sklearn error ValueError: Input contains NaN, infinity or a value too large for dtype('float64')

This might happen inside scikit, and it depends on what you're doing. I recommend reading the documentation for the functions you're using. You might be using one which depends e.g. on your matrix being positive definite and not fulfilling that criteria.

EDIT: How could I miss that:

np.isnan(mat.any()) #and gets False
np.isfinite(mat.all()) #and gets True

is obviously wrong. Right would be:

np.any(np.isnan(mat))

and

np.all(np.isfinite(mat))

You want to check wheter any of the element is NaN, and not whether the return value of the any function is a number...

I got the same error message when using sklearn with pandas. My solution is to reset the index of my dataframe df before running any sklearn code:

df = df.reset_index()

I encountered this issue many times when I removed some entries in my df, such as

df = df[df.label=='desired_one']

This is my function (based on this) to clean the dataset of nan, Inf, and missing cells (for skewed datasets):

import pandas as pd
import numpy as np

def clean_dataset(df):
    assert isinstance(df, pd.DataFrame), "df needs to be a pd.DataFrame"
    df.dropna(inplace=True)
    indices_to_keep = ~df.isin([np.nan, np.inf, -np.inf]).any(1)
    return df[indices_to_keep].astype(np.float64)