Data Analysis -- 3rd Course

Step 1. Import the necessary libraries In [1]: Step 2. Create the DataFrame that should look like the one below. In [2]: Out[2]: Step 3. Create a Scatterplot of preTestScore and postTestScore, with the size of each point determined by age Hint: Don't forget to place the labels In [ ]: Step 4. Create a Scatterplot of preTestScore and postTestScore. This time the size should be 4.5 times the postTestScore and the color determined by sex In [ ]:

Step 1. Import the necessary libraries In [ ]: Step 2. Import the dataset from this address. https://github.com/guipsamora/pandas_exercises/blob/master/04_Apply/Students_Alcohol_Consumption/student-mat.csv Step 3. Assign it to a variable called df. In [ ]: Step 4. For the purpose of this exercise slice the dataframe from 'school' until the 'guardian' column In [ ]: Step 5. Create a lambda function that captalize strings. In [ ]: Step 6. Capitalize both Mjob and Fjob In [ ]: Step 7. Print the last elements of the data set. In [ ]: Step 8. Did you notice the original dataframe is still lowercase? Why is that? Fix it and captalize Mjob and Fjob. In [ ]: Step 9. Create a function called majority that return a boolean value to a new column called legal_drinker In [ ]: In [ ]: Step 10. Multiply every number of the dataset by 10. I know this makes no sense, don't forget it is just an exercise In [ ]: In [ ]:

Be ready till the next week be prepared for the first quiz It will be accounted for 4 labs Several questions will be randomly chosen from the code snippets out of the 5 pdf files which you took from flash card. For each line of the given code excerpt, you are to provide elegant explanation about each of its chunk, parameter, answer how output will look like As to theoretical questions be prepared to answer to the following: what is mean, median, standard deviation, 25th percentile, 50th percentile, 75th percentile, outliers, missing values in data science Good luck!

Be ready to answer for randomly chosen questions out of here http://www.labri.fr/perso/nrougier/teaching/numpy.100/index.html

\ Step 1. Import the necessary libraries In [ ]: Step 2. Import the dataset from this address. https://raw.githubusercontent.com/justmarkham/DAT8/master/data/drinks.csv Step 3. Assign it to a variable called drinks. In [ ]: Step 4. Which continent drinks more beer on average? In [ ]: Step 5. For each continent print the statistics for wine consumption. In [ ]: Step 6. Print the mean alcoohol consumption per continent for every column In [ ]: Step 7. Print the median alcoohol consumption per continent for every column In [ ]: Step 8. Print the mean, min and max values for spirit consumption. This time output a DataFrame In [ ]:

https://tmp60.tmpnb.org/user/eN5KVTjGg3E0/tree