How to use the finmarketpy.economics.EventStudy function in finmarketpy

# fetch NFP times from Bloomberg
    md_request = MarketDataRequest(
        start_date=start_date,              # start date
        finish_date=finish_date,            # finish date
        category="events",
        freq='daily',                       # daily data
        data_source='bloomberg',            # use Bloomberg as data source
        tickers=['NFP'],
        fields=['release-date-time-full'],  # which fields to download
        vendor_tickers=['NFP TCH Index'],   # ticker (Bloomberg)
        cache_algo='internet_load_return')  # how to return data

    df_event_times = market.fetch_market(md_request)
    df_event_times = pandas.DataFrame(index=df_event_times['NFP.release-date-time-full'])

    es = EventStudy()

    # work out cumulative asset price moves moves over the event
    df_event = es.get_intraday_moves_over_custom_event(df, df_event_times)

    # create an average move
    df_event['Avg'] = df_event.mean(axis=1)

    # plotting spot over economic data event
    style = Style()
    style.scale_factor = 3
    style.file_output = 'usdjpy-nfp.png'

    style.title = 'USDJPY spot moves over recent NFP'

    # plot in shades of blue (so earlier releases are lighter, later releases are darker)
    style.color = 'Blues';