Pandas plot line with different line styles?

Question

I am plotting several lines on the same plot, using the ggplot style. With this style, the lines become all solid lines. So the visibility is not good. How can I change each line to have different styles, e.g., one with dashed lines, or something?

import pandas as pd
import matplotlib.pyplot as plt
plt.style.use('ggplot')

fig,ax = plt.subplots(figsize=(15,5))
ax.set_title('Loss curve', fontsize=15)
ax.set_ylabel('Loss')
ax.set_xlabel('Epoch')
df1.plot.line(ax=ax,x='epoch',y=["train_loss"])
df2.plot.line(ax=ax,x='epoch',y=["train_loss"])
plt.show()

Pass linestyle='--' to the plot command? Other line styles here. — Quang Hoang
– Quang Hoang, Commented Oct 20, 2021 at 20:31
This thread is what you looking for --> stackoverflow.com/questions/16320148/… — Maximilian Freitag
– Maximilian Freitag, Commented Oct 20, 2021 at 20:36

AfterFray · Accepted Answer · 2021-10-22 04:28:43Z

6

You can use linestyle to change each line with different styles.

Here is an example :

import pandas as pd
import matplotlib.pyplot as plt
plt.style.use('ggplot')

fig,ax = plt.subplots(figsize=(15,5))
ax.set_title('Loss curve', fontsize=15)
ax.set_ylabel('Loss')
ax.set_xlabel('Epoch')

df1 = pd.DataFrame({'epoch' : [10,20,30,40,50,60],
                    'train_loss' : [6,5,4,3,2,1]})

df2 = pd.DataFrame({'epoch' : [10,20,30,40,50,60],
                    'train_loss' : [6.5,5.5,4.5,3.5,2.5,1.5]})

df1.plot.line(ax=ax,x='epoch',y=["train_loss"], 
              linewidth= 1.5, linestyle='-.')
df2.plot.line(ax=ax,x='epoch',y=["train_loss"], linewidth= 1.5,
              linestyle='-')
plt.show()

The above code will show the graph as following :

At plt.plot.line(), you can check more styles as solid, dash, dash-dot, dotted, and etc.

answered Oct 22, 2021 at 4:28

AfterFray

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Comments

lehalle · Accepted Answer · 2024-10-29 12:31:53Z

0

simple give a list in the style property of the lines, like in

f_int_df = pandas.DataFrame(f_int_lst)
f_int_df['ds_pos'] = -F(q0, s_pos, alpha=alpha, gamma=gamma)
f_int_df.set_index('s')[['sum', 'ds_pos']].plot(
    figsize=(4,2), lw=3, grid=True, 
    style=['-', '--'], 
    title="$\propto\int_{q_0\wedge(q_0-s)}^\infty (1+a)^{-3} (1+a+s)^{-3}\, da$"
)

that gives (focus on the style=['-', '--'] line of code):

answered Oct 29, 2024 at 12:31

lehalle

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