4 examples of 'remove nan from dataframe' in Python

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@pytest.fixture
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def df_nan_col_removed(self, df_with_nan):
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    df = df_with_nan
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    df["timestamp"] = df.index * 1000
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    col_removed_df, mask = preprocessing.remove_nan_columns(df)
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    return col_removed_df, mask

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def fill_missing_values(df_data):
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    """Fill missing values in data frame, in place."""    
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    df_data.fillna(method="ffill", inplace="True")
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    df_data.fillna(method='bfill', inplace="True")

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def normalize(dataframe):
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    """Centers and scales each column in the data frame to zero mean and unit variance.
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    Args:
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        dataframe (pandas.DataFrame):  Input dataframe.
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    Returns:
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        pandas.DataFrame: Normalized dataframe.
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    """
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    dataframe = dataframe.set_index("timestamp")
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    dataframe = (dataframe - dataframe.mean()) / dataframe.std()
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    return dataframe.reset_index()

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def drop_some(df_: pd.DataFrame, thresh: int) -> pd.DataFrame:
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    # thresh is the minimum number of NA, the 1 indicates that columns should be dropped not rows
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    return df_.dropna(1, thresh=thresh)