Python sum column in dataframe
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Write a Numpy program to find out smallest and sum of array elements 0,1,2,3,4,5,6,7,8,9. OR Write a python programming code to display and create a 8x8 ndarray and fill it with a checkerboard pattern i.e. 0 and 1 at alternative positions.
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Write python statement to create a one –dimensional array using arrange() function .Elements will be in the range 10 to 30 with a step of 4 (including both 10 and 30). Reshape this one-dimensional array to two dimensional array of shape(2,3).
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d1= pd.DataFrame(d1) d2= pd.DataFrame(d2) print(d1) print(d2) Write the command to add df1 and df2. df1+df2. Write a command to find the average of marks1 column of df2 dataframe. df2['marks1'].mean() 3(1 mark for each correct answer) Ans. English Chemistry Maths Physics. Student1 NaN 78 78 45
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Create a data frame for examination result and display row labels, column labels data types of each column and the dimensions Filter out rows based on different criteria such as duplicate rows.. Find the sum of each column, or find the column with the lowest mean.
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df1=pd.DataFrame(d1) Write the python statement using suitable functions among (apply/ apply_map / sum() / mean() _____#To calculate square root of each element of data frame _____# To Calculate mean() _____# To Calculate total no. of non null values in each column
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2. Write a small python code to delete a column namely “head1” from a dataframe df1. Ans: df = df1.pop(‘head1’) .. 3. What is groupby() function in Pandas.? Write its syntax. Ans: The . groupby function in pandas creates groups internally based on the field’s values. Syntax:. groupby (by= None,axis =0 or 1) 4.
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Slice the modified dataframe column and apply summarization functions one at a time using ‘groupby’ pandas method. Pass the indexes as a list to the groupby function. For eg: if count, sum and weighted average are values to be calculated - create a data type of dtype for each of the 3 functions.
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Consider the following DataFrame. import pandas as pd. import numpy as np. d1={'Sal':[50000,60000,55000],'bonus':[3000,4000,5000]} df1=pd.DataFrame(d1) Write the python statement using suitable functions among (apply/ apply_map / sum() / mean() _____#To calculate square root of each element . of data frame
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