4 examples of 'remove nan from dataframe' in Python

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86def df_nan_col_removed(self, df_with_nan):
87 df = df_with_nan
88 df["timestamp"] = df.index * 1000
89 col_removed_df, mask = preprocessing.remove_nan_columns(df)
90 return col_removed_df, mask
19def fill_missing_values(df_data):
20 """Fill missing values in data frame, in place."""
21 df_data.fillna(method="ffill", inplace="True")
22 df_data.fillna(method='bfill', inplace="True")
88def normalize(dataframe):
89 """Centers and scales each column in the data frame to zero mean and unit variance.
91 Args:
92 dataframe (pandas.DataFrame): Input dataframe.
94 Returns:
95 pandas.DataFrame: Normalized dataframe.
96 """
97 dataframe = dataframe.set_index("timestamp")
98 dataframe = (dataframe - dataframe.mean()) / dataframe.std()
99 return dataframe.reset_index()
259def drop_some(df_: pd.DataFrame, thresh: int) -> pd.DataFrame:
260 # thresh is the minimum number of NA, the 1 indicates that columns should be dropped not rows
261 return df_.dropna(1, thresh=thresh)

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