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requested changes
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DJ
@@ -137,11 +137,11 @@ Retrieve a candlestick chart for the currently loaded instrument. Not a live cha
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* -c : Specify the number of candles to retrieve. (default=180)
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* -a : Adds AD (Accumulation/Distribution Index) to the chart. AD is a cumulative indicator that uses volume and price to assess whether a stock is being accumulated or distributed. This provides insight into how strong a trend is. [Investopedia](#https://www.investopedia.com/terms/a/accumulationdistribution.asp)
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* -b : Adds Bollinger Bands to the chart. Bollinger bands are a set of trendlines plotted two standard deviations (positively and negatively) away from a simple moving average of a security's price. [Investopedia](#https://www.investopedia.com/terms/b/bollingerbands.asp)
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* -C : Adds CCI (Commodity Channel Index) to the chart. CCI is a momentum-based oscillator used to help determine when an investment vehicle is reaching a condition of being overbought or oversold. [Investopedia](#https://www.investopedia.com/terms/c/commoditychannelindex.asp)
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* -e : Adds EMA (Exponential Moving Average) to the chart. EMA is a moving average that places a greater weight and significance on the most recent data points. [Investopedia](#https://www.investopedia.com/terms/e/ema.asp)
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* -C : Adds CCI (Commodity Channel Index) to the chart. CCI is a momentum-based oscillator used to help determine when an investment vehicle is reaching a condition of being overbought or oversold. (default=14) [Investopedia](#https://www.investopedia.com/terms/c/commoditychannelindex.asp)
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* -e : Adds EMA (Exponential Moving Average) to the chart. EMA is a moving average that places a greater weight and significance on the most recent data points. (default=10) [Investopedia](#https://www.investopedia.com/terms/e/ema.asp)
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* -o : Adds OBV (On Balance Volume) to the chart. OBV is a momentum indicator that uses volume flow to predict changes in price. [Investopedia](#https://www.investopedia.com/terms/o/onbalancevolume.asp)
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* -r : Adds RSI (Relative Strength Index) to the chart. RSI is a momentum indicator that measures the magnitude of recent price changes to evaluate overbought or oversold conditions. [Investopedia](#https://www.investopedia.com/terms/r/rsi.asp)
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* -s : Adds SMA (Simple Moving Average) to the chart. SMA calculates the average of a selected range of prices, usually closing prices, by the number of periods in that range. [Investopedia](#https://www.investopedia.com/terms/s/sma.asp)
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* -r : Adds RSI (Relative Strength Index) to the chart. RSI is a momentum indicator that measures the magnitude of recent price changes to evaluate overbought or oversold conditions. (default=14) [Investopedia](#https://www.investopedia.com/terms/r/rsi.asp)
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* -s : Adds SMA (Simple Moving Average) to the chart. SMA calculates the average of a selected range of prices, usually closing prices, by the number of periods in that range. (defaults= 20, 50) [Investopedia](#https://www.investopedia.com/terms/s/sma.asp)
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* -v : Adds VWAP (Volume Weighted Average Price) to the chart. VWAP gives the average price a security has traded at throughout the day, based on both volume and price. [Investopedia](#https://www.investopedia.com/terms/v/vwap.asp)
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## price <a name="price"></a>
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@@ -7,8 +7,10 @@ from gamestonk_terminal.menu import session
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from gamestonk_terminal.forex import fx_view
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from gamestonk_terminal import config_terminal as cfg
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from gamestonk_terminal.due_diligence import news_view, reddit_view
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from gamestonk_terminal.behavioural_analysis import stocktwits_view, twitter_view
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from gamestonk_terminal.exploratory_data_analysis import eda_api
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from gamestonk_terminal.behavioural_analysis import stocktwits_view
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from gamestonk_terminal.exploratory_data_analysis import eda_controller
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import pandas as pd
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account = cfg.OANDA_ACCOUNT
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@@ -38,13 +40,7 @@ class ForexController:
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"bullbear",
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"messages",
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"reddit",
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"infer",
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"sentiment",
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"edasummary",
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"edarolling",
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"edadecompose",
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"edacusum",
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"edahist",
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"eda",
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]
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def __init__(self):
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@@ -94,16 +90,8 @@ class ForexController:
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" reddit search reddit for posts about the loaded instrument"
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)
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print(
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" edasummary brief summary statistics using exploratory data analysis"
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" eda exploratory data analysis, e.g.: decompose, cusum, residuals analysis"
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)
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print(" edarolling rolling mean and std deviation")
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print(
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" edadecompose decomposition in cyclic-trend, season, and residuals"
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)
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print(
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" edacusum detects abrupt changes using cumulative sum algorithm"
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)
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print("")
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def switch(self, an_input: str):
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@@ -191,44 +179,27 @@ class ForexController:
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"""Call news [News API]"""
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news_view.news(other_args, self.instrument)
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def call_bullbear(self, other_args):
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def call_bullbear(self, other_args: List[str]):
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"""Call bullbear fom stocktwits"""
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instrument = fx_view.format_instrument(self.instrument, " ")
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stocktwits_view.bullbear(other_args, instrument)
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def call_messages(self, other_args):
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def call_messages(self, other_args: List[str]):
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"""Call messages from stocktwits"""
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instrument = fx_view.format_instrument(self.instrument, " ")
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stocktwits_view.messages(other_args, instrument)
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def call_edasummary(self, other_args: List[str]):
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df = fx_view.get_candles_dataframe(account, self.instrument, None)
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eda_api.summary(other_args, df)
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def call_edarolling(self, other_args: List[str]):
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df = fx_view.get_candles_dataframe(account, self.instrument, None)
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df.columns = ["Open", "Low", "High", "5. adjusted close", "Volume"]
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eda_api.rolling(other_args, self.instrument, df)
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def call_edadecompose(self, other_args: List[str]):
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df = fx_view.get_candles_dataframe(account, self.instrument, None)
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df.columns = ["Open", "Low", "High", "5. adjusted close", "Volume"]
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eda_api.decompose(other_args, self.instrument, df)
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def call_edacusum(self, other_args: List[str]):
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df = fx_view.get_candles_dataframe(account, self.instrument, None)
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df.columns = ["Open", "Low", "High", "5. adjusted close", "Volume"]
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eda_api.cusum(other_args, self.instrument, df)
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def call_reddit(self, other_args: List[str]):
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instrument = fx_view.format_instrument(self.instrument, " ")
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reddit_view.due_diligence(other_args, instrument)
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def call_infer(self, other_args: List[str]):
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twitter_view.inference(other_args, self.instrument)
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def call_sentiment(self, other_args: List[str]):
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twitter_view.sentiment(other_args, self.instrument)
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def call_eda(self, other_args):
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df = fx_view.get_candles_dataframe(account, self.instrument, None)
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df = df.rename(columns={"Close": "5. adjusted close"})
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instrument = self.instrument
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s_start = pd.to_datetime(df.index.values[0])
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s_interval = "1440min"
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eda_controller.menu(df, instrument, s_start, s_interval)
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def menu():
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@@ -645,7 +645,7 @@ def add_plots(df, ns_parser):
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ema = ta.ema(df["Close"])
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ema_plot = mpf.make_addplot(ema, panel=0)
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plots_to_add.append(ema_plot)
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legends.append("20 EMA")
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legends.append("10 EMA")
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if ns_parser.rsi:
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rsi = ta.rsi(df["Close"])
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