CODEWITHSUNDEEP
pythonpython-3.xpandas
Rohit Lamba
Rohit Lamba

Reputation: 186

How to add title to each subplot

I want to add title for each subplot. I want to assign a separate title to each subplot from a list of title in same sequence.

title_list = ['Table1', 'Table2',, 'Table3', 'Table4', 'Table5, 'Table6']

Hence assign title for df1 as 'Table1', df2 as 'Table2'.. and so on.

My Code as below:

import matplotlib.pyplot as plt
import pandas as pd
import numpy as np
# dataframe sample data
df1 = pd.DataFrame(np.random.rand(10,2)*100, columns=['A', 'B'])
df2 = pd.DataFrame(np.random.rand(10,2)*100, columns=['A', 'B'])
df3 = pd.DataFrame(np.random.rand(10,2)*100, columns=['A', 'B'])
df4 = pd.DataFrame(np.random.rand(10,2)*100, columns=['A', 'B'])
df5 = pd.DataFrame(np.random.rand(10,2)*100, columns=['A', 'B'])
df6 = pd.DataFrame(np.random.rand(10,2)*100, columns=['A', 'B'])

#define number of rows and columns for subplots
nrow=3
ncol=2

# make a list of all dataframes 
df_list = [df1 ,df2, df3, df4, df5, df6]
fig, axes = plt.subplots(nrow, ncol)

# plot counter
count=0
for r in range(nrow):
    for c in range(ncol):
        df_list[count].plot(ax=axes[r,c])
        count+=1

Upvotes: 1

Views: 2553

Answers (2)

Patryk Kowalski
Patryk Kowalski

Reputation: 571

Add ax.set_title like below

for r in range(nrow):
    for c in range(ncol):
        axes[r,c].set_title(title_list[(r*c) + c])
        df_list[count].plot(ax=axes[r,c])
        count+=1

Upvotes: 1

lumbric
lumbric

Reputation: 9093

You can use the method set_title() on the axis object:

axes[r, c].set_title(f"This is row={r} and column={c}")

I also added a call fig.tight_layout() to fix the spacing between subplots.

plot output of sample code

The complete code:

import matplotlib.pyplot as plt
import pandas as pd
import numpy as np
# dataframe sample data
df1 = pd.DataFrame(np.random.rand(10,2)*100, columns=['A', 'B'])
df2 = pd.DataFrame(np.random.rand(10,2)*100, columns=['A', 'B'])
df3 = pd.DataFrame(np.random.rand(10,2)*100, columns=['A', 'B'])
df4 = pd.DataFrame(np.random.rand(10,2)*100, columns=['A', 'B'])
df5 = pd.DataFrame(np.random.rand(10,2)*100, columns=['A', 'B'])
df6 = pd.DataFrame(np.random.rand(10,2)*100, columns=['A', 'B'])

#define number of rows and columns for subplots
nrow=3
ncol=2

# make a list of all dataframes 
df_list = [df1 ,df2, df3, df4, df5, df6]
fig, axes = plt.subplots(nrow, ncol)

# plot counter
count=0
for r in range(nrow):
    for c in range(ncol):
        df_list[count].plot(ax=axes[r,c])
        count+=1
        axes[r, c].set_title(f"This is row={r} and column={c}")
        
fig.tight_layout()

Note that you can simplify the creation of your sample data:

# dataframe sample data
df_list = [pd.DataFrame(np.random.rand(10,2)*100, columns=['A', 'B'])
           for _ in range(nrow * ncol)]

Upvotes: 2

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