How to plot different column of a Pandas data frame with different marker, using pandas.plot() function?

Question

I have a pandas data frame with 5 different column. I want to plot them with different color, lable, and marker for each column. I manage to make a different color and different label for each column, by passing a list of colors/label for each column. However this does not work for the marker. Any idea on how to do it? Here is the code example:


ds # a pandas data frame with 3 columns

list_label=['A','B','C']
list_color=['tab:red','tab:green','tab:blue']
list_marker=['o','s','v']

ds.plot(color=list_color, label=list_label, marker=list_marker)

The later line produce an error like AttributeError: 'Line2D' object has no property 'list_marker'

ALollz · Accepted Answer · 2020-01-24 16:38:13Z

3

Plot each Series separately on the same figure so you can specify the correct marker.

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

df = pd.DataFrame(np.random.randint(1, 10, (10, 3)))
list_label=['A', 'B', 'C']
list_color=['tab:red', 'tab:green', 'tab:blue']
list_marker=['o', 's', 'v']

fig, ax = plt.subplots()

for i, col in enumerate(df):
    df[col].plot(color=list_color[i], marker=list_marker[i], label=list_label[i], ax=ax)

plt.legend()    
plt.show()

answered Jan 24, 2020 at 16:38

ALollz

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1 Comment

BayesianMonk Over a year ago

Thanks for the idea! But I was wondering if there was a solution without using a loop, as it can be done for the color or the label keyword.

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