I am writing a function and passing a nested list to it. The goal is to find the mean of the each nested list. For eg. if the below is the input
[[1914.05004882812], [1930.65002441406, 1934.5]]
I want the output to be like the below, mean of each individual list.
[1914.05004883 1932.57501221]
This works for some, but for some values I am getting the nested list as it is. Below is the function and the output. can you please let me know what have I done wrong here? I am learning python and please excuse me if the terminologies I used are incorrect. I am using google colab to test this.
def groupmeancalc(groups):
print('type of group is ' + str(type(groups)))
print(groups)
print('size of group is ' + str(len(groups)))
if len(groups)==1:
nparrr=np.array(groups)
nparr=np.mean(nparrr)
print('Below are the values')
print(nparr)
else:
nparrr=np.array(groups)
nparr=np.vectorize(np.mean)(nparrr)
print('Below are the values')
print(nparr)
Below are the outputs that are coming as expected.
type of group is <class 'list'>
[[1918.80004882812], [1938.69995117188, 1940.05004882812]]
size of group is 2
Below are the values
[1918.80004883 1939.375 ]
type of group is <class 'list'>
[[5510.2001953125, 5519.9501953125], [5545.10009765625]]
size of group is 2
Below are the values
[5515.07519531 5545.10009766]
Below is where I am not getting the expected output. Here you can see the nested list is not flattened, and wherever 2 or more elements are present, mean is not calculated.
type of group is <class 'list'>
[[1355.59997558594], [1363.0], [1372.05004882812]]
size of group is 3
Below are the values
[[1355.59997559]
[1363. ]
[1372.05004883]]
type of group is <class 'list'>
[[1349.15002441406, 1351.5], [1358.90002441406, 1359.0]]
size of group is 2
Below are the values
[[1349.15002441 1351.5 ]
[1358.90002441 1359. ]]
If you need a list as output, I think map will work:
def map_f(x):
return list(map(np.mean,x))
Try:
map_f([[1914.05004882812], [1930.65002441406, 1934.5]])
[1350.3250122070299, 1358.9500122070299]
map_f([[1349.15002441406, 1351.5], [1358.90002441406, 1359.0]])
[1350.3250122070299, 1358.9500122070299]
map_f([[1355.59997558594], [1363.0], [1372.05004882812]])
[1355.59997558594, 1363.0, 1372.05004882812]