How to show different colors on a plot for values from different columns

Question

Please consider the small dataframe test:

import pandas as pd
import matplotlib.pyplot as plt

df = pd.DataFrame(
         [
             [1, 1.0, 0.0, 0.0],
             [1, 0.75, 0.25, 0.0],
             [1, 0.576, 0.396, 0.028]
         ],
         columns = ["State", "1", "2", "3"]
    )

I am now plotting the 3 last columns by:

fig = plt.figure()
ax = plt.subplot()

ax.plot(df[["1","2","3"]], label = ["1 (from 1)","2 (from 1)","3 (from 1)"], 
        color = "red", marker = ".", linestyle="-")
ax.legend(loc='center left', bbox_to_anchor=(1, 0.5),
          fancybox=True, shadow=True)
plt.show()

What would be the easiest way to show a different color for each column of data, such as "red" for column 1, "blue" for column 2 and green for column 3 ?

Asked By: Andrew

||

Source

Answer 1

I would say that the easiest way would be to use the pandas built-in plot.

Otherwise, you need to loop :

fig, ax = plt.subplots()

colors = ["red", "blue", "green"]
labels = ["1 (from 1)","2 (from 1)","3 (from 1)"]

for idx, col in enumerate(["1", "2", "3"]):
    ax.plot(df[col], label=labels[idx], color=colors[idx], marker=".", linestyle="-")

ax.legend(loc="center left", bbox_to_anchor=(1, 0.5),
          fancybox=True, shadow=True)
plt.show();

Output :

Answered By: Timeless

Answer 2

You can also use .plot.line():

df1 = df[["1","2","3"]]
axes = df1.plot.line(subplots=False, color={"1": "red", "2": "blue", "3":"green"})

or .plot(style={})

axes = df1.plot(style={"1": "*:r", "2": "-.b", "3":"+--g"})

Answered By: Hermann12

How to show different colors on a plot for values from different columns

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