Pandas DataFrame | rfloordiv method
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Pandas DataFrame.rfloordiv(~) method performs integer division between a scalar, sequence, Series or DataFrame and the values in the source DataFrame, that is:
other // DataFrame
Note that this is the reverse of DataFrame.floordiv(~), which does the following:
DataFrame // other
Unless you use the parameters axis, level and fill_value, rfloordiv(~) is equivalent to performing division using the // operator.
Parameters
1. otherlink | scalar or sequence or Series or DataFrame
The resulting DataFrame will be other divided by the source DataFrame via integer division.
2. axislink | int or string | optional
Whether to broadcast other for each column or row of the source DataFrame:
Axis | Description |
|---|---|
|
|
|
|
Note that this is only relevant if the shape of the source DataFrame and that of other does not match up. By default, axis=1.
3. level | int or string | optional
The name or the integer index of the level to consider. This is relevant only if your DataFrame is Multi-index.
4. fill_valuelink | float or None | optional
The value to replace NaN before the computation. Note that if both pair of entries are NaN, then the result would still be NaN. By default, fill_value=None.
Return Value
A new DataFrame resulting from the integer division.
Examples
Basic usage
Consider the following DataFrame:
df = pd.DataFrame({"A":[1,2], "B":[3,4]})df_other = pd.DataFrame({"A":[5,6], "B":[7,8]})
A B | A B0 1 3 | 0 5 71 2 4 | 1 6 8
Performing integer division:
df.rfloordiv(df_other)
A B0 5 21 3 2
Here, we're performing the following element-wise integer division:
5//1 7//36//2 8//4
Note that this is equivalent to:
df_other // df
A B0 5 21 3 2
Broadcasting
Consider the following DataFrame:
df = pd.DataFrame({"A":[2,3], "B":[4,5]})df
A B0 2 41 3 5
Row-wise integer division
By default, axis=1, which means that other will be broadcasted for each row in df:
df.rfloordiv([7,8]) # axis=10
A B0 3 21 2 1
Here, we're performing the following element-wise integer division:
7//2 8//47//3 8//5
Column-wise integer division
To broadcast other for each column in df, set axis=0 like so:
df.rfloordiv([7,8], axis=0)
A B0 3 11 2 1
Here, we're performing the following element-wise division:
7//2 7//48//3 8//5
Specifying fill_value
Consider the following DataFrames:
df = pd.DataFrame({"A":[2,np.NaN], "B":[np.NaN,5]})df_other = pd.DataFrame({"A":[7,8],"B":[np.NaN,np.NaN]})
A B | A B0 2.0 NaN | 0 7 NaN1 NaN 5.0 | 1 8 NaN
By default, when we compute the integer division using rfloordiv(~), any operation with NaN results in NaN:
df.rfloordiv(df_other)
A B0 3.0 NaN1 NaN NaN
We can fill NaNs before we perform integer division by using the fill_value parameter:
df.rfloordiv(df_other, fill_value=2)
A B0 3.0 NaN1 2.0 0.0
Notice how if the integer division is between two NaN, then the result would always be NaN regardless of fill_value.
