The DataFrame.truediv() method in Python pandas
AKASH BAJWAThe pandas library and DataFrame
pandas is a data analysis software package in Python for manipulating data. This library contains the class DataFrame.
A pandas DataFrame is a 2D data structure organized in rows and columns in a tabular format. It allows us to store tabular data and perform various operations on data using methods. The three main components of pandas DataFrame are:
- Principal data — the data on which the methods are applied.
- Rows.
- Columns.
The DataFrame.truediv() method
Here, truediv() means true division, which means that the result will be float. The truediv() method will perform floating division on all elements of the DataFrame so that the resulting elements will be float even if they would otherwise be expected to be int.
Syntax
The below line demonstrates the syntax of truediv() method.
DataFrame.truediv(other, axis = 'columns', level = None, fill_value = None)
Parameters
The truediv() method takes one required parameter, while the other parameters are optional.
other: This is the divisor. It can be a list-like object or a data structure with a single or multiple elements. This is a required parameter.axis: This determines the axis on whichtruediv()will operate. If set to0or'index', it will operate on the index. When set to1or'columns', it will operate on columns. This is an optional parameter.level: This determines the level in the supplied MultiIndex on whichtruediv()will match index values. This is an optional parameterfill_value: This specifies the value which will replaceNaNvalues in the result. This can be a float value orNone.
Return value
The truediv() method will return a DataFrame with the intended results. All columns that truediv() operated on will contain float values.
Example one
In our first example, we will use truediv() on a DataFrame with a scalar passed in the other argument.
# importing pandas as pd
import pandas as pd
# Creating a dataframe with three observations
df= pd.DataFrame({"S":[360,50,10],
"T":[50,0,30],
"U":[70,70,0]})
# Print the dataframe
print(df, "\n")
#dividing each and every value by 4
print(df.truediv(other = 4))Explanation
- Line 2: We import the pandas library as
pd. - Lines 4–6: We create a
DataFramedfwith columnsS,T, andU. - Line 8: We print
df. - Line 10: We use
truediv()ondfwith4asother.
We find the following in the output:
- All elements in the resulting
DataFramehave been divided by 4. - All elements in the resulting
DataFrameare float.
Example two
In our second example, we will divide a DataFrame with a Python list passed in the other argument. We will also set axis to 'columns'.
Note:
'columns'is the default value foraxis.
# importing pandas as pd
import pandas as pd
# Creating a dataframe with three observations
df= pd.DataFrame({"S":[360,50,10],
"T":[50,0,30],
"U":[70,70,0]})
# Print the dataframe
print(df, "\n")
#dividing each and every value by 4
print(df.truediv(other = [20, 10, 50], axis='columns'))Explanation
- Line 2: We import the pandas library as
pd. - Lines 4–6: We create a
DataFramedfwith columnsS,T, andU. - Line 8: We print
df. - Line 10: We use
truediv()ondfwhereotheris a Python list with elements[20, 10, 50], and print the result.
We find the following in the output:
- Elements of the
DataFramedfhave been divided so that for every row, the first element has been divided with the first element of the listother, the second element has been divided with the second element of the listother, and so on. - All elements in the resulting
DataFrameare float.
Example three
In our third example, we will divide a DataFrame with a pandas series passed in the other argument. We will also set axis to 'index'.
Note: When using
truediv()withaxisset to'index', ensure thatotherhas the same number of indexes asdf.
# importing pandas as pd
import pandas as pd
# Creating a dataframe with three observations
df= pd.DataFrame({"A":[100,50,10],
"B":[50,20,30],
"C":[70,70,25]})
# Print the dataframe
print(df, "\n")
# subtracting with series type data
print(df.truediv(pd.Series([5, 10, 2], index=[0,1,2]), axis='index'))Explanation
- Line 2: We import the pandas library as
pd. - Lines 4–6: We create a
DataFramedfwith columnsA,B, andC. - Line 8: We print
df. - Line 10: We use
truediv()ondfwhereotheris a pandas series with elements[5, 10, 2], and print the result.
We find the following in the output:
- Elements of the
DataFramedfhave been divided so that for every column, the first element has been divided with the first element of the seriesother, the second element has been divided with the second element of the seriesother, and so on. - All elements in the resulting
DataFrameare float.
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