Add support for loading data from pandas dataframe

Right now, we only support loading data from numpy arrays. It would be nice if there was a helper function to convert a dataframe of scores to numpy arrays. Some initial code to help what this might look like:

def get_all_return_values(df):
  games = list(df['game'].unique())
  return_vals = {}
  for game in games:
    game_df = df[df['game'] == game]
    arr = game_df.groupby('wid')['normalized_score'].apply(list).values
    return_vals[game] = np.stack(arr, axis=0)
  return return_vals

def convert_to_matrix(x):
  return np.stack([x[k] for k in sorted(x.keys())], axis=1)

## Usage
# Array of shape (num_runs, num_games, num_steps)`
all_normalized_scores = convert_to_matrix(get_all_return_values(score_df))

The above code assumes we have a pandas Dataframe with keys run_number, 'gameandnormalized_score` containing scores for all steps (in a ordered manner).