If I have a Pandas DataFrame and want to calculate the median value for each column, it seems that the argument axis=1 should give the median by columns (according to the documentation). But in practice, axis=0 gives the column medians. Here is a simple replicable example:
import pandas as pd
my_data = [[1.1, 2.2, 3.3], [1.2, 2.3, 3.4], [1.3, 2.4, 3.5]]
df = pd.DataFrame(my_data)
print(df.head())
print("\nTry to calculate median with axis=1\n")
print(df.median(axis=1))
It is showing the median by row. Changing it to axis=0 shows the median by column. Does this have to do with the way that the index is set for the DataFrame?
It does what it is supposed to do, axis = 1 means to apply the function each row. You can see from this other example
>>> print(df.sum(axis = 1))
0 6.6
1 6.9
2 7.2
dtype: float64
Or equivalently
>>> print(df.apply(sum, axis = 1))
0 6.6
1 6.9
2 7.2
dtype: float64
and you can see in the documentation
axis : {0 or ‘index’, 1 or ‘columns’}, default 0
Axis along which the function is applied:
0 or ‘index’: apply function to each column.
1 or ‘columns’: apply function to each row.
So if you want to calculate the mean of each row column you should use axis = 0