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Python Pandas DataFrame.ix[] function slices rows or columns based on the value of the argument.

pandas.DataFrame.ix[]grammar

DataFrame.ix[index = None,
             label = None]

parameter

return

It returns the modified DataFrame.

Sample code: DataFrame.ix[]How to split row index

import pandas as pd

dataframe=pd.DataFrame({'Attendance': {0: 60, 1: 100, 2: 80,3: 78,4: 95},
                        'Name': {0: 'Olivia', 1: 'John', 2: 'Laura',3: 'Ben',4: 'Kevin'},
                        'Obtained Marks': {0: 90, 1: 75, 2: 82, 3: 64, 4: 45}})

print("The Original Data frame is: \n")
print(dataframe)

dataframe1 = dataframe.ix[:2, ]
print("The Modified Data frame is: \n")
print(dataframe1)

Output:

The Original Data frame is: 

   Attendance    Name  Obtained Marks
0          60  Olivia              90
1         100    John              75
2          80   Laura              82
3          78     Ben              64
4          95   Kevin              45
The Modified Data frame is: 

   Attendance    Name  Obtained Marks
0          60  Olivia              90
1         100    John              75
2          80   Laura              82

It has sliced ​​the row indices 3and 4.

Example code: DataFrame.ix[]Method for slicing column index

In Pandas, to slice columns of a DataFrame, we will ix[]call the slice function on the column labels using indexing.

import pandas as pd

dataframe=pd.DataFrame({'Attendance': {0: 60, 1: 100, 2: 80,3: 78,4: 95},
                        'Name': {0: 'Olivia', 1: 'John', 2: 'Laura',3: 'Ben',4: 'Kevin'},
                        'Obtained Marks': {0: 90, 1: 75, 2: 82, 3: 64, 4: 45}})

print("The Original Data frame is: \n")
print(dataframe)

dataframe1 = dataframe.ix[ : , :1]
print("The Modified Data frame is: \n")
print(dataframe1)

Output:

The Original Data frame is: 

   Attendance    Name  Obtained Marks
0          60  Olivia              90
1         100    John              75
2          80   Laura              82
3          78     Ben              64
4          95   Kevin              45
The Modified Data frame is: 

   Attendance
0          60
1         100
2          80
3          78
4          95

Now only the first column of the DataFrame is returned.

Example code: DataFrame.ix[]How to split column labels

We can also pass the column label as an argument to keep that column and slice the other columns.

import pandas as pd

dataframe=pd.DataFrame({'Attendance': {0: 60, 1: 100, 2: 80,3: 78,4: 95},
                        'Name': {0: 'Olivia', 1: 'John', 2: 'Laura',3: 'Ben',4: 'Kevin'},
                        'Obtained Marks': {0: 90, 1: 75, 2: 82, 3: 64, 4: 45}})

print("The Original Data frame is: \n")
print(dataframe)

dataframe1 = dataframe.ix[ : ,"Name"]
print("The Modified Data frame is: \n")
print(dataframe1)

Output:

The Original Data frame is: 

   Attendance    Name  Obtained Marks
0          60  Olivia              90
1         100    John              75
2          80   Laura              82
3          78     Ben              64
4          95   Kevin              45
The Modified Data frame is: 

0    Olivia
1      John
2     Laura
3       Ben
4     Kevin
Name: Name, dtype: object

The function preserves Namethe column while slicing the other columns. But you should notice that the function preserves Namethe values ​​of the column and slices its labels.