Write the statement to change the value at 5th row, 6th column in a Dataframe df.
Ans:df.iat[4,5] = 23 you can assign any value to the given element.
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Sumita Arora Solution
Write statement(s) to delete a column from a Dataframe.
Ans:Syntax to delete a column from a Dataframe is :del <dataframe object>[<column name>]for example:del df[‘first’]
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Write statement(s) to delete a row from Dataframe
Ans:We can use df.drop(<row Number>) or df.drop(<row name>) statements to delete a row. for exampledf.drop(4)ordf.drop(‘first’)
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Write code statement for Dataframe df for the following: (a) Delete an existing column from it. (b) Delete row from 3 to 6 from it. (c) Check the Dataframe has any missing values. (d) Fill all missing values with 999 in it.
Ans:(a)del df[<columnname>](b)df.drop(range(3,7))(c)df.isnull().values.any()(d)df.fillna(999, inplace = True)
How would you add a new column namely ‘val’ to a Dataframe df that has 10 rows in it and has columns as ‘Item’, ‘Qty’, ‘Price’ ? You can choose to put any values of your choice.
Ans:to add a new column ‘val’ in dataframe ‘df’ we will write-df[‘val’]=[12,23,45,43,55,12,23,43,11,29]Here we are assigning 10 different values to ‘val’ column as df have 10 rows.
Write the code segment to list the following, from Dataframe namely sales. (a) List only columns ‘Item’ and ‘revenue’ (b) List rows from 3 to 7 (c) List the value of cell in 5th row, ‘Item’ column.
Ans:(a)print(df[[‘Item’,’revenue’]) (b)print(df.loc(3:8)) (c)print(df.Item[5])
Given a dataframe df as shown below:
A B D 0 15 17 19 1 16 18 20 2 20 21 22 What will be the result of following code segment ?(a) df[‘C’] = np.NaN(b) df[‘C’] = [2,5](c) df[‘C’] = [12, 15, 27] Ans (a) A B D C 0 15 17 19 NaN 1 16 18 20 NaN 2 20 21
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Given following Series objects: (b) What will be the result of S1 – S2 ?
S1 S2 0 3 0 12 1 5 2 10 2 6 3 15 4 10 4 20 5 12 6 27 Ans: 0 9 1 NaN 2 4 3 NaN 4 10 5 NaN 6 NaN
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Given following Series objects: (a) What will be the result of S1 + S2 ?
S1 S2 0 3 0 12 1 5 2 10 2 6 3 15 4 10 4 20 5 12 6 27 Ans: 0 15 1 NaN 2 16 3 NaN 4 30 5 NaN 6 NaN
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Write commands to print following details of a Series object seal.
a) if the series is empty – print(seal.empty)b) indexes of the series – print(seal.index)c) the data type of underlying data – print(seal.dtype)d) if the series stores any NaN values – print(seal.hasnans)
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