Delete data/questions/3

data/questions/3/answer.txt

@@ -1,3 +0,0 @@
-Winter Average PM2.5: 67.4923443634478
-Monsoon Average PM2.5: 34.42519611317571
-Summer Average PM2.5: nan

data/questions/3/code.py

@@ -1,26 +0,0 @@
-def true_code():
-    import pandas as pd
-    
-    # [Station name] = 'Lal Bahadur Shastri Nagar, Kalaburagi - KSPCB'
-    df = pd.read_csv('data/raw_data/Data.csv', sep=",")
-    
-    df['Timestamp'] = pd.to_datetime(df['Timestamp'])
-    df['Year'] = df['Timestamp'].dt.year
-    df['Month'] = df['Timestamp'].dt.month
-    
-    data = df[df['Year'] == 2018]
-    data = data[data['station'] == 'Lal Bahadur Shastri Nagar, Kalaburagi - KSPCB']
-    
-    winter_data = data[(data['Month'] == 12) | (data['Month'] <= 2)]
-    summer_data = data[(data['Month'] >= 3) & (data['Month'] <= 5)]
-    monsoon_data = data[(data['Month'] >= 6) & (data['Month'] <= 9)]
-    
-    summer_avg = summer_data['PM2.5'].mean()
-    winter_avg = winter_data['PM2.5'].mean()
-    monsoon_avg = monsoon_data['PM2.5'].mean()
-    
-    print("Winter Average PM2.5:", winter_avg)
-    print("Monsoon Average PM2.5:", monsoon_avg)
-    print("Summer Average PM2.5:", summer_avg)
-
-true_code()

data/questions/3/metadata.json

@@ -1,9 +0,0 @@
-{
-    "question_id": 3,
-    "category": "temporal",
-    "answer_category": "mutiple",
-    "plot": false,
-    "libraries": [
-        "pandas"
-    ]
-}

data/questions/3/question.txt

@@ -1 +0,0 @@
-For the year 2018, calculate the average PM2.5 concentration for each season (Winter: December-February, Summer: March-May, and Monsoon: June-September) for station [Station name]. Identify the season with the highest pollution and suggest potential factors contributing to the increase.