Python is a great language for doing data analysis, primarily because of the fantastic ecosystem of data-centric python packages. Pandas is one of those packages and makes importing and analyzing data much easier.
Pandas DataFrame.plot.bar()
plots the graph vertically in form of rectangular bars.
Syntax : DataFrame.plot.bar(x=None, y=None, **kwds)
Parameters:
x : (label or position, optional) Allows plotting of one column versus another. If not specified, the index of the DataFrame is used.
y : (label or position, optional) Allows plotting of one column versus another. If not specified, all numerical columns are used.
**kwds : Additional keyword argumentsReturns: matplotlib.axes.Axes or np.ndarray of them
Example #1: Using DataFrame.plot.bar()
to plot the graph vertically in form of rectangular bars
# importing matplotlib import matplotlib.pyplot # importing pandas as pd import pandas as pd # importing numpy as np import numpy as np # creating a dataframe df = pd.DataFrame(np.random.rand( 10 , 3 ), columns = [ 'a' , 'b' , 'c' ]) print (df) |
Now we will use a function DataFrame.plot.bar()
to plot a graph vertically in form of rectangular bars
# using a function df.plot.bar() df.plot.bar() |
Output:
Example #2: Using DataFrame.plot.bar()
to plot the graph vertically in form of rectangular bars.
# importing matplotlib import matplotlib.pyplot # importing pandas as pd import pandas as pd # importing numpy as np import numpy as np # creating a dataframe df = pd.DataFrame(np.random.rand( 10 , 10 ), columns = [ 'a' , 'b' , 'c' , 'd' , 'e' , 'f' , 'g' , 'h' , 'i' , 'j' ]) df |
Now we will use a function DataFrame.plot.bar()
to plot a graph vertically in form of rectangular bars
# using a function df.plot.bar() df.plot.bar() |
Output :
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