Analyze

submissions/mishc/analyse.py

@@ -0,0 +1,49 @@
+#1. Write a script to identify the number of songs in the file.
+#2. Write a script that identify the number of songs in the key of E.
+#3. Count the occurrences of values in a specified column (e.g., artist names) and determine the most common value.
+
+import sys
+import os
+def analysis(csvObject):
+    try:
+        header = next(csvObject)
+
+        analyse_val={"num_songs":0,"num_songs_E":0, "artist_count":0, "artist_names":{}}
+
+        for row in csvObject:
+            number_of_songs(row,header,analyse_val)
+            most_common_artist_name(row, header, analyse_val)
+
+        print_results(analyse_val)    
+
+    except Exception as e:
+        print("Error in the 'analysis' function:", e)
+        exc_type, exc_obj, exc_tb = sys.exc_info()
+        fname = os.path.split(exc_tb.tb_frame.f_code.co_filename)[1]
+        print(exc_type, fname, exc_tb.tb_lineno)
+
+
+def number_of_songs(row, header,analyse_val):
+    index_key = header.index('key')
+    analyse_val['num_songs'] += 1
+    key=row[index_key]
+    if key=="E":   
+        analyse_val['num_songs_E'] += 1
+def most_common_artist_name(row, header, analyse_val):
+    index_name = header.index('artist(s)_name')
+    artist_name=row[index_name]
+    artist_names=artist_name.split(',')
+    for artist_name in artist_names:
+        if artist_name not in analyse_val['artist_names']:
+            analyse_val['artist_names'][artist_name]=1
+        else:
+            analyse_val['artist_names'][artist_name]+=1
+
+
+def print_results(analyse_val):
+
+    print("Number of songs:", analyse_val['num_songs'])
+    print("Number of songs in key E:", analyse_val['num_songs_E'])
+
+    sorted_dict = sorted(analyse_val['artist_names'].items(), key=lambda item:item[1], reverse=True)
+    print("Most common artist name:", next(iter(sorted_dict))[0])

submissions/mishc/delete_double_rows.py

@@ -0,0 +1,12 @@
+def delete_double_rows(csvObject):
+
+    unique_lines = []
+    encountered_lines = set()
+
+    for row in csvObject:
+        row_tuple = tuple(row)
+
+        if row_tuple not in encountered_lines:
+            unique_lines.append(row)
+            encountered_lines.add(row_tuple)
+    return unique_lines

submissions/mishc/index.py

@@ -0,0 +1,27 @@
+import csv, sys,os
+from delete_double_rows import delete_double_rows 
+import analyse as anal
+
+
+try:        
+    with open('spotify-2023.csv', 'r', encoding='ISO-8859-1') as file:
+        csv_reader = csv.reader(file)
+        unique_lines=delete_double_rows(csv_reader)
+    with open('spotify-2023.csv', 'w', newline='') as file:
+        writer = csv.writer(file)
+        writer.writerows(unique_lines)
+    with open('spotify-2023.csv', 'r', encoding='ISO-8859-1') as file: 
+        csv_reader = csv.reader(file)  
+        anal.analysis(csv_reader)
+
+
+except FileNotFoundError:
+    print("File not found")
+except csv.Error as e:
+    print(f"CSV Error: {type(e).__name__} - {str(e)}")
+except Exception as e:
+    print(f"An error occurred: {type(e).__name__} - {str(e)}")
+    exc_type, exc_obj, exc_tb = sys.exc_info()
+    fname = os.path.split(exc_tb.tb_frame.f_code.co_filename)[1]
+    print(exc_type, fname, exc_tb.tb_lineno)
+