# remove 0 values from dataframe

df.loc[~(df==0).all(axis=1)]

**Here is what the above code is Doing:**

1. df.loc[~(df==0).all(axis=1)]

– This is a boolean mask that will return True for all rows that have at least one non-zero value.

– The ~ is a bitwise operator that inverts the True/False values.

– The .all(axis=1) is a boolean method that returns True if all values in a row are True.

– The .loc[] is a pandas method that allows you to select rows and columns by label.

2. df.loc[~(df==0).all(axis=1)] = np.nan

– This replaces all rows that have at least one non-zero value with NaN.