Iterating over rows to find mean of a data frame in Python

Question

I have a dataframe of 100 random numbers and I would like to find the mean as follows:

mean0 should have mean of 0,5,10,... rows

mean1 should have mean of 1,6,11,16,.... rows

.

. mean4 should have mean of 4,9,14,... rows.

So far, I am able to find the mean0 but I am not able to figure out a way to iterate the process in order to obtain the remaining means.

My code is as follows:

import numpy as np
import pandas as pd
import csv

data = np.random.randint(1, 100, size=100)
df = pd.DataFrame(data)

print(df)

df.to_csv('example.csv', index=False)

df1 = df[::5]
print("Every 12th row is:\n",df1)

df2 = df1.mean()
print(df2)

Does this answer your question? Groupby certain number of rows pandas — Ignatius Reilly
– Ignatius Reilly, Commented Jul 8, 2022 at 17:42

7shoe · Accepted Answer · 2022-07-08 17:53:13Z

2

Since df[::5] is equivalent to df[0::5], you could use df[1::5], df[2::5], df[3::5], and df[4::5] for the remaining dataframes with subsequent application of mean by df[i::5].mean().

It is not explicitly showcased in the Pandas documentation examples but identical list slicing with [start:stop:step].

edited Jul 8, 2022 at 17:53

answered Jul 8, 2022 at 17:46

7shoe

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Comments

mozway · Accepted Answer · 2022-07-08 18:02:49Z

1

I would use the underlying numpy array:

df[0].to_numpy().reshape(-1, 5).mean(0)

output: array([40.8 , 52.75, 43.2 , 55.05, 47.45])

answered Jul 8, 2022 at 18:02

mozway

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5 Comments

A. Gehani Over a year ago

This gives me an error: raise KeyError(key) from err KeyError: 0 I don't understand why. Can you please help me?

mozway Over a year ago

Obviously, you should use the name of your column. In the provided example this was 0. If the name is 'col' -> df['col']...

A. Gehani Over a year ago

When I tried to run the command with the code given above, it gives me the desired results but when I used the same command with df= pd.read_csv('example.csv'), it gives me the error. I haven't changed the name of the column in both the cases. Can you help me to understand what is wrong here?

mozway Over a year ago

Use print(df.columns) to see the column names. If you have 0 use df[0], for '0' use df['0']. If you have a single column you can use positional indexing: df.iloc[:,0]. This is all basic pandas and had little to do with how my solution works. The pre-requisite is that you are able to select your column, and that the column contains a multiple of 5 elements.

A. Gehani Over a year ago

Thanks! I renamed the column and it worked perfectly for me. Thank you once again.

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