Create six TIME SERIES(USING pd.series function) and store in a Pandas data frame: a)The data frame must have an index that is a range of dates from 2016-01-01 until today. b)Each column contains one set of random numbers in a range 0 to 1 (each column will haveone random number for each date). number of columns = 6 number of rows = date range between today and 2016-01-01
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Create six TIME SERIES(USING pd.series function) and store in a Pandas data frame:
a)The data frame must have an index that is a range of dates from 2016-01-01 until today.
b)Each column contains one set of random numbers in a range 0 to 1 (each column will haveone random number for each date).
number of columns = 6
number of rows = date range between today and 2016-01-01
Step by step
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- Create six TIME SERIES(USING pd.series function) and store in a Pandas data frame:a)The data frame must have an index that is a range of dates from 2016-01-01 until today.b)Each column contains one set of random numbers in a range 0 to 1 (each column will haveone random number for each date).dataset in picture Use the given dataset to perform the following using python: Name of dataframe (your reg_no+your_name) Import the given data set Find out its header and information Calculate the mean, median and mode of covid_deaths, covid_recoveries, and covid_cases Find out the total of covid affected cases(all three cases) in all countries Find out the total of covid related deaths in all countries Countries covid_deaths covid_recoveries covid_cases Pakistan 10000 520000 55000 India 12000 120000 130000 Bangladesh 14000 123000 120000 Srilanka 19000 213000 45000 Bhutan 12000 212 44000 Nepal 1000 9000 12300 Australia 80000 560000 32100 Singapore 2000 130000 12345 England 100000 320000 89765 USA 100000 890000 87898Use the R data set “anscombe” to save a subset of all the columns of the data except x4 and y4
- Create a pandas DataFrame with two columns. The first column should be titled F for Fahrenheit, and should contain the numbers from 0 to 100, counting by fives. The second column should be titled C for Celsius, and contain the corresponding temperature in degrees Celsius for the number in the first column.The file LaptopSalesJanuary2008.csv contains data for all sales of laptops at a computer chain in London in January 2008. This is a subset of the full dataset that includes data for the entire year. I. Create a bar chart, showing the average retail price by store. Which store has the highest average? Which has the lowest? Please give proper explanation and typed answer only.This is Pandas Which of the following would be a correct way to return rows 0 through 5 of columns "Name" and "Age" from the data frame df? df.loc[0:5, ["Name", "Age"]] df.loc[:5, "Name", "Age"] df.loc[0:6, ["Name", "Age"]] df.loc[:6, "Name", "Age"]
- Use the data file “marketing_campaign.csv” for this problem. Note: There are rows at the top of the file that must be skipped. a. Read the data into R and create a subset consisting of the following columns: Education, Marital_Status, Income, Dt_Customer, MntFruits, and Complain. b. Convert the data a type of the following columns: Education Ordered factor (Hint: Level of “2n Cycle” is between Graduation and Master Marital_Status Unordered factor Income Double precision numeric Complain Logical c. Convert the data type of Dt_Customer to Date. d. With proper code check the data types of columns are as stated in (b) and (c).Import the pets.csv dataset from your data file into Rstudio. Use the unique function on the pet column to find all the unique pets in the data. Which is the second pet in the resulting output?I need to merge three datasets so that I can create a custom function that would do the following: Create a function called theme_by_year that takes as input a year (as an integer) and shows the theme ids and theme names (listed in order by theme id) that were in sets that year. The column names must be id and name_themes (to differentiate between the name of a theme and the name of a set) in that order. The index should be reset and go from 0 to n-1. Each theme should only be listed once even if it appeared in more than one set from that year -- duplicate themes should be based on theme id and not name since there are some themes with the same name but with a different id. Hint: It will help if you were to think about merging appropriate DataFrames to help you get this answer. The desired output should look like this: theme_by_year(1960) Output: id name_themes0 371 Supplemental1 497 Books2 513 Classic Here's what I tried, but I did not get the desired output:
- Open a SAS session. Suppose we want to create a variable in the sashelp.pricedata dataset. Use a DATA step to create a copy of the sashelp.pricedata dataset and create a new variable that is the sum of the price1, price2, ..., price 17 variables. Note that when using a SAS function, you can specify all columns between two columns (including start and end) using the word of and a dash. The syntax similar to name_of_function(of columnstart-columnend) What is the value of the sum variable for the fifth observation (MAY98)? Report your answer to one decimal placeIn cell H2, get the unique Area values using UNIQUE(). In column I, use COUNTIF() to get the count of each Area. Pass the data range from A2 to A45 as absolute addresses, and the filter criteria from H2 to H9. In column J, use COUNTIFS() to get the count of each area with more than 20 Swallow-tails. the first two arguments are the same as the previous step, then add a condition for column D to be greater than 20. Area Locality Skipper Swallowtail White-yellow Blue Brush-footed Area Count of Area Count of Area with 20 Swallowtails Indian Subcontinent Indian Subcontinent 307 94 99 458 482 Western Himalaya Western Himalaya 63 31 42 129 152 Western Himalaya Kangra Hills 25 23 37 56 87 Western Himalaya Shimla Hills 41 21 34 88 115 Western Himalaya Dehradun Valley 22 11 19 42 54 Western Himalaya Mussoorie Hills 54 23 32 88 126 Western Himalaya Mussoorie Town 14 10 13 44 65 Western Himalaya Kumaon Hills 52 26 37 109 147…You are contracted to complete the data system for Citywide Taxi Company. Now, the information for each taxi is expanded to include: taxi id (such as CTC0001), the driver’s name, the maker of the Car (such as Ford), the model of the car (such as Escape), the Color of the Car (such as Black), the license number (such as HXT 4578), the number of passages the car served in the entire shift (integer type, this field will be left empty for this project). Your C++ program will (with array of class object): Define a class for the car with all members of variable mentioned above as private; Write all necessary class member functions to access those member variables (write or read); Read up to 50 records of data from the keyboard (provide a method to end the input before reaching 50 records) Save all records inputted from step 3 to a disk file called CTC.dat.