Python Pandas Series mod() Function

Python Pandas Series mod() Function

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Pandas Series mod() Function:

The mod() method of the Pandas returns the element-wise modulo of series and other. It’s the same as series%other, except with the ability to include a fill_value as one of the arguments to fill in missing data.

Syntax:

Series.mod(other, level=None, fill_value=None)

Parameters

other: This is required. It indicates a Series or a scalar value.

level: This is optional. To broadcast over a level, specify an int or a name that matches the Index values on the passed MultiIndex level. The type of this may be int or name. None is the default value.

fill_value: This is optional. It indicates a value to fill in any current missing (NaN) values, as well as any new elements required for successful Series alignment. The result will be missing if data is missing in both corresponding Series locations. The type of this may be float or None. None is the default value.

Return Value:

The result of the arithmetic operation is returned.

Pandas Series mod() Function in Python

Example1

Approach:

  • Import pandas module using the import keyword.
  • Pass some random list as an argument to the Series() function of the pandas module to create a series.
  • Store it in a variable.
  • Print the above-given series.
  • Apply mod() function on all the elements of the given series by passing some random number to it to get the modulus values and print the result.
  • Here it gives the remainder when all the elements of the given series divided by 5
  • The Exit of the Program.

Below is the implementation:

# Import pandas module using the import keyword.
import pandas as pd
# Pass some random list as an argument to the Series() function
# of the pandas module to create a series.
# Store it in a variable.
gvn_series = pd.Series([12, 25, 34, 45, 82])
# Print the above given series
print("The given series is:")
print(gvn_series)
print()
# Apply mod() function on all the elements of the given series
# by passing some random number to it to get the modulus values and print the result.
# Here it gives the remainder when all the elements of the given series divided by 5
print("The modulus of all the elements of the given series when divided by 5:")
print(gvn_series.mod(5))

Output:

The given series is:
0    12
1    25
2    34
3    45
4    82
dtype: int64

The modulus of all the elements of the given series when divided by 5:
0    2
1    0
2    4
3    0
4    2
dtype: int64

Example2

Approach:

  • Import pandas module using the import keyword.
  • Import numpy module using the import keyword.
  • Pass some random list, index values as the arguments to the Series() function of the pandas module to create a series.
  • Store it in a variable.
  • Similarly, Pass some random list, index values as the arguments to the Series() function of the pandas module to create another series.
  • Store it in another variable.
  • Print the above first given series
  • Print the above second given series
  • Pass the given second series and fill_value as some random number as the arguments to the mod() function and apply it to the first series and print the series.
  • Here, each element of the first series will get divided by the corresponding element of the second series by filling NaN values with the given fill_value and returning the remainder of it.
  • The Exit of the Program.

Below is the implementation:

# Import pandas module using the import keyword.
import pandas as pd
# Import numpy module using the import keyword.
import numpy as np
# Pass some random list, index values as the arguments to the 
# Series() function of the pandas module to create a series.
# Store it in a variable.
gvn_series1 = pd.Series([41, 24, 32, np.NaN], 
              index=['P', 'Q', 'R', 'S'])
# Similarly, Pass some random list, index values as the arguments to the 
# Series() function of the pandas module to create another series.
# Store it in another variable.
gvn_series2 = pd.Series([5, 6, np.NaN, 2], 
              index=['P', 'Q', 'R', 'S'])
# Print the above first given series
print("The given first series is:")
print(gvn_series1)
print()
# Print the above second given series
print("The given second series is:")
print(gvn_series2)
print()
# Pass the given second series and fill_value as some random number as the 
# arguments to the mod() function and apply it to the first series.
# Here, each element of the first series will get divided by the corresponding element
# of the second series by filling NaN values with the given fill_value and 
# returning the remainder of it.
print("The remainder when dividing firstseries by corresponding elements of secondseries:")
print(gvn_series1.mod(gvn_series2, fill_value=10))

Output:

The given first series is:
P    41.0
Q    24.0
R    32.0
S     NaN
dtype: float64

The given second series is:
P    5.0
Q    6.0
R    NaN
S    2.0
dtype: float64

The remainder when dividing firstseries by corresponding elements of secondseries:
P    1.0
Q    0.0
R    2.0
S    0.0
dtype: float64

Example3

Approach:

  • Import pandas module using the import keyword.
  • Pass some random key-value pair(dictionary) as arguments to the DataFrame() function of the pandas module to create a dataframe.
  • Store it in a variable.
  • Print the given dataframe
  • Floor Divide the column gvn_list1 by gvn_list2 using the floordiv() function and store it as a new column in the dataframe.
  • Print the dataframe after adding a new column(gvn_list1//gvn_list2).
  • The Exit of the Program.

Below is the implementation:

# Import pandas module using the import keyword.
import pandas as pd
# Pass some random key-value pair(dictionary) as arguments to the 
# DataFrame() function of the pandas module to create a dataframe
# Store it in a variable.
data_frme  = pd.DataFrame({
  "gvn_list1": [45, 24, 54, 90],
  "gvn_list2": [5, 7, 6, 4]
})
# Print the given dataframe
print("The given Dataframe:")
print(data_frme)
print()

# Get the modulus(remainder) values when column gvn_list1 divided by gvn_list2 
# using the mod() function and store it as a new column in the dataframe.
data_frme ['Modulus(remainder)'] = data_frme ['gvn_list1'].mod(data_frme ['gvn_list2'])
# Print the dataframe after adding a new column( modulus(remainder))
print("The dataframe after adding a new column(modulus(remainder)):")
print(data_frme )

Output:

The given Dataframe:
   gvn_list1  gvn_list2
0         45          5
1         24          7
2         54          6
3         90          4

The dataframe after adding a new column(modulus(remainder)):
   gvn_list1  gvn_list2  Modulus(remainder)
0         45          5                   0
1         24          7                   3
2         54          6                   0
3         90          4                   2