Ze1598 · July 28, 2021 23:34 · Jul 28, 2021 · Jul 28, 2021 · Jul 28, 2021 · Jul 28, 2021
diff --git a/save_scraped_data_in_df.py b/save_scraped_data_in_df.py
@@ -71,7 +71,28 @@ def get_stats_per_level(num_levels: int, df: pd.DataFrame) -> pd.DataFrame:
     return df
 
 # Remaining code seen before to scrape data
+for operator in op_dict:
 # (...)
+    if len(rank_buttons) == 1:
+        # Get stats for all E0 levels
+        main_df = get_stats_per_level(30, main_df)
+
+    elif len(rank_buttons) == 2:
+        # Get stats for all E0 levels
+        main_df = get_stats_per_level(40, main_df)
+        # Now promote to E1 i.e. click the E1 button
+        rank_buttons[1].click()
+        main_df = get_stats_per_level(55, main_df)
+
+    elif len(rank_buttons) == 3:
+        # Get stats for all E0 levels
+        main_df = get_stats_per_level(50, main_df)
+        # Now promote to E1 i.e. click the E1 button
+        rank_buttons[1].click()
+        main_df = get_stats_per_level(80, main_df)
+        # Now promote to E2 i.e. click the E2 button
+        rank_buttons[2].click()
+        main_df = get_stats_per_level(90, main_df)
 
 # Scraping completed, time to output the CSV
 # Remove duplicate rows because of the issue discussed earlier

diff --git a/save_scraped_data_in_df.py b/save_scraped_data_in_df.py
@@ -29,7 +29,6 @@
     }
 )
 
-
 # Refactored function
 # Given the number of levels, it levels up the character that many times and reads its stats each time
 def get_stats_per_level(num_levels: int, df: pd.DataFrame) -> pd.DataFrame:

diff --git a/save_scraped_data_in_df.py b/save_scraped_data_in_df.py
@@ -74,7 +74,6 @@ def get_stats_per_level(num_levels: int, df: pd.DataFrame) -> pd.DataFrame:
 # Remaining code seen before to scrape data
 # (...)
 
-
 # Scraping completed, time to output the CSV
 # Remove duplicate rows because of the issue discussed earlier
 main_df.drop_duplicates(inplace=True)

diff --git a/save_scraped_data_in_df.py b/save_scraped_data_in_df.py
@@ -0,0 +1,85 @@
+# Imports
+# (...)
+
+# selenium set up
+# (...)
+
+# scrape dictionary of characters and output as pickle
+# (...)
+
+# Running dataframe to collect operator data into
+main_df = pd.DataFrame(
+    {
+        "operator": list(),
+        "rarity": list(),
+        "class": list(),
+        "promotion_level": list(),
+        "level": list(),
+        "hp": list(),
+        "attack": list(),
+        "defense": list(),
+        "resistance": list(),
+        "redeployment_time": list(),
+        "dp_cost": list(),
+        "block_count": list(),
+        "attack_interval": list(),
+        "cn_release_date": list(),
+        "global_release_date": list(),
+        "is_limited": list()
+    }
+)
+
+
+# Refactored function
+# Given the number of levels, it levels up the character that many times and reads its stats each time
+def get_stats_per_level(num_levels: int, df: pd.DataFrame) -> pd.DataFrame:
+
+    for i in range(num_levels):
+
+        # Logic to scrape data seen before
+        # (...)
+
+        # To add the new row of data, it can be added as a dictionary
+        row_to_append = {
+            "operator": operator,
+            "rarity": operator_rarity,
+            "class": operator_class,
+            "promotion_level": promotion_level,
+            "level": operator_level,
+            "hp": op_hp,
+            "attack": op_atk,
+            "defense": op_def,
+            "resistance": op_res,
+            "redeployment_time": op_redeploy,
+            "dp_cost": op_cost,
+            "block_count": op_block,
+            "attack_interval": op_atk_interv,
+            "cn_release_date": cn_release_date,
+            "global_release_date": global_release_date,
+            "is_limited": operator_is_limited
+        }
+        # And now append that dictionary as a new row
+        df = df.append(row_to_append, ignore_index=True)
+
+        # Same code as before but I kept in the snippet because it's short
+        # Get the arrow to increase operator level
+        increase_level_button = driver.find_element_by_class_name("fa-arrow-right")
+        # Click the button (increase 1 level)
+        increase_level_button.click()
+
+    # And now the dataframe with the latest data is returned
+    # Return the DF with all the data accumulated so far
+    return df
+
+# Remaining code seen before to scrape data
+# (...)
+
+
+# Scraping completed, time to output the CSV
+# Remove duplicate rows because of the issue discussed earlier
+main_df.drop_duplicates(inplace=True)
+# main_df.to_csv("arknights_operator_stats.csv", index=False)
+main_df.to_csv("test.csv", index=False)
+
+# Close the Selenium Chrome driver
+driver.quit()