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| { | |
| "plot_stock_data(stock_data: pd.DataFrame, ax: Optional[plt.Axes] = None, figure_type: str = 'line', title_name: str ='') -> plt.Axes:\n": "\"\"\"\n This function plots stock data.\n\n Args:\n - stock_data: the stock data to plot. The DataFrame should contain three columns:\n - Column 1: trade date in 'YYYYMMDD'\n - Column 2: Stock name or code (string format)\n - Column 3: Index value (numeric format)\n The DataFrame can be time series data or cross-sectional data. If it is time-series data, the first column represents different trade time, the second column represents the same name. For cross-sectional data, the first column is the same, the second column contains different stocks.\n\n - ax: matplotlib Axes object, the axes to plot the data on\n - figure_type: either 'line' or 'bar'\n - title_name\n\n Returns:\n - matplotlib Axes object, the axes containing the plot\n \"\"\"", | |
| "plot_k_line(stock_data: pd.DataFrame, title: str = '') -> None:\n": "\"\"\"\n Plots a K-line chart of stock price and volume.\n\n Args:\n stock_data : A pandas DataFrame containing the stock price information, in which each row\n represents a daily record. The DataFrame must contain the 'trade_date','open', 'close', 'high', 'low','volume', 'name' columns, which is used for k-line and volume.\n 如果dataframe中还含有'macd'，'kdj', 'rsi', 'cci', 'boll','pe_ttm','turnover_rate'等列，则在k线图下方绘制这些指标的子图.\n \"\"\"", | |
| "print_save_table(df: pd.DataFrame, title_name: str, save:bool = False ,file_path: str = './output/') -> None:": "\"\"\"\n It prints the dataframe and saves it to a CSV file at the specified file path.\n\n Args:\n - df: the dataframe to be printed and saved to a CSV file\n - title_name: the name to be printed and saved\n - save: whether to save as a CSV file\n - file_path \n\n \"\"\"", | |
| "output_mean_median_col(data: pd.DataFrame, col: str = 'new_feature') -> float:\n": "# It calculates the mean and median value for the specified column." | |
| } | |