Compute row average in pandas
Solution 1:
You can specify a new column. You also need to compute the mean along the rows, so use axis=1
.
df['mean'] = df.mean(axis=1)
>>> df
Y1961 Y1962 Y1963 Y1964 Y1965 Region mean
0 82.567307 83.104757 83.183700 83.030338 82.831958 US 82.943612
1 2.699372 2.610110 2.587919 2.696451 2.846247 US 2.688020
2 14.131355 13.690028 13.599516 13.649176 13.649046 US 13.743824
3 0.048589 0.046982 0.046583 0.046225 0.051750 US 0.048026
4 0.553377 0.548123 0.582282 0.577811 0.620999 US 0.576518
Solution 2:
We can find the the mean of a row using the range function, i.e in your case, from the Y1961 column to the Y1965
df['mean'] = df.iloc[:, 0:4].mean(axis=1)
And if you want to select individual columns
df['mean'] = df.iloc[:, [0,1,2,3,4].mean(axis=1)
Solution 3:
I think this is what you are looking for:
df.drop('Region', axis=1).apply(lambda x: x.mean(), axis=1)