data operations using pandas

Author: NirmalSilwal

Jash Data Science interview/challenge2.py

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+"""
+Pandas programming task
+
+1. Load the data into a Pandas dataframe
+2. Remove records where scheme_code is NULL
+3. Sort the data by nav_date
+4. Fill Missing values in nav column by the last known value in the field after sorting by nav_date (Fill forward)
+5. Save the output dataframe with the name pandas_challenge_output.csv
+6. Send output file as well as the code in a zip file
+
+Code evaluation criteria:
+1. Correctness of the output file and code
+2. Code should be clean and readable
+3. optimal with respect to time and space complexity (e.g. avoid unnecessary extra variables and loops) 
+
+"""
+
+def process_df(input_csv):
+
+    #TODO: implement your code here
+
+    # loading pandas library
+    import pandas as pd
+    
+    # 1. Load the data into a Pandas dataframe
+    
+    df = pd.read_csv(input_csv)
+
+    # 2. Remove records where scheme_code is NULL
+    
+    df.dropna(subset=['scheme_code'], inplace=True)
+    
+    # 3. Sort the data by nav_date
+    
+    # first converting to datetime format 
+    df['nav_date'] = pd.to_datetime(df['nav_date'])
+
+    df.sort_values(by='nav_date', inplace=True)
+
+    # 4. Fill Missing values in nav column by the last known value in the field after sorting by nav_date (Fill forward)
+    
+    df['nav'].ffill(axis=0, inplace=True)
+    
+    # 5. Save the output dataframe with the name pandas_challenge_output.csv
+
+    df.to_csv('pandas_challenge_output.csv')
+    
+    
+process_df('challenge2_input.csv')