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pythonpandasdataframedata-analysis
Arpit Sharma
Arpit Sharma

Reputation: 365

Pandas : finding the average of values within a particular limit in a column

I have imported the first three columns of a .csv file named as Time, Test 1 and Test 2 in my python program. 

import pandas as pd
fields = ['Time', 'Time 1', 'Time 2']
df=pd.read_csv('file.csv', skipinitialspace=True, usecols=fields)

Here is the file which I imported in the program.

enter image description here

How can I make a function which finds the mean/average of the values in the Test 1 column between a given time limit? The time limits (starting and end values) are to be taken as the parameters in the function.

e.g., I want to find the average of the values in the column Test 1 from 0.50 seconds to 4.88 seconds. The limits (0.50 and 4.88) would be the function's parameter.

Upvotes: 1

Views: 2162

Answers (2)

N.Hung
N.Hung

Reputation: 154

You can use the between mask and mean, std function from numpy library.
For example: this line of code will estimate the mean of the Test 1 while it was taken between time 0.0 and 5.0: 

np.mean(df[df['Time'].between(0.0, 5.0)]['Test 1'])

Upvotes: 0

jezrael
jezrael

Reputation: 863301

I think need between for boolen mask, filter by boolean indexing and get mean:

def custom_mean(x,y):
    return df.loc[df['Time'].between(x,y), 'Test 1'].mean()

Sample:

df = pd.DataFrame({'Time':[0.0, 0.25, 0.5, 0.68, 0.94, 1.25, 1.65, 1.88, 2.05, 2.98, 3.45, 3.99, 4.06, 4.68, 4.88, 5.06, 6.0],
                   'Test 1':np.random.randint(10, size=17)})

print (df)
    Test 1  Time
0        3  0.00
1        6  0.25
2        5  0.50
3        4  0.68
4        8  0.94
5        9  1.25
6        1  1.65
7        7  1.88
8        9  2.05
9        6  2.98
10       8  3.45
11       0  3.99
12       5  4.06
13       0  4.68
14       9  4.88
15       6  5.06
16       2  6.00

def custom_mean(x,y):
    return df.loc[df['Time'].between(x,y), 'Test 1'].mean()

print (custom_mean(0.50, 1.0))
5.666666666666667

#verify
print (df.loc[df['Time'].between(0.50, 1.0), 'Test 1'])
2    5
3    4
4    8
Name: Test 1, dtype: int32

Upvotes: 3

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