Removed .ix

cuemacro · Aug 24, 2020 · d3c3084 · d3c3084
1 parent 543dfba
commit d3c3084
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Showing 6 changed files with 40 additions and 31 deletions.
diff --git a/README.md b/README.md
@@ -104,6 +104,7 @@ In finmarketpy/examples you will find several examples, including some simple tr
 
 # Release Notes
 
+* 0.11.5 - finmarketpy (24 Aug 2020)
 * 0.11.4 - finmarketpy (06 May 2020)
 * 0.11.3 - finmarketpy (04 Dec 2019)
 * 0.11.1 - finmarketpy (23 Oct 2019)
@@ -114,6 +115,8 @@ In finmarketpy/examples you will find several examples, including some simple tr
 
 # finmarketpy log
 
+* 24 Aug 2020
+    * Replaced .ix to work with later versions of pandas
 * 07 May 2020
     * Improved QuickChart, adding additional labels, fixing example
 * 06 May 2020

diff --git a/finmarketpy/backtest/backtestengine.py b/finmarketpy/backtest/backtestengine.py
@@ -1857,15 +1857,15 @@ def plot_strategy_net_exposures_notional(self, strip=None, silent_plot=False, re
     #### grab signals for specific days
     def _grab_signals(self, strategy_signal, date=None, strip=None):
         if date is None:
-            last_day = strategy_signal.ix[-1].transpose().to_frame()
+            last_day = strategy_signal.loc[-1].transpose().to_frame()
         else:
             if not (isinstance(date, list)):
                 date = [date]
 
             last_day = []
 
             for d in date:
-                last_day.append(strategy_signal.ix[d].transpose().to_frame())
+                last_day.append(strategy_signal[d].transpose().to_frame())
 
             last_day = pandas.concat(last_day, axis=1)
             last_day = last_day.sort_index(axis=1)
@@ -2053,7 +2053,7 @@ def calculate_leverage_factor(self, returns_df, vol_target, vol_max_leverage, vo
         # # now realign back to days when we trade
         # returns_df, lev_df = returns_df.align(lev_df, join='left', axis=0)
 
-        lev_df.ix[0:vol_periods] = numpy.nan  # ignore the first elements before the vol window kicks in
+        lev_df[0:vol_periods] = numpy.nan  # ignore the first elements before the vol window kicks in
 
         return lev_df
 

diff --git a/finmarketpy/economics/eventstudy.py b/finmarketpy/economics/eventstudy.py
@@ -59,7 +59,7 @@ def get_economic_event_ret_over_custom_event_day(self, data_frame_in, event_date
             data_frame.index = data_frame.index + bday
 
         # set as New York time and select only those ON vols at the 10am NY cut just before the event
-        data_frame_events = data_frame.ix[event_dates.index]
+        data_frame_events = data_frame[event_dates.index]
         data_frame_events.columns = data_frame.columns.values + '-' + name + ' ' + event
 
         return data_frame_events
@@ -104,13 +104,15 @@ def get_intraday_moves_over_custom_event(self, data_frame_rets, ef_time_frame, v
         # TODO vectorise this!
         for i in range(0, len(ef_time_frame.index)):
             try:
-                data_frame_rets.ix[start_index[i]:finish_index[i], 'Ind'] = ords
+                data_frame_rets['Ind'][start_index[i]:finish_index[i]] = ords
             except:
-                data_frame_rets.ix[start_index[i]:finish_index[i], 'Ind'] = ords[0:(finish_index[i] - start_index[i])]
+                data_frame_rets['Ind'][start_index[i]:finish_index[i]] = ords[0:(finish_index[i] - start_index[i])]
 
-        # set the release dates
-        data_frame_rets.ix[start_index, 'Rel'] = ef_time  # set entry points
-        data_frame_rets.ix[finish_index + 1, 'Rel'] = numpy.zeros(len(start_index))  # set exit points
+        data_frame_rets['Rel'] = numpy.nan
+
+        # Set the release dates
+        data_frame_rets['Rel'][start_index] = ef_time  # set entry points
+        data_frame_rets['Rel'][finish_index + 1] = numpy.zeros(len(start_index))  # set exit points
         data_frame_rets['Rel'] = data_frame_rets['Rel'].fillna(method='pad')  # fill down signals
 
         data_frame_rets = data_frame_rets[pandas.notnull(data_frame_rets['Ind'])]  # get rid of other
@@ -122,7 +124,7 @@ def get_intraday_moves_over_custom_event(self, data_frame_rets, ef_time_frame, v
 
         if create_index:
             calculations = Calculations()
-            data_frame.ix[-minute_start + min_offset, :] = numpy.nan
+            data_frame.iloc[-minute_start + min_offset] = numpy.nan
             data_frame = calculations.create_mult_index(data_frame)
         else:
             if vol is True:
@@ -548,7 +550,7 @@ def get_economic_data_history(self, start_date, finish_date, country_group, data
         return self.market_data_generator.fetch_market_data(md_request)
 
     def grasp_coded_entry(self, df, index):
-        df = df.ix[index:].stack()
+        df = df[index:].stack()
         df = df.reset_index()
         df.columns = ['Date', 'Name', 'Val']
 

diff --git a/finmarketpy/economics/quickchart.py b/finmarketpy/economics/quickchart.py
@@ -1,7 +1,7 @@
 __author__ = 'saeedamen'  # Saeed Amen / saeed@thalesians.com
 
 #
-# Copyright 2016 Cuemacro
+# Copyright 2020 Cuemacro
 #
 # Licensed under the Apache License, Version 2.0 (the "License"); you may not use this file except in compliance with the
 # License. You may obtain a copy of the License at http://www.apache.org/licenses/LICENSE-2.0
@@ -40,7 +40,7 @@ def plot_chart(self, tickers=None, tickers_rhs=None, start_date=None, finish_dat
                    reindex=False, yoy=False, plotly_plot_mode='offline_png',
                    quandl_api_key=dataconstants.quandl_api_key,
                    fred_api_key=dataconstants.fred_api_key,
-                   alpha_vantage_api_key=dataconstants.alpha_vantage_api_key):
+                   alpha_vantage_api_key=dataconstants.alpha_vantage_api_key, df=None):
 
         if start_date is None:
             start_date = datetime.datetime.utcnow().date() - timedelta(days=60)
@@ -72,17 +72,19 @@ def plot_chart(self, tickers=None, tickers_rhs=None, start_date=None, finish_dat
         else:
             tickers_rhs = {}
 
-        md_request = MarketDataRequest(start_date=start_date, finish_date=finish_date,
-                                       freq=freq,
-                                       data_source=self._data_source,
-                                       tickers=list(tickers.keys()), vendor_tickers=list(tickers.values()),
-                                       fields=list(fields.keys()),
-                                       vendor_fields=list(fields.values()),
-                                       quandl_api_key=quandl_api_key,
-                                       fred_api_key=fred_api_key,
-                                       alpha_vantage_api_key=alpha_vantage_api_key)
-
-        df = self._market.fetch_market(md_request=md_request)
+        if df is None:
+            md_request = MarketDataRequest(start_date=start_date, finish_date=finish_date,
+                                           freq=freq,
+                                           data_source=self._data_source,
+                                           tickers=list(tickers.keys()), vendor_tickers=list(tickers.values()),
+                                           fields=list(fields.keys()),
+                                           vendor_fields=list(fields.values()),
+                                           quandl_api_key=quandl_api_key,
+                                           fred_api_key=fred_api_key,
+                                           alpha_vantage_api_key=alpha_vantage_api_key)
+
+            df = self._market.fetch_market(md_request=md_request)
+
         df = df.fillna(method='ffill')
         df.columns = [x.split('.')[0] for x in df.columns]
 

diff --git a/finmarketpy_examples/quickchart_examples.py b/finmarketpy_examples/quickchart_examples.py
@@ -42,11 +42,13 @@
     from finmarketpy.economics import QuickChart
 
     # Plot with matplotlib - Major USD crosses reindexed from 100 in 2020
-    QuickChart(engine='matplotlib', data_source='bloomberg').plot_chart(tickers=['EURUSD Curncy', 'GBPUSD Curncy', 'AUDUSD Curncy'],
-    title='USD crosses in 2020',
-            start_date='01 Jan 2020', reindex=True, source='Bloomberg')
+    QuickChart(engine='matplotlib', data_source='bloomberg').plot_chart(
+        tickers=['EURUSD Curncy', 'GBPUSD Curncy', 'AUDUSD Curncy'],
+        title='USD crosses in 2020',
+        start_date='01 Jan 2020', reindex=True, source='Bloomberg')
 
     # Plot with Plotly - Major USD crosses reindexed from 100 in 2020
-    QuickChart(engine='plotly', data_source='bloomberg').plot_chart(tickers=['EURUSD Curncy', 'GBPUSD Curncy', 'AUDUSD Curncy'],
-    title='USD crosses in 2020 (Plotly)',
-            start_date='01 Jan 2020', reindex=True, source='Bloomberg')
+    QuickChart(engine='plotly', data_source='bloomberg').plot_chart(
+        tickers=['EURUSD Curncy', 'GBPUSD Curncy', 'AUDUSD Curncy'],
+        title='USD crosses in 2020 (Plotly)',
+        start_date='01 Jan 2020', reindex=True, source='Bloomberg')
diff --git a/setup.py b/setup.py
@@ -4,7 +4,7 @@
 trading strategies using a simple to use API, which has prebuilt templates for you to define backtest."""
 
 setup(name='finmarketpy',
-      version='0.11.4',
+      version='0.11.5',
       description='finmarketpy is a Python based library for backtesting trading strategies',
       author='Saeed Amen',
       author_email='saeed@cuemacro.com',