Why 'Mode()[0]', Not Just 'Mode()?

Q&A DQ Courses
#1

In 7/9 stats Module of "mode. The output of mode : 0 6. Here, is that true? 0 refers to index and 6 is the mode value?

my original code " houses[‘Mo Sold’].mode() " did not work.
The error says ValueError: The truth value of a Series is ambiguous. Use a.empty, a.bool(), a.item(), a.any() or a.all().
Only I changed the code as the solution’s— mode()[0], then it works.

image

I did notice in our FAQ discussion forum, someone asked the same question and whoever gave the answer didn’t clarify my confusion. Do we always have to have mode()[0]? I checked geeksforgeeks or other documentation, it didn’t suggest mode()[0].

image

#2

Reading the documentation

import pandas as pd
help(pd.Series.mode)

mode(self, dropna=True)
    Return the mode(s) of the dataset.
    
    Always returns Series even if only one value is returned.
    
    Parameters
    ----------
    dropna : bool, default True
        Don't consider counts of NaN/NaT.
    
        .. versionadded:: 0.24.0
    
    Returns
    -------
    Series
        Modes of the Series in sorted order.

x = houses["Mo Sold"].mode()

.mode() returns a series regardless whether one value is returned.

The series for houses["Mo Sold"].mode():

\begin{array}{|c|c|} \hline - & 0 \\ \hline 0 & 6\\ \hline \end{array}

houses["Mo Sold"].mode()[0] returns the single value in the series.

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#3

There can be multiple modes.

x = [1, 1, 1, 1, 2, 2, 2, 2, 3, 3, 3, 3]

Then there will be three modes with frequency 4 - 1, 2, and 3.

>>> import pandas as pd

Sample Series data:

>>> s = pd.Series([1, 1, 1, 1, 2, 2, 2, 2, 3, 3, 3, 3])

>>> s
0     1
1     1
2     1
3     1
4     2
5     2
6     2
7     2
8     3
9     3
10    3
11    3
dtype: int64

Using .mode:

>>> x = s.mode()
>>> x
0    1
1    2
2    3
dtype: int64

Retrieving multiple modes:

>>> x[0]
1
>>> x[1]
2
>>> x[2]
3
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#4

@alvinctk Thank you for your explanation. It does explain this question very well. But here comes a new question.
So the output(in my picture) of "print(mode) is 0 and 6 means what? two modes or 0 refers to index and 6 is mode?

image

I am confused of this picture you showed me. Is it a series or an array? 0 on the top right means column index and 0 on the bottom left means row indexing?

I did notice in stats course, I have to be careful of differentiating list/array and series because they represent different way to write the function. eg .series.sum() or sum(array).

#5

0 is just to indicate the indexes. It is a series.
You can see it on dataquest variable checker.
x = houses["Mo Sold"].mode()

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