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Solve the following problem using Python, implementing the functions described below, one line at a time
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Description:
 def import_series_from_dataframe(network, dataframe, cls_name, attr):
 """ Import time series from a pandas DataFrame. Parameters dataframe : pandas.DataFrame cls_name : string Name of class of component attr : string Name of series attribute Examples -------- """


    df = network.df(cls_name)
    pnl = network.pnl(cls_name)
    list_name = network.components[cls_name]["list_name"]

    diff = dataframe.columns.difference(df.index)
    if len(diff) > 0:
        logger.warning("Components {} for attribute {} of {} are not in main components dataframe {}".format(diff,attr,cls_name,list_name))

    attr_series = network.components[cls_name]["attrs"].loc[attr]
    columns = dataframe.columns

    diff = network.snapshots.difference(dataframe.index)
    if len(diff):
        logger.warning("Snapshots {} are missing from {} of {}. Filling with default value '{}'".format(diff,attr,cls_name,attr_series["default"]))
        dataframe = dataframe.reindex(network.snapshots, fill_value=attr_series["default"])

    if not attr_series.static:
        pnl[attr] = pnl[attr].reindex(columns=df.index|columns, fill_value=attr_series.default)
    else:
        pnl[attr] = pnl[attr].reindex(columns=(pnl[attr].columns | columns))

    pnl[attr].loc[network.snapshots, columns] = dataframe.loc[network.snapshots, columns]