shared_utils to calitp_data_analysis for rt_predictions/

Author: tiffanychu90

rt_predictions/chart_utils.py

@@ -1,6 +1,6 @@
 import altair as alt
-from shared_utils import calitp_color_palette as cp
 import pandas as pd
+from calitp_data_analysis import calitp_color_palette as cp
 
 def altair_dropdown(df, column_for_dropdown:str, title_of_dropdown:str):
     """

rt_predictions/sample_query_materialized_tables.py

@@ -10,18 +10,17 @@
 os.environ["CALITP_BQ_MAX_BYTES"] = str(12_000_000_000_000)
 os.environ['USE_PYGEOS'] = '0'
 
+import numpy as np
 import pandas as pd
 from siuba import *
 
 from calitp_data_analysis.sql import query_sql
 from calitp_data_analysis.tables import tbls
-import shared_utils
 import datetime as dt
 
 from segment_speed_utils.project_vars import (PREDICTIONS_GCS, 
                                               analysis_date)
 analysis_date = dt.datetime.fromisoformat(analysis_date)
-import numpy as np
 
 sampling_periods = {}
 sampling_periods['am'] = [dt.datetime.combine(analysis_date, dt.time(8, 0)),

rt_predictions/summarize_sampled_updates.py

@@ -2,21 +2,20 @@
 os.environ["CALITP_BQ_MAX_BYTES"] = str(12_000_000_000_000)
 os.environ['USE_PYGEOS'] = '0'
 
+import numpy as np
 import pandas as pd
+import pytz
 from siuba import *
 
 from calitp_data_analysis.sql import query_sql
 from calitp_data_analysis.tables import tbls
-import shared_utils
 import datetime as dt
 import sample_query_materialized_tables as smpl
 
 from segment_speed_utils.project_vars import (PREDICTIONS_GCS, 
                                               analysis_date)
 analysis_date = dt.datetime.fromisoformat(analysis_date)
 
-import pytz
-import numpy as np
 
 service_levels = smpl.get_service_levels()
 tu_datasets = smpl.get_tu_datasets()