The following is a dataset of bridges in Pittsburgh. The original dataset was prepared by Yoram Reich and Steven J. Fenves, Department of Civil Engineering and Engineering Design Research Center, Carnegie Mellon University. Note: Complete lab either manually with Excel/Google Sheets or by using Python Libraries Use this dataset to complete the following tasks: a. Address all the missing values. b. Look for outliers and smooth noisy data. c. Prepare the dataset to establish a relation among: i. Length of the bridge and its purpose. ii. Number of lanes and its materials. iii. Span of the bridge and number of lanes.
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- Solve the following problem using python and jupyter notebook, plus matplotlib. You have two datasets regarding information on each cup soccer team in the World Cups: Year 2002:Position,Team,Games Played,Win,Draw,Loss,Goals For,Goals Against,Goal Difference,Points.1,Brazil,7,7,0,0,18,4,14,212,Germany,7,5,1,1,14,3,11,163,Turkey,7,4,1,2,10,6,4,134,South Korea,7,3,3,2,2,2,8,6,2,115,Spain,5,3,2,0,10,5,5,116,England,5,2,2,1,6,3,3,87,Senegal,5,2,2,1,7,6,1,88,United States,5,2,1,2,7,7,0,79,Japan,4,2,1,1,5,3,2,710,Denmark,4,2,1,1,5,5,0,7 Year 2022: Position,Team,Games Played,Win,Draw,Loss,Goals For,Goals Against,Goal Difference,Points.1,Argentina,7,6,0,1,15,8,7,182,France,7,5,0,2,16,8,8,153,Croatia,7,4,2,1,8,7,1,144,Morocco,7,4,1,2,6,5,1,135,England,5,3,1,1,13,4,9,106,Netherlands,5,3,1,1,10,4,6,107,Portugal,5,3,0,2,12,6,6,98,Brazil,5,3,0,2,8,3,5,99,Japan,4,2,0,2,5,4,1,610,Senegal,4,2,0,2,5,7,-2,6 You are requested to perform: A) Remove rows with null data from both datasetsB) Apply a filter…I need help with this question of Data Structure and algorithm with some conceptual explanation as well Consider the function g(n) = 1+ c + c2....+cn, where c is a positive real number greater than 1. 1) g(n) = Θ(1) (True or False) 2) g(n) = Θ(n) (True or False) 3) g(n) = Θ(cn) (True or False)To replace current values with different values dynamically, replace is very helpful. To demonstrate this, if you wanted to replace the zeroes and ones in the current dataset with boolean values, true or false, you could do this using replace. In df, replace 0 with False and 1 with True. Store this output in df_bool.
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