How to useastype() function in Python Pandas
Syntax:
df['column_name']= df['column_name'].astype(data_type)
where, df is the input dataframe
Example:
Python3
# importing pandas import pandas as pd # importing numpy import numpy as np # importing matplotlib.pyplot import matplotlib.pyplot as plt petal_length = [ '3.3' , '3.5' , '4.0' , '4.5' , '4.6' , '5.0' , '5.5' , '6.0' , '6.5' , '7.0' ] petal_width = [ '3.6' , '3.8' , '4.4' , '6.6' , '6.8' , '7.0' , '7.5' , '8.0' , '8.5' , '8.9' ] df = pd.DataFrame({ 'petal_length(cm)' : petal_length, 'petal_width(cm)' : petal_width}) df[ 'petal_length(cm)' ] = df[ 'petal_length(cm)' ].astype( float ) df[ 'petal_width(cm)' ] = df[ 'petal_width(cm)' ].astype( float ) df.plot(x = 'petal_length(cm)' , y = 'petal_width(cm)' ) plt.show() |
Output:
How to Fix: TypeError: no numeric data to plot
In this article, we will fix the error: TypeError: no numeric data to plot
Cases of this error occurrence:
Python3
# importing pandas import pandas as pd # importing numpy import numpy as np import matplotlib.pyplot as plt petal_length = [ '3.3' , '3.5' , '4.0' , '4.5' , '4.6' , '5.0' , '5.5' , '6.0' , '6.5' , '7.0' ] petal_width = [ '3.6' , '3.8' , '4.4' , '6.6' , '6.8' , '7.0' , '7.5' , '8.0' , '8.5' , '8.9' ] df = pd.DataFrame({ 'petal_length(cm)' : petal_length, 'petal_width(cm)' : petal_width}) df.plot(x = 'petal_length(cm)' , y = 'petal_width(cm)' ) plt.show() |
Output:
TypeError: no numeric data to plot
Reason for the error :
Plotting can be done only on numeric data when we plot the data with datatype different that numeric data this error raises. To know whether the data types are numeric or not we can know it by using the function dtypes().
print(df.dtypes)
The data that we use to plot must be numeric.
Fixing the error:
This error can be fixed by converting the data to be plotted into numeric data. To convert the data to numeric data we can use the functions astype() or to_numeric().
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