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Plot Certain Rows of a Pandas DataFrame Using Matplotlib
To plot certain rows of a Pandas dataframe, we can take the following steps −
- Set the figure size and adjust the padding between and around the subplots.
- Create a Pandas data frame, df. It should be a two-dimensional, size-mutable, potentially heterogeneous tabular data.
- Make rows of Pandas plot. Use iloc() function to slice the df and print specific rows.
- To display the figure, use show() method.
Example
from matplotlib import pyplot as plt import numpy as np import pandas as pd plt.rcParams["figure.figsize"] = [7.50, 3.50] plt.rcParams["figure.autolayout"] = True df = pd.DataFrame(np.random.randn(10, 5), columns=list('abcde')) df.iloc[0:6].plot(y='e') print(df.iloc[0:6]) # plt.show()
Output
We have 10 rows in the dataframe. When we execute the code, it will print the first 6 rows on the console because iloc[0:6] slices the first 6 rows from the dataframe.
a b c d e 0 1.826023 0.606137 0.389687 -0.497605 0.164785 1 0.571941 2.324981 -1.154445 0.757724 0.570713 2 -1.328481 1.248171 -0.849694 -1.133029 -0.977927 3 -0.509296 1.086251 0.809288 0.409166 -0.080694 4 0.973164 1.328212 0.858214 0.997309 -0.375427 5 1.014649 1.480790 -1.451903 -0.306659 -0.382312
To plot this sliced dataframe, uncomment the last line plt.show() in the code and execute it again.
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