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DataFrame.py
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DataFrame.py
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from abc import ABC, abstractmethod
from yahoo_fin import stock_info, news
import utils
# Abstract Class for all statements.
class DataFrame(ABC):
def __init__(self):
self.ticker = None
self.company_name = None
self.dataframe = None
self.flabels = None
self.column_int = None
@abstractmethod
def plot_graph(self):
pass
@abstractmethod
def show_stats(self):
pass
# Methods inherited.
def get_dataframe(self, sheet_type):
"""
Will get pandas dataframe of chosen statement for given ticker.
sheet_type: String | Choose from "balance", "income" or "cashflow" statements.
"""
dataframe = []
if sheet_type == "balance":
dataframe = stock_info.get_balance_sheet(self.ticker) # Also confirms ticker exists.
elif sheet_type == "income":
dataframe = stock_info.get_income_statement(self.ticker)
elif sheet_type == "cashflow":
dataframe = stock_info.get_cash_flow(self.ticker)
else:
print("You need to add a sheet_type parameter to the get_dataframe() method in class.")
exit()
self.company_name = utils.get_company_name(self.ticker) # Get companies name using ticker.
if not dataframe.empty:
return dataframe
else:
print(f"We can't find any information with the ticker {self.ticker} you have entered.")
def parse_dataframe(self):
"""
Extract information such as x, y labels from dataframe.
"""
label1 = list(self.dataframe.index) # Financial Labels
label2 = [date.date() for date in list(self.dataframe.columns)] # Date Labels
return label1, label2
def get_row(self, label, append_iter=None):
"""
From dataframe extract row with matching query as financial label.
"""
try:
data_row = self.dataframe.iloc[self.flabels.index(label)]
if append_iter is not None:
append_iter.append((label, data_row))
except ValueError as e:
# This label is not in dataframe finance labels available.
return []
else:
return data_row
def subplot_col_int(self, position):
"""
Used for designating the subplot value, according on whether there is enough data
for presentation.
"""
sub_string = str(self.column_int) + "1" + str(position)
return int(sub_string)
def parse_stat(self, data, title):
"""
Method used in conjunction with show_stats method.
:param data: DataFrame
:param title: String
:return: None
"""
try:
dates = [date.date() for date in list(data.axes[0])]
print(title)
for index, value in enumerate(data.values):
print(f"{dates[index]} --> {value}")
except Exception as e:
pass
return
# Debugging Methods.
def show_contents(self):
"""Shows type of data passed and contents of this data."""
print(type(self.dataframe))
print(self.dataframe)
# Experimental Methods to use later on.
def gen_stats(self):
"""These stats are just extracted from yahoo and not calculated locally."""
stock_stats = stock_info.get_stats(self.ticker)
val_stock_stats = stock_info.get_stats_valuation(self.ticker)
print(stock_stats)
print(val_stock_stats)
def get_news(self):
news_outlet = news.get_yf_rss(self.ticker)
return news_outlet