Python Matplotlib – first plot of "subplots" is slightly off

I’m facing a weird issue with Matplotlib’s subplots() method. I’ve got a Pandas Dataframe I want to plot that has 4 columns.

One option is to plot each column in a separate axis using plt.subplots():

import matplotlib.pyplot as plt
import pandas as pd


data = pd.read_csv("data.csv", sep="\t")

fig, axes = plt.subplots(4, 1, sharex=True)
for i, c in enumerate(data.columns):
    axes[i].plot(data[c], label=f"{c}")
    axes[i].legend()

plt.show()

which results in:

However, if I simply call plot() on the Dataframe directly:

data.plot()
plt.show()

I get this result:

Why does the first plot look slightly off compared to the other three when using plt.subplots(), whereas it looks perfectly aligned according to pd.DataFrame.plot()? Which one should I trust?

>Solution :

The range of your y-axis is very small on the first subplot, between -0.5 to 0.5, compared to the range on the other subplots [-20;20]. That would explain why you don’t see the shift when you plot the dataframe directly. There is no incompatibility here between your 2 plotting methods as far as I can tell.