The error is reproducible if the array is of dtype=object:

import numpy  as np

label0 = np.random.random((50, 3)).astype(object)
np.cov(label0, rowvar=False)

AttributeError: 'float' object has no attribute 'shape'

If possible you should convert it to a numeric type. For example:

np.cov(label0.astype(float), rowvar=False)  # works

Note: object arrays are rarely useful (they are slow and not all NumPy functions deal gracefully with these - like in this case), so it could make sense to check where it came from and also fix that.

Check the Pandas documentation, but I think

X_train = df_train.drop(['ID','TARGET'], axis=1).values

.values returns a numpy array, not a Pandas dataframe. An array does not have a columns attribute.

remove_features_identical - if you pass this an array, make sure you are only using array, not dataframe, features. Otherwise, make sure you pass it a dataframe. And don't use variable names like DataFrame.

This function is expecting a pandas DataFrame or Series but is getting a numpy ndarray.

You are using the right method but in a wrong way :)

nan_to_num is a method of numpy module, not numpy.ndarray. So instead of calling nan_to_num on you data, call it on numpy module giving your data as a paramter:

import numpy as np
data = np.array([1,2,3,np.nan,np.nan,5])
data_without_nan = np.nan_to_num(data)

prints:

array([1., 2., 3., 0., 0., 5.])

In your example:

import numpy as np
val = np.nan_to_num(setTo.ravel())

Using .values on a pandas dataframe gives you a numpy array. This will not contain column names and such. You do this when setting X like this:

X = dataset[['Read?', 'x1', .. ,'x47']].values 

But then you try to get the column names from X (which it does not have) by writing X.columns here:

coeff_df = pd.DataFrame(regressor.coef_, X.columns, columns=['Coefficient'])

So store your column names in a variable or input them again, like this:

coeff_df = pd.DataFrame(regressor.coef_, ['Read?', 'x1', .. ,'x47'], columns=['Coefficient'])

Given that numpy.ndarray is the Python type of "numpy arrays", the error is just saying that arrays don't have a diff method. diff is a function defined in the numpy module.

Instead of np.log(close_prices).diff(), do

np.diff(np.log(close_prices))