mirror of
https://github.com/OpenBB-finance/OpenBB.git
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db844a567f
* fixed Pandas SettingWithCopyWarnings * fixed typo in test_google_view * fixed typo in test_google_view
268 lines
7.4 KiB
Python
268 lines
7.4 KiB
Python
"""Google View."""
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__docformat__ = "numpy"
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import logging
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import os
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from typing import Optional, List
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import pandas as pd
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import matplotlib.pyplot as plt
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from openbb_terminal.config_terminal import theme
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from openbb_terminal.config_plot import PLOT_DPI
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from openbb_terminal.common.behavioural_analysis import google_model
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from openbb_terminal.decorators import log_start_end
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from openbb_terminal.helper_funcs import (
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export_data,
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plot_autoscale,
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print_rich_table,
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is_valid_axes_count,
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)
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from openbb_terminal.rich_config import console
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logger = logging.getLogger(__name__)
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@log_start_end(log=logger)
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def display_mentions(
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symbol: str,
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start_date: str = "",
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export: str = "",
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external_axes: Optional[List[plt.Axes]] = None,
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):
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"""Plot weekly bars of stock's interest over time. other users watchlist. [Source: Google]
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Parameters
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----------
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symbol : str
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Ticker symbol
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start_date : str
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Start date as YYYY-MM-DD string
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export: str
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Format to export data
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external_axes : Optional[List[plt.Axes]], optional
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External axes (1 axis is expected in the list), by default None
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"""
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df_interest = google_model.get_mentions(symbol)
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# This plot has 1 axis
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if external_axes is None:
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_, ax = plt.subplots(figsize=plot_autoscale(), dpi=PLOT_DPI)
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elif is_valid_axes_count(external_axes, 1):
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(ax,) = external_axes
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else:
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return
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ax.set_title(f"Interest over time on {symbol}")
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if start_date:
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df_interest = df_interest[start_date:] # type: ignore
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ax.bar(df_interest.index, df_interest[symbol], width=2)
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ax.bar(
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df_interest.index[-1],
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df_interest[symbol].values[-1],
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width=theme.volume_bar_width,
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)
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else:
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ax.bar(df_interest.index, df_interest[symbol], width=1)
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ax.bar(
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df_interest.index[-1],
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df_interest[symbol].values[-1],
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width=theme.volume_bar_width,
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)
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ax.set_ylabel("Interest [%]")
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ax.set_xlim(df_interest.index[0], df_interest.index[-1])
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theme.style_primary_axis(ax)
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if external_axes is None:
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theme.visualize_output()
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export_data(
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export, os.path.dirname(os.path.abspath(__file__)), "mentions", df_interest
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)
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@log_start_end(log=logger)
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def display_correlation_interest(
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symbol: str,
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data: pd.DataFrame,
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words: List[str],
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export: str = "",
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external_axes: Optional[List[plt.Axes]] = None,
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):
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"""Plot interest over time of words/sentences versus stock price. [Source: Google]
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Parameters
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----------
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symbol : str
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Ticker symbol to check price
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data : pd.DataFrame
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Data dataframe
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words : List[str]
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Words to check for interest for
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export: str
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Format to export data
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external_axes : Optional[List[plt.Axes]], optional
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External axes (1 axis is expected in the list), by default None
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"""
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# This plot has 1 axis
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if external_axes is None:
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_, ax = plt.subplots(
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figsize=plot_autoscale(),
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dpi=PLOT_DPI,
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nrows=2,
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ncols=1,
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sharex=True,
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gridspec_kw={"height_ratios": [1, 2]},
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)
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elif is_valid_axes_count(external_axes, 1):
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(ax,) = external_axes
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else:
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return
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ax[0].set_title(
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f"{symbol.upper()} stock price and interest over time on {','.join(words)}"
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)
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ax[0].plot(
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data.index,
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data["Adj Close"].values,
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c="#FCED00",
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)
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ax[0].set_ylabel("Stock Price")
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ax[0].set_xlim(data.index[0], data.index[-1])
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colors = theme.get_colors()[1:]
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for idx, word in enumerate(words):
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df_interest = google_model.get_mentions(word)
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ax[1].plot(df_interest.index, df_interest[word], "-", color=colors[idx])
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ax[1].set_ylabel("Interest [%]")
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ax[1].set_xlim(data.index[0], data.index[-1])
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ax[1].legend(words)
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theme.style_primary_axis(ax[0])
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theme.style_primary_axis(ax[1])
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if external_axes is None:
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theme.visualize_output()
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export_data(
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export, os.path.dirname(os.path.abspath(__file__)), "interest", df_interest
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)
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@log_start_end(log=logger)
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def display_regions(
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symbol: str,
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limit: int = 5,
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export: str = "",
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external_axes: Optional[List[plt.Axes]] = None,
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):
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"""Plot bars of regions based on stock's interest. [Source: Google]
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Parameters
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----------
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symbol : str
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Ticker symbol
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limit: int
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Number of regions to show
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export: str
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Format to export data
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external_axes : Optional[List[plt.Axes]], optional
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External axes (1 axis is expected in the list), by default None
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"""
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df_interest_region = google_model.get_regions(symbol)
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# This plot has 1 axis
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if external_axes is None:
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_, ax = plt.subplots(figsize=plot_autoscale(), dpi=PLOT_DPI)
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elif is_valid_axes_count(external_axes, 1):
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(ax,) = external_axes
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else:
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return
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if df_interest_region.empty:
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console.print("No region data found.")
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console.print("")
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return
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df_interest_region = df_interest_region.head(limit)
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df = df_interest_region.sort_values([symbol], ascending=True)
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ax.set_title(f"Top's regions interest on {symbol}")
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ax.barh(
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y=df.index, width=df[symbol], color=theme.get_colors(reverse=True), zorder=3
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)
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ax.set_xlabel("Interest [%]")
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ax.set_ylabel("Region")
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theme.style_primary_axis(ax)
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if external_axes is None:
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theme.visualize_output()
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export_data(export, os.path.dirname(os.path.abspath(__file__)), "regions", df)
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@log_start_end(log=logger)
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def display_queries(symbol: str, limit: int = 5, export: str = ""):
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"""Print top related queries with this stock's query. [Source: Google]
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Parameters
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----------
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symbol : str
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Ticker symbol
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limit: int
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Number of regions to show
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export: {"csv","json","xlsx","png","jpg","pdf","svg"}
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Format to export data
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Returns
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-------
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None
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"""
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# Retrieve a dict with top and rising queries
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dict_related_queries = google_model.get_queries(symbol)
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# Select the DataFrame "top" from the dict
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df_top_queries = dict_related_queries[symbol]["top"].head(limit).copy()
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df_export = (
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df_top_queries.copy()
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) # export the raw values, prior to string manipulation
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# convert to strings and add %
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df_top_queries["value"] = df_top_queries["value"].apply(lambda x: str(x) + "%")
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print_rich_table(
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df_top_queries,
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headers=list(df_top_queries.columns),
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title=f"Top {symbol}'s related queries",
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)
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export_data(
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export, os.path.dirname(os.path.abspath(__file__)), "queries", df_export
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)
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@log_start_end(log=logger)
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def display_rise(symbol: str, limit: int = 10, export: str = ""):
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"""Print top rising related queries with this stock's query. [Source: Google]
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Parameters
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----------
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symbol : str
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Ticker symbol
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limit: int
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Number of regions to show
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export: str
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Format to export data
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"""
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df_related_queries = google_model.get_rise(symbol)
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print_rich_table(
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df_related_queries.head(limit),
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headers=list(df_related_queries.columns),
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title=f"Top rising {symbol}'s related queries",
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)
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export_data(
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export, os.path.dirname(os.path.abspath(__file__)), "rise", df_related_queries
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)
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