When dealing with dates that are datetime objects

For labels with 'Jul 2021', 'Aug 2021', etc, use

import datetime
import matplotlib.pyplot as plt # Matplotlib.pyplot object

# Please note that df is a DataFrame object. Substitute your DataFrame object's name below. 
dates_index = df.index 

# You can use df.index in the list comprehension as well as in the plt.plot and plt.xticks operations as an alternative to dates_index.
labels = [f'{date.strftime("%b")} {date.strftime("%Y")}' for date in dates_index]
print(labels)

plt.plot(y=['Actual','add_add','add_mul','mul_add','mul_mul','Philips'],figsize=(5,4), 
                 legend=True,color=['b','r','g','m','y','black'],ylabel='Quantity',xlabel='Date')
plt.xticks(dates_index, labels)
plt.show() # Visualize the plot

For labels with 'Jul 21', 'Aug 21', etc, use

import datetime
import matplotlib.pyplot as plt # Matplotlib.pyplot object

# Please note that df is a DataFrame object. Substitute your DataFrame object's name below. 
dates_index = df.index

# You can use df.index in the list comprehension as well as in the plt.plot and plt.xticks operations as an alternative to dates_index.
labels = [f'{date.strftime("%b")} {date.strftime("%y")}' for date in dates_index]
print(labels)

plt.plot(y=['Actual','add_add','add_mul','mul_add','mul_mul','Philips'],figsize=(5,4), 
                 legend=True,color=['b','r','g','m','y','black'],ylabel='Quantity',xlabel='Date')
plt.xticks(dates_index, labels)
plt.show() # Visualize the plot

For labels with 'Jul', 'Aug', etc, use

import datetime
import matplotlib.pyplot as plt # Matplotlib.pyplot object

# Please note that df is a DataFrame object. Substitute your DataFrame object's name below.
dates_index = df.index 

# You can use df.index in the list comprehension as well as in the plt.plot and plt.xticks operations as an alternative to dates_index.
labels = [f'{date.strftime("%b")}' for date in dates_index]
print(labels)

plt.plot(y=['Actual','add_add','add_mul','mul_add','mul_mul','Philips'],figsize=(5,4), 
                 legend=True,color=['b','r','g','m','y','black'],ylabel='Quantity',xlabel='Date')
plt.xticks(dates_index, labels)
plt.show() # Visualize the plot

When dealing with dates that are str objects

For labels with 'Jul 2021', 'Aug 2021', etc, use

import datetime
import matplotlib.pyplot as plt # Matplotlib.pyplot object

# Please note that df is a DataFrame object. Substitute your DataFrame object's name below.
dates_index = df.index

# You can use df.index in the list comprehension as well as in the plt.plot and plt.xticks operations as an alternative to dates_index.
labels = [f'{(datetime.datetime.strptime(date, "%Y-%m-%d")).strftime("%b")} {datetime.datetime.strptime(date, "%Y-%m-%d").year}' for date in dates_index]
print(labels)

plt.plot(y=['Actual','add_add','add_mul','mul_add','mul_mul','Philips'],figsize=(5,4), 
                 legend=True,color=['b','r','g','m','y','black'],ylabel='Quantity',xlabel='Date')
plt.xticks(dates_index, labels)
plt.show() # Visualize the plot

For labels with 'Jul 21', 'Aug 21', etc, use

import datetime
import matplotlib.pyplot as plt # Matplotlib.pyplot object

# Please note that df is a DataFrame object. Substitute your DataFrame object's name below.
dates_index = df.index 

# You can use df.index in the list comprehension as well as in the plt.plot and plt.xticks operations as an alternative to dates_index.
labels = [f'{(datetime.datetime.strptime(date, "%Y-%m-%d")).strftime("%b")} {datetime.datetime.strptime(date, "%Y-%m-%d").strftime("%y")}' for date in dates_index]
print(labels)

plt.plot(y=['Actual','add_add','add_mul','mul_add','mul_mul','Philips'],figsize=(5,4), 
                 legend=True,color=['b','r','g','m','y','black'],ylabel='Quantity',xlabel='Date')
plt.xticks(dates_index, labels)
plt.show() # Visualize the plot

For labels with 'Jul', 'Aug', etc, use

import datetime
import matplotlib.pyplot as plt # Matplotlib.pyplot object

# Please note that df is a DataFrame object. Substitute your DataFrame object's name below.
dates_index = df.index 

# You can use df.index in the list comprehension as well as in the plt.plot and plt.xticks operations as an alternative to dates_index.
labels = [f'{(datetime.datetime.strptime(date, "%Y-%m-%d")).strftime("%b")}' for date in dates_index]
print(labels)

plt.plot(y=['Actual','add_add','add_mul','mul_add','mul_mul','Philips'],figsize=(5,4), 
                 legend=True,color=['b','r','g','m','y','black'],ylabel='Quantity',xlabel='Date')
plt.xticks(dates_index, labels)
plt.show() # Visualize the plot
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