I want to plot two DataFrame in a single plot.Though, I have seen similar post but none seems to work out.

First 5 rows of my dataframe looks like this:

df1

    name    type        start       stop    strand
0   geneA   transcript  2000        7764        +
1   geneA   exon        2700        5100        +
2   geneA   exon        6000        6800        +
3   geneB   transcript  9000        12720       -
4   geneB   exon        9900        10100       -

df2

    P1      P2       P3      P4
0   0.28    0.14    0.19    0.19
1   0.30    0.16    0.17    0.20
2   0.26    0.13    0.20    0.12
3   0.21    0.13    0.25    0.15
4   0.31    0.03    0.24    0.20

I want the plot to look like this:

I tried doing this:

import pandas as pd
import matplotlib.pyplot as plt
import numpy as np

ax = df1.plot()df1.plot(ax=ax)

but, the output was not meaningful. I will appreciate suggestions/solutions on how to achieve this.

Here is a minimal example:

import matplotlib.pyplot as pltf, axes = plt.subplots(nrows=len(df2.columns)+1, sharex=True, )# plots for df2 columns
i = 0
for col in df2.columns:df2[col].plot(ax=axes[i])axes[i].set_ylim(0, 1.2)axes[i].set_ylabel(col)i+=1## code to plot annotations
# axes[-1].plot(…)
axes[-1].set_xlabel('Genomic position')# remove space between plots
plt.subplots_adjust(hspace=0)

Here is the full graph:

f, axes = plt.subplots(nrows=len(df2.columns)+1, sharex=True, )# plots for df2 columns
i = 0
for col in df2.columns:df2[col].plot(ax=axes[i], color='#505050')axes[i].set_ylim(0, 1.3)axes[i].set_ylabel(col)i+=1## code to plot annotations
axes[-1].set_xlabel('Genomic position')
axes[-1].set_ylabel('annotations')
axes[-1].set_ylim(-0.5, 1.5)
axes[-1].set_yticks([0, 1])
axes[-1].set_yticklabels(['−', '+'])for _, r in df1.iterrows():marker = '|'lw=1if r['type'] == 'exon':marker=Nonelw=8y = 1 if r['strand'] == '+' else 0axes[-1].plot((r['start'], r['stop']), (y, y),marker=marker, lw=lw,solid_capstyle='butt',color='#505050')# remove space between plots
plt.subplots_adjust(hspace=0)