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 ?
CodePudding user response:
I would say that the easiest way would be to use the
CodePudding user response:
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"})