Predict the output of following code fragments one by one. For every next code fragment, consider that the changes by previous code fragment are in place. That is, for code fragment (b), changes made by code fragment (a) are persisting ; for (c), changes by (a) and (b) are persisting and so on.

(a)

import pandas as pd
columns=['2015', '2016', '2017', '2018']
index=['Messi', 'Ronaldo', 'Neymar', 'Hazard']
df = pd.DataFrame(columns = columns, index = index)
print(df)
df.to_csv("c:\one.csv")

(b)

df['2015']['Messi'] = 12 
df['2016']['Ronaldo'] = 11 
df['2017']['Neymar'] = 8 
df['2018']['Hazard'] = 16 
print(df)
df.to_csv("c:\\two.csv", sep = '@')

(c)

new_df = pd.read_csv('c:\one.csv', index_col = 0) 
print(new_df)

(d)

new_df = pd.read_csv('c:\one.csv') 
print(new_df)

(e)

new_df = pd.read_csv('c:\\two.csv') 
print(new_df)

(f)

new_df = pd.read_csv('c:\\two.csv', sep = '@')
print(new_df)

(a)

        2015 2016 2017 2018
Messi    NaN  NaN  NaN  NaN
Ronaldo  NaN  NaN  NaN  NaN
Neymar   NaN  NaN  NaN  NaN
Hazard   NaN  NaN  NaN  NaN

Working

The DataFrame df is created with defined columns and index labels. It is then printed, showing NaN values since no data is provided. Afterwards, df is written to a CSV file named one.csv.

The contents of the file one.csv are as follows:

,2015,2016,2017,2018
Messi,,,,
Ronaldo,,,,
Neymar,,,,
Hazard,,,,

(b)

        2015 2016 2017 2018
Messi     12  NaN  NaN  NaN
Ronaldo  NaN   11  NaN  NaN
Neymar   NaN  NaN    8  NaN
Hazard   NaN  NaN  NaN   16

Working

The code assigns values to specific cells in the DataFrame df, such as setting the value of 'Messi' in the '2015' column to 12 and so on. After printing the modified DataFrame, it is saved to a CSV file named two.csv using '@' as the separator.

The contents of the file two.csv are as follows:

@2015@2016@2017@2018
Messi@12@@@
Ronaldo@@11@@
Neymar@@@8@
Hazard@@@@16

(c)

         2015  2016  2017  2018
Messi     NaN   NaN   NaN   NaN
Ronaldo   NaN   NaN   NaN   NaN
Neymar    NaN   NaN   NaN   NaN
Hazard    NaN   NaN   NaN   NaN

Working

The code reads the CSV file named one.csv into a new DataFrame new_df. The parameter index_col = 0 means the first column of the CSV file will be used as the index. It then prints the contents of new_df. Since the CSV file has an empty DataFrame, the new_df DataFrame will be empty as well.

The contents of the file one.csv are as follows:

,2015,2016,2017,2018
Messi,,,,
Ronaldo,,,,
Neymar,,,,
Hazard,,,,

(d)

  Unnamed: 0  2015  2016  2017  2018
0      Messi   NaN   NaN   NaN   NaN
1    Ronaldo   NaN   NaN   NaN   NaN
2     Neymar   NaN   NaN   NaN   NaN
3     Hazard   NaN   NaN   NaN   NaN

Working

The code used the pandas read_csv() function to extract data from one.csv file. The retrieved data is then stored in a DataFrame called new_df and then it is printed. Since the index_col parameter is not specified, the DataFrame is using default numerical indexes. The DataFrame displays "Unnamed: 0" as the header for the first column because the CSV file doesn't have a header row.

The contents of the file one.csv are as follows:

,2015,2016,2017,2018
Messi,,,,
Ronaldo,,,,
Neymar,,,,
Hazard,,,,

(e)

  @2015@2016@2017@2018
0          Messi@12@@@
1        Ronaldo@@11@@
2          Neymar@@@8@
3         Hazard@@@@16

Working

The code used the pandas read_csv() function to extract data from the two.csv file. The retrieved data is then stored in a DataFrame called new_df and printed. However, if the actual separator in the two.csv file is "@" instead of the default comma (,), then the code without specifying the sep parameter, will not parse the data correctly. It will assume that the data is comma-separated and will not display the correct structure of the data in the DataFrame.

The contents of the file two.csv are as follows:

@2015@2016@2017@2018
Messi@12@@@
Ronaldo@@11@@
Neymar@@@8@
Hazard@@@@16

(f)

  Unnamed: 0  2015  2016  2017  2018
0      Messi  12.0   NaN   NaN   NaN
1    Ronaldo   NaN  11.0   NaN   NaN
2     Neymar   NaN   NaN   8.0   NaN
3     Hazard   NaN   NaN   NaN  16.0

Working

The code extracts data from the two.csv file using the read_csv() function and assigns it to the new_df DataFrame. It then prints new_df. The sep parameter is used to ensure that the DataFrame is correctly parsed, and default indexes are used since index_col is not specified. The term 'Unnamed' is used because a header for the first column is not mentioned in the CSV file.

The contents of the file two.csv are as follows:

@2015@2016@2017@2018
Messi@12@@@
Ronaldo@@11@@
Neymar@@@8@
Hazard@@@@16