Page 458 - AI Ver 3.0 class 10_Flipbook
P. 458

• Modifying an existing Row

                 [1]:   f2.loc[33]=['Sneha',95,'C']
                        print(f2)

                              Name  Marks Section
                        11    Riya     92       A
                        22  Sonali     90       E
                        33   Sneha     95       C
                        44   Nitin     84       C
                 • Modifying an existing column

                 [1]:   f2['Marks']=[92,97, 91,89]
                        print(f2)
                              Name  Marks Section
                        11    Riya     92       A
                        22  Sonali     97       E
                        33   Sneha     91       C
                        44   Nitin     89       C
                 • Deleting a Row

                 To delete a row or a column, the .drop() method is used with the DataFrame. The parameter axis=0 is used for
                 deleting a row and axis=1 for deleting a column.

                 [1]:   f2=f2.drop(22,axis=0)
                        print(f2)

                             Name    Marks  Section
                        11   Riya       92        A
                        33  Sneha       91        C
                        44  Nitin       89        C
                 • Deleting a Column

                 [1]:   f2=f2.drop('Marks',axis=1)
                        print(f2)
                             Name   Section
                        11   Riya         A
                        33  Sneha         C
                        44  Nitin         C


                            Task                                                            21 st  Century   #Technology Literacy
                                                                                                Skills

                Find out what happens when you add the following statements in a DataFrame created earlier:
                a.  f2.loc[22]
                b.  f2[:] = 0
                c.  f2.loc[33]=0



              Python with Pandas is used in a wide range of fields, including academic and commercial domains like finance,
              economics, statistics, and analytics. Pandas offers several important features:
                 • It provides a fast and efficient way to manage and explore data using Series and DataFrames, making it suitable
                for data science.

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