Fixing Forecast SDK with data from other menus (#3554)

* minor check incase using sdk

* fixes combine

* datetime formating

* Update forecast.md

* fix testing

openbb_terminal/forecast/forecast_model.py

@@ -42,6 +42,18 @@ def get_default_files() -> Dict[str, Path]:
     return default_files
 
 
+def sdk_dt_format(x) -> str:
+    """Convert any Timestamp to YYYY-MM-DD when using SDK
+    Args:
+        x: Pandas Timestamp of any length
+    Returns:
+        x: formatted string
+    """
+    x = pd.to_datetime(x)
+    x = x.strftime("%Y-%m-%d")
+    return x
+
+
 @log_start_end(log=logger)
 def get_options(
     datasets: Dict[str, pd.DataFrame], dataset_name: str = None
@@ -415,6 +427,18 @@ def combine_dfs(
     data: pd.DataFrame
         The new dataframe
     """
+
+    # for use with SDK
+    # check if date is index, if true, reset index
+    if df1.index.name == "date":
+        df1 = df1.reset_index()
+        # remove 00:00:00 from 2019-11-19 00:00:00
+        df1["date"] = df1["date"].apply(lambda x: sdk_dt_format(x))
+    if df2.index.name == "date":
+        df2 = df2.reset_index()
+        # remove 00:00:00 from 2019-11-19 00:00:00
+        df2["date"] = df2["date"].apply(lambda x: sdk_dt_format(x))
+
     if column not in df2:
         console.print(
             f"Not able to find the column {column}. Please choose one of "

openbb_terminal/forecast/helpers.py

@@ -635,6 +635,13 @@ def get_series(
         fill_missing_dates=True,
     )
     try:
+        # for the sdk, we must check if date is a column not an index
+        # check if date is in the index, if true, reset the index
+        if time_col in data.index.names:
+            data.reset_index(inplace=True)
+            # remove 00:00:00 from 2019-11-19 00:00:00
+            data[time_col] = data[time_col].apply(lambda x: dt_format(x))
+
         ticker_series = TimeSeries.from_dataframe(**filler_kwargs)
     except ValueError:
         # remove business days to allow base lib to assume freq

website/content/sdk/guides/intros/forecast.md

@@ -64,12 +64,28 @@ help(openbb.forecast)
 
 ## Examples
 
+### combine
+​
+Combine columns from different datasets
+​
+```python
+spy = openbb.stocks.load("spy")
+aapl = openbb.stocks.load("aapl")
+
+# merge the data
+combined_df = openbb.forecast.combine(spy,aapl, dataset="aapl", column= "Close")
+openbb.forecast.show(combined_df)
+```
+<img width="507" alt="image" src="https://user-images.githubusercontent.com/105685594/203791078-181431cb-99bf-4d26-bfff-b4cf34b5dee2.png">
+![Combine View](https://user-images.githubusercontent.com/105685594/203791078-181431cb-99bf-4d26-bfff-b4cf34b5dee2.png)
+
+
 ### corr
 ​
 Shows a correlation matrix between columns in dataset
 ​
 ```python
-df = pd.read_csv(ANDREW_REPLACE)
+df = openbb.stocks.load("aapl")
 openbb.forecast.corr_chart(df)
 ```
 ![Corr View](https://user-images.githubusercontent.com/72827203/202424217-b549b6e7-b121-4273-a7d9-b478e89cd65a.png)
@@ -80,7 +96,7 @@ openbb.forecast.corr_chart(df)
 This command allows you to see seasonality patterns in your data
 
 ```python
-df = pd.read_csv(ANDREW_REPLACE)
+df = openbb.stocks.load("aapl")
 openbb.forecast.season_chart(df)
 ```
 ​
@@ -92,7 +108,7 @@ openbb.forecast.season_chart(df)
 Predicts the future value of time series data using exponential smoothing
 ​
 ```python
-df = pd.read_csv(ANDREW_REPLACE)
+df = openbb.stocks.load("aapl")
 openbb.forecast.expo_chart(df)
 ```
 ​