Mean of several rows in pandas dataframe

Question

I have a rather big dataframe for my calculation method (SSA) - about 80000 rows. I'd like to average my data by several rows (20 for example). How can I do this?

I have a dataframe, for example:

 1. 00h         03h         06h         09h         12h
10  0.003546    0.000885    0.006852    0.00171     0.001708
11  0.00667     0.012603    0.012933    0.05603     0.025855
12  0.089116    0.054549    0.022177    0.090342    0.070226
13  0.28974     0.246415    0.297231    0.399953    0.287122

And in the end, I'd like something like this:

this

How can I do this?

jezrael · Accepted Answer · 2020-01-08 13:07:24Z

1

Use integer division by range created by length of DataFrame with numpy.arange and aggregate mean:

df = df.groupby(np.arange(len(df))//2).mean()
print (df)

        00h       03h       06h       09h       12h
0  0.005108  0.006744  0.009893  0.028870  0.013782
1  0.189428  0.150482  0.159704  0.245147  0.178674

answered Jan 8, 2020 at 13:07

jezrael

868k103 gold badges1.4k silver badges1.3k bronze badges

Sign up to request clarification or add additional context in comments.

1 Comment

Misha Over a year ago

And in the case of 80000 rows and 20ty-row averaging, I should use df = df.groupby(np.arange(len(df))//20).mean() ?

Collectives™ on Stack Overflow

Mean of several rows in pandas dataframe

1 Answer 1

1 Comment

Your Answer

Hot Network Questions

Collectives™ on Stack Overflow

1 Answer 1

1 Comment

Your Answer

Sign up or log in

Post as a guest

Related