p2

WS24_25/PyCharm/pythonProject/.idea/misc.xml

@@ -3,5 +3,5 @@
   <component name="Black">
     <option name="sdkName" value="Python 3.12 (pythonProject)" />
   </component>
-  <component name="ProjectRootManager" version="2" project-jdk-name="Python 3.11 (pythonProject)" project-jdk-type="Python SDK" />
+  <component name="ProjectRootManager" version="2" project-jdk-name="Python 3.8 (pythonProject)" project-jdk-type="Python SDK" />
 </project>

WS24_25/PyCharm/pythonProject/.idea/pythonProject.iml

@@ -5,7 +5,7 @@
       <excludeFolder url="file://$MODULE_DIR$/.venv" />
       <excludeFolder url="file://$MODULE_DIR$/venv" />
     </content>
-    <orderEntry type="jdk" jdkName="Python 3.11 (pythonProject)" jdkType="Python SDK" />
+    <orderEntry type="jdk" jdkName="Python 3.8 (pythonProject)" jdkType="Python SDK" />
     <orderEntry type="sourceFolder" forTests="false" />
   </component>
 </module>

WS24_25/PyCharm/pythonProject/P2/cvsToJson.py

@@ -0,0 +1,29 @@
+import json
+
+
+def csv_to_json(input_file: str, output_file: str):
+    data = []
+
+    # Step 1: Read the CSV file manually
+    with open(input_file, 'r') as file:
+        lines = file.readlines()
+
+    # Step 2: Parse the first line to get the headers
+    headers = lines[0].strip().split(';')
+
+    # Step 3: Parse the subsequent lines to get the data
+    for line in lines[1:]:
+        values = line.strip().split(';')
+        # Create a dictionary for each row
+        row_dict = {headers[i]: values[i] for i in range(len(headers))}
+        data.append(row_dict)
+
+    # Step 4: Save the data to a JSON file
+    with open(output_file, 'w') as json_file:
+        json.dump(data, json_file, indent=4)
+
+
+# Usage
+input_csv_file = 'AmesHousing.csv'
+output_json_file = 'AmesHousing.json'
+csv_to_json(input_csv_file, output_json_file)

WS24_25/PyCharm/pythonProject/P2/summary.py

@@ -0,0 +1,19 @@
+import pandas as pd
+
+
+def summarize_csv(file_path: str):
+    # Step 1: Load the CSV file using pandas
+    df = pd.read_csv(file_path, delimiter=';')
+
+    # Step 2: Print general information about the data
+    print("Data Info:")
+    print(df.info())
+
+    # Step 3: Print statistical summary of the numerical columns
+    print("\nStatistical Summary:")
+    print(df.describe())
+
+
+# Usage
+input_csv_file = 'AmesHousing.csv'
+summarize_csv(input_csv_file)