merge dev

Signed-off-by: James Kunstle <[email protected]>

8Knot/pages/contributions/visualizations/cntrb_pr_assignment.py

@@ -217,12 +217,7 @@ def process_data(df: pd.DataFrame, interval, assign_req, start_date, end_date):
     df_contrib = df[df["assignment_action"] == "assigned"]
 
     # count the assignments total for each contributor
-    df_contrib = (
-        df_contrib["assignee"]
-        .value_counts()
-        .to_frame()
-        .reset_index()
-    )
+    df_contrib = df_contrib["assignee"].value_counts().to_frame().reset_index()
 
     # create list of all contributors that meet the assignment requirement
     contributors = df_contrib["assignee"][df_contrib["count"] >= assign_req].to_list()

8Knot/pages/contributions/visualizations/cntrib_issue_assignment.py

@@ -214,12 +214,7 @@ def process_data(df: pd.DataFrame, interval, assign_req, start_date, end_date):
     df_contrib = df[df["assignment_action"] == "assigned"]
 
     # count the assignments total for each contributor
-    df_contrib = (
-        df_contrib["assignee"]
-        .value_counts()
-        .to_frame()
-        .reset_index()
-    )
+    df_contrib = df_contrib["assignee"].value_counts().to_frame().reset_index()
 
     # create list of all contributors that meet the assignment requirement
     contributors = df_contrib["assignee"][df_contrib["count"] >= assign_req].to_list()

8Knot/pages/contributions/visualizations/issues_over_time.py

@@ -189,7 +189,7 @@ def process_data(df: pd.DataFrame, interval, start_date, end_date):
     created_range = pd.to_datetime(df["created_at"]).dt.to_period(interval).value_counts().sort_index()
 
     # converts to data frame object and creates date column from period values
-    df_created = created_range.to_frame().reset_index().rename(columns={"created": "Date", "count": "created"})
+    df_created = created_range.to_frame().reset_index().rename(columns={"created_at": "Date", "count": "created_at"})
 
     # converts date column to a datetime object, converts to string first to handle period information
     # the period slice is to handle weekly corner case
@@ -199,7 +199,6 @@ def process_data(df: pd.DataFrame, interval, start_date, end_date):
     closed_range = pd.to_datetime(df["closed_at"]).dt.to_period(interval).value_counts().sort_index()
     df_closed = closed_range.to_frame().reset_index().rename(columns={"closed_at": "Date", "count": "closed_at"})
 
-
     df_closed["Date"] = pd.to_datetime(df_closed["Date"].astype(str).str[:period_slice])
 
     # first and last elements of the dataframe are the

8Knot/pages/contributions/visualizations/pr_over_time.py

@@ -165,20 +165,20 @@ def process_data(df: pd.DataFrame, interval):
     created_range = df["created_at"].dt.to_period(interval).value_counts().sort_index()
 
     # converts to data frame object and created date column from period values
-    df_created = created_range.to_frame().reset_index().rename(columns={"created": "Date", "count": "created"})
+    df_created = created_range.to_frame().reset_index().rename(columns={"created_at": "Date", "count": "created_at"})
 
     # converts date column to a datetime object, converts to string first to handle period information
     # the period slice is to handle weekly corner case
     df_created["Date"] = pd.to_datetime(df_created["Date"].astype(str).str[:period_slice])
 
     # df for merged prs in time interval
     merged_range = pd.to_datetime(df["merged_at"]).dt.to_period(interval).value_counts().sort_index()
-    df_merged = merged_range.to_frame().reset_index().rename(columns={"merged": "Date", "count": "merged"})
+    df_merged = merged_range.to_frame().reset_index().rename(columns={"merged_at": "Date", "count": "merged_at"})
     df_merged["Date"] = pd.to_datetime(df_merged["Date"].astype(str).str[:period_slice])
 
     # df for closed prs in time interval
     closed_range = pd.to_datetime(df["closed_at"]).dt.to_period(interval).value_counts().sort_index()
-    df_closed = closed_range.to_frame().reset_index().rename(columns={"closed": "Date", "count": "closed"})
+    df_closed = closed_range.to_frame().reset_index().rename(columns={"closed_at": "Date", "count": "closed_at"})
     df_closed["Date"] = pd.to_datetime(df_closed["Date"].astype(str).str[:period_slice])
 
     # A single df created for plotting merged and closed as stacked bar chart

8Knot/pages/contributors/visualizations/new_contributor.py

@@ -186,19 +186,10 @@ def process_data(df, interval):
         return df, None
 
     # get the count of new contributors in the desired interval in pandas period format, sort index to order entries
-<<<<<<< HEAD
     created_range = pd.to_datetime(df["created_at"]).dt.to_period(interval).value_counts().sort_index()
 
     # converts to data frame object and creates date column from period values
-    df_contribs = created_range.to_frame().reset_index().rename(columns={"index": "Date", "created_at": "contribs"})
-=======
-    created_range = pd.to_datetime(df["created"]).dt.to_period(interval).value_counts().sort_index()
-    logging.critical(f"created_range new_contributor.py {created_range}")
-
-    # converts to data frame object and creates date column from period values
-    df_contribs = created_range.to_frame().reset_index().rename(columns={"created": "Date", "count": "contribs"})
-    logging.critical(f"df_contribs new_contributor.py {df_contribs}")
->>>>>>> 7d12c64 (fixes df names for contributors page)
+    df_contribs = created_range.to_frame().reset_index().rename(columns={"created_at": "Date", "count": "contribs"})
 
     # converts date column to a datetime object, converts to string first to handle period information
     df_contribs["Date"] = pd.to_datetime(df_contribs["Date"].astype(str))