Add NASDAQ datalink retail trader dataset (#941)

Co-authored-by: James Maslek <james@macbook-pro.myfiosgateway.com>

gamestonk_terminal/stocks/discovery/disc_controller.py

@@ -10,7 +10,7 @@ from matplotlib import pyplot as plt
 from prompt_toolkit.completion import NestedCompleter
 
 from gamestonk_terminal import feature_flags as gtff
-from gamestonk_terminal.helper_funcs import get_flair
+from gamestonk_terminal.helper_funcs import EXPORT_ONLY_RAW_DATA_ALLOWED, get_flair
 from gamestonk_terminal.helper_funcs import (
     parse_known_args_and_warn,
     check_non_negative,
@@ -30,6 +30,7 @@ from gamestonk_terminal.stocks.discovery import (
     finnhub_view,
     geekofwallstreet_view,
     financedatabase_view,
+    nasdaq_view,
 )
 
 
@@ -64,6 +65,7 @@ class DiscoveryController:
         "rtearn",
         "fds",
         "cnews",
+        "rtat",
     ]
 
     CHOICES += CHOICES_COMMANDS
@@ -113,6 +115,8 @@ pennystockflow.com
     hotpenny       today's hot penny stocks
 Finance Database:
     fds            advanced Equities search based on country, sector, industry, name and/or description
+NASDAQ Data Link (Formerly Quandl):
+    rtat           top 10 retail traded stocks per day
 """
         print(help_text)
 
@@ -1008,6 +1012,35 @@ Finance Database:
             options=ns_parser.options,
         )
 
+    @try_except
+    def call_rtat(self, other_args: List[str]):
+        """Process fds command"""
+        parser = argparse.ArgumentParser(
+            add_help=False,
+            formatter_class=argparse.ArgumentDefaultsHelpFormatter,
+            prog="rtat",
+            description="""
+                Tracking over $30B USD/day of individual investors trades,
+                RTAT gives a daily view into retail activity and sentiment for over 9,500 US traded stocks,
+                ADRs, and ETPs
+            """,
+        )
+        parser.add_argument(
+            "-n",
+            "--num",
+            dest="n_days",
+            help="Number of days to show",
+            default=3,
+            type=check_positive,
+        )
+
+        ns_parser = parse_known_args_and_warn(
+            parser, other_args, export_allowed=EXPORT_ONLY_RAW_DATA_ALLOWED
+        )
+        if not ns_parser:
+            return
+        nasdaq_view.display_top_retail(n_days=ns_parser.n_days, export=ns_parser.export)
+
 
 def menu():
     """Discovery Menu"""

gamestonk_terminal/stocks/discovery/nasdaq_model.py

@@ -0,0 +1,25 @@
+"""NASDAQ DataLink Model"""
+__docformat__ = "numpy"
+
+import pandas as pd
+import requests
+import gamestonk_terminal.config_terminal as cfg
+
+
+def get_retail_tickers() -> pd.DataFrame:
+    """Gets the top 10 retail stocks per day
+
+    Returns
+    -------
+    pd.DataFrame
+        Dataframe of tickers
+    """
+    r = requests.get(
+        f"https://data.nasdaq.com/api/v3/datatables/NDAQ/RTAT10/?api_key={cfg.API_KEY_QUANDL}"
+    )
+    if r.status_code != 200:
+        return pd.DataFrame()
+
+    df = pd.DataFrame(r.json()["datatable"]["data"])
+    df.columns = ["Date", "Ticker", "Activity", "Sentiment"]
+    return df

gamestonk_terminal/stocks/discovery/nasdaq_view.py

@@ -0,0 +1,41 @@
+"""NASDAQ DataLink View"""
+__docformat__ = "numpy"
+
+import os
+
+from colorama import Style
+from tabulate import tabulate
+
+from gamestonk_terminal.helper_funcs import export_data
+from gamestonk_terminal.stocks.discovery import nasdaq_model
+import gamestonk_terminal.feature_flags as gtff
+
+
+def display_top_retail(n_days: int = 3, export: str = ""):
+    """Display the top 10 retail traded stocks for last days
+
+    Parameters
+    ----------
+    n_days : int, optional
+        Number of days to show by default 3
+    export : str, optional
+        Format to export data, by default ""
+    """
+    retails = nasdaq_model.get_retail_tickers()
+    for date, df in retails.head(n_days * 10).groupby("Date"):
+        print(f"{Style.BRIGHT}{date} Top Retail:{Style.RESET_ALL}")
+        df = df.drop(columns=["Date"])
+        if gtff.USE_TABULATE_DF:
+            print(
+                tabulate(
+                    df.reset_index(drop=True),
+                    headers=df.columns[1:],
+                    showindex=False,
+                    tablefmt="fancy_grid",
+                )
+            )
+        else:
+            print(df.reset_index(drop=True).to_string(index=False))
+
+        print("")
+    export_data(export, os.path.dirname(os.path.abspath(__file__)), "rtat", retails)

website/content/stocks/discovery/rtat/_index.md

@@ -0,0 +1,14 @@
+```
+usage: rtat [-n N_DAYS] [-h] [--export {csv,json,xlsx}]
+```
+
+Tracking over $30B USD/day of individual investors trades, RTAT gives a daily view into retail activity and sentiment for over 9,500 US traded stocks, ADRs, and ETPs
+
+```
+optional arguments:
+  -n N_DAYS, --num N_DAYS
+                        Number of days to show (default: 3)
+  -h, --help            show this help message (default: False)
+  --export {csv,json,xlsx}
+                        Export raw data into csv, json, xlsx (default: )
+```

website/data/menu/main.yml

@@ -50,6 +50,8 @@ main:
             ref: "/stocks/discovery/hotpenny"
           - name: fds
             ref: "/stocks/discovery/fds"
+          - name: rtat
+            ref: "/stocks/discovery/rtat"
       - name: dark pool shorts
         ref: "/stocks/dark_pool_shorts"
         sub: