2. Compatible Data Types#

  • We can use

    • Python lists

    • Numpy arrays

    • Pandas Series & Dataframes

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

2.1. Python lists#

plt.plot([1,2,3,4,5,])

[<matplotlib.lines.Line2D at 0x7f83203da3a0>]
../_images/565622fb94c4dcdecc2f6bc877d1c313d0e3d1f62b580aae8d1839ef22b3cc71.png

2.2. Numpy array#

plt.plot(np.array([1,2,3,4,5]))

[<matplotlib.lines.Line2D at 0x7f83180719a0>]
../_images/565622fb94c4dcdecc2f6bc877d1c313d0e3d1f62b580aae8d1839ef22b3cc71.png

2.3. Pandas Series#

plt.plot(pd.Series([1,2,3,4,5]))

[<matplotlib.lines.Line2D at 0x7f83181761c0>]
../_images/565622fb94c4dcdecc2f6bc877d1c313d0e3d1f62b580aae8d1839ef22b3cc71.png

2.4. Pandas Dataframe#

  • In case of Dataframe

    • Each column will be plotted as separate line

    • Index of Dataframe becomes x axis

col = [10,20,30,40,50]
df=pd.DataFrame(data=col)
df
0
0 10
1 20
2 30
3 40
4 50 
plt.plot(df)

[<matplotlib.lines.Line2D at 0x7f83181f7130>]
../_images/6de122f220b2fd4256801988519a48eb2e325a17848b4b0ce9d20916be0a9cb8.png