Calculate mean of dataframe with missing data

Question

I have a data frame that has some cells with missing data that has inf instead. e.g:

a       b       c
2       3       4
2       3       inf

I want this result:

2        3       4

Is there a way to use the mean function or find the averages of the entire data frame.

BENY · Accepted Answer · 2021-01-20 01:50:18Z

1

Let us do it with mask inf to nan

df.mask(np.isinf(df)).mean()
Out[63]: 
a    2.0
b    3.0
c    4.0
dtype: float64

answered Jan 20, 2021 at 1:50

BENY

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Comments

Pablo C · Accepted Answer · 2021-01-20 02:01:27Z

1

Here's a solution without NumPy:

df.replace(float("inf"), float("nan")).mean(axis = 0)

You can also replace -inf and any other value:

df.replace([float("inf"), float("-inf")], float("nan")).mean(axis = 0)

answered Jan 20, 2021 at 2:01

Pablo C

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Jon S · Accepted Answer · 2021-01-20 01:46:07Z

0

np.nanmean(df,axis=0)

answered Jan 20, 2021 at 1:46

Jon S

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