INTRODUCTION – Working with Data in Python
Introduces one to comparatively less general theoretical concepts, such as file reading and writing as the essential for managing data input and output. Further on, introduces handling of manipulated data by using Python libraries as ready-to-use power tools for doing mathematical work with data.
These libraries will prepare you to deal successfully and effectively with complicated data analysis work. By the end of this module, you will thoroughly know how to work on data with all tools and techniques at your disposal.
Learning Objectives:
- Illustrate how Pandas makes use of data frames.
- Use the Pandas library for data analysis.
- Read text files using Python libraries like “open” and “with.”
- Use NumPy to create one-dimensional and two-dimensional arrays.
- Write and save files in Python.
PRACTICE QUIZ 1
1. What are the most common modes used when opening a file?
- (a)ppend, (r)edline, (w)rite
- (a)ppend, (r)ead, (w)rite (CORRECT)
- (s)ave, (r)ead, (w)rite
- (a)ppend, (c)lose, (w)rite
2. What is the data attribute that will return the title of the file?
- File1.name (CORRECT)
- File1.mode
- File1.open()
- File1.close()
3. What is the command that tells Python to begin a new line?
- \b
- \q
- \e
- \n (CORRECT)
4. What attribute is used to input data into a file?
- File1.write() (CORRECT)
- File1.open()
- File1.read()
- File1.close()
5. What does the attribute name of the file object display ?
- The name of the file (CORRECT)
- The mode of the file
6. What is the advantage of using the with statement to open a file
- it automatically closes the file object (CORRECT)
- it saves a backup
7. Consider the file object File1 in write mode, what would the following line of code write to the
file:File1.write(“Hello\n world”
- Hello\n world
- Hello
- world (CORRECT)
- Hello world
correct the \n represents a new line
PRACTICE QUIZ 2
1. What python object do you cast to a dataframe?
- set
- tuple
- dictionary (CORRECT)
2. How would you access the first-row and first column in the dataframe df?
- df.ix[0,0] (CORRECT)
- df.ix[0,1]
- df.ix[1,0]
3. What is the proper way to load a CSV file using pandas?
- pandas.from_csv(‘data.csv’)
- pandas.load_csv(‘data.csv’)
- pandas.read_csv(‘data.csv’) (CORRECT)
- pandas.import_csv(‘data.csv’)
4. Use this dataframe to answer the question.
How would you select the Genre disco? Select all that apply.
- df.iloc[6, ‘genre’]
- df.loc[6, 5]
- df.iloc[6, 4] (CORRECT)
- df.loc[‘Bee Gees’, ‘Genre’]
5. Use this dataframe to answer the question.
Which will NOT evaluate to 20.6? Select all that apply.
- df.iloc[4,5]
- df.iloc[6,5]
- df.loc[4,’Music Recording Sales’] (CORRECT)
- df.iloc[6, ‘Music Recording Sales (millions)’] (CORRECT)
6. Use this dataframe to answer the question.
How do we select Albums The Dark Side of the Moon to Their Greatest Hits
- (1971-1975)? Select all that apply.
- df.iloc[2:5, ‘Album’]
- df.loc[2:5, ‘Album’] (CORRECT)
- df.iloc[2:6, 1] (CORRECT)
- df.loc[2:5, 1]
PRACTICE QUIZ 3
1. What is the Python library used for scientific computing and is a basis for Pandas?
- Tkinter
- Requests
- Numpy (CORRECT)
- datetime
2. What attribute is used to retrieve the number of elements in an array?
- a.size (CORRECT)
- a.ndim
- a.shape
- a.dtype
3. How would you change the first element to “10” in this array c:array([100,1,2,3,0])?
- c[2]=10
- c[1]=10
- c[0]=10 (CORRECT)
- c[4]=10
4. What attribute is used to return the number of dimensions in an array?
- a.size
- a.shape
- a.ndim (CORRECT)
- a.dtype
5. What is the type of the following
array:a=np.array([0,1,7,3, 7])
- int
- numpy.ndarray (CORRECT)
6. Consider the following lines of code:
c=np.array([20,1,2,3,4])
c[0]=100
c[0]=2
what is the value of c[0]
- 100
- 20
- 2 (CORRECT)
7. consider the numpy array u how would you multiply each element in the numpy array by 2
- 2*u (CORRECT)
- [2,2]*u
8. How would you perform the dot product between the numpy arrays u and v
- np.dot(u,v) (CORRECT)
- u*v
9. What is the shape of the following array:
A=np.array([[1,0,1],[0,1,1]])
- (2,3) (CORRECT)
- (3,2)
- 6
correct, the first element of the tuple is the number of rows the second is the number of columns
10. Consider the following array:
A=np.array([[1,0,1],[2,2,2]])
what is the value in A[0,1]?
- 0 (CORRECT)
- 1
- 2
11. What is the result of the following operation:
Y=np.array([[2,1],[1,2]])
Z=2*
- array([[4, 2],
- [2, 4]]) (CORRECT)
- array([[2, 2],
- [2, 2]])
- array([[2, 1],
- [1, 2]])
correct, multiplying the array by two doubles each element
MODULE 4 GRADED QUIZ
1. What is the result of the following lines of code?
a=np.array([0,1])
b=np.array([1,0])
np.dot(a,b)
- 0 (CORRECT)
- 1
- array([1,1])
2. What is the value of Z after the following code is run?
X=np.array([[1,0],[0,1]])
Y=np.array([[0,1],[1,0]])
Z=X+
- array([[1,1],[1,1]]) (CORRECT)
- array([[1,0],[0,1]])
- array([[0,1],[1,1]])
correct, the ‘+’ corresponds to matrix addition
3. What values does the variable out take if the following lines of code are run?
X=np.array([[1,0,1],[2,2,2]])
out=X[0:2,2]
out
- array([1,0])
- array([1,2]) (CORRECT)
- array([1,1])
correct, In a data frame, the very first index corresponds to the rows, while the next indexes correspond to the columns.
4. What do the following lines of code do?
with open(“Example1.txt”,”r”) as file1:
FileContent=file1.readlines()
print(FileContent)
- Read the file “Example1.txt” (CORRECT)
- Write to the file “Example1.txt”
- Append the file “Example1.txt”
Correct, the mode is set to r for read.
5. What do the following lines of code do?
with open(“Example.txt”,”w”) as writefile:
writefile.write(“This is line A\n”)
writefile.write(“This is line B\n”)
- Read the file “Example.txt”
- Write to the file “Example.txt” (CORRECT)
- Append the file “Example.txt”
6. What do the following lines of code do?
with open(“Example3.txt”,”w”) as file1:
file1.write(“This is line C\n”)
- Read the file “Example3.txt”.
- Append the file “Example3.txt”.
- error (CORRECT)
Correct. There is no indent.
7. Consider the dataframe df. How would you access the element in the 2nd row and 1st column?
- df.iloc[1,0] (CORRECT)
- df.iloc[2,1]
- df.iloc[0,1]
8. In the lab, you learned you can also obtain a series from a dataframe df, select the correct way to assign the column with the header Length to a pandas series to the variable x.
- x=df[‘Length’] (CORRECT)
- x=df[[‘Length’]]
- x=df.[[‘Length’]]
9. What is the result of the following lines of code?
a=np.array([-1,1])
b=np.array([1,1])
np.dot(a,b)
- array([0,2])
- 1
- 0 (CORRECT)
10. How do you perform matrix multiplication on the numpy arrays A and B ?
- A+B
- A*B
- np.dot(A,B) (CORRECT)
11. What values does the variable out take if the following lines of code are run?
X=np.array([[1,0,1],[2,2,2]])
out=X[0,1:3]
out
- array([0,1]) (CORRECT)
- array([1,0,1])
- array([2,2])
correct, In a certain data structure, such as a Pandas DataFrame, the first index refers to rows, and the second index refers to columns.
12. What is the value of Z after the following code is run?
X=np.array([[1,0],[0,1]])
Y=np.array([[2,2],[2,2]])
Z=np.dot(X,Y)
- array([[2,2],[2,2]]) (CORRECT)
- array([[2,0],[0,2] ])
- array([[3,2],[2,3]])
correct, the dot function corresponds to matrix multiplication
13. Consider the following text file: Example1.txt:
This is line 1
This is line 2
This is line 3
What is the output of the following lines of code?
with open(“Example1.txt”,”r”) as File1:
file_stuff=File1.readline ()
print(file_stuff)
- This is line 1 (CORRECT)
- This is line 1
- This is line 2
- This is line 3
- This is line 1
- This is line 2
14. What task do the following lines of code perform?
with open(‘Example2.txt’,’r’) as readfile:
with open(‘Example3.txt’,’w’) as writefile:
for line in readfile:
writefile.write(line)
- Check the mode of the open function for each file object.
- Copy the text from Example2.txt to Example3.txt. (CORRECT)
- Print out the content of Example2.txt.
15. What function would you use to load a csv file in Pandas?
- pd.read_csv (CORRECT)
- pd.read_excel
16. What is the value of Z after the following code is run?
X=np.array([[1,0],[0,1]])
Y=np.array([[2,1],[1,2]])
Z=np.dot(X,Y)
- array([[2,1],[1,2] ]) (CORRECT)
- array([[2,0],[1,0]])
- array([[3,1],[1,3] ])
correct, the dot function corresponds to matrix multiplication
17. Consider the following line of code:
with open(example1,”r”) as file1:
What mode is the file object in?
- read (CORRECT)
- write
- append
Correct, the mode is set to r for read.
18. What do the following lines of code do?
with open(“Example.txt”,”a”) as writefile:
writefile.write(“This is line A\n”)
writefile.write(“This is line B\n”)
- Read the file “Example.txt”
- Append the file “Example.txt” (CORRECT)
- Write to the file “Example.txt”
19. Consider the dataframe df. How would you access the element in the 1st row 3rd column
- df.iloc[2,0]
- df.iloc[1,3]
- df.iloc[0,2] (CORRECT)
20. What method gets the unique elements of the following: df[‘Length’] ?
- unique (CORRECT)
- head
21. What values does the variable out take if the following lines of code are run?
X=np.array([[1,0,1],[2,2,2]])
out=X[0:2,2]
out
- array([1,0])
- array([1,2]) (CORRECT)
- array([1,1])
correct, The first index in a data frame represents the rows while the second index represents the columns.
22. Consider the following text file: Example1.txt:
This is line 1
This is line 2
This is line 3
What is the output of the following lines of code?
with open(“Example1.txt”,”r”) as file1:
FileContent=file1.read()
print(FileContent)
- This is line 1
- This is line 2
- This is line 3 (CORRECT)
- This is line 1
- This
CONCLUSION – Working with Data in Python
All in all, this module serves as a thorough introduction to working with data in the context of Python. You will be brought on board with the most fundamental skills: reading and writing files-the basic data management procedures.
You will then go on to gain proficiency with the most powerful libraries in Python for data manipulation and mathematical operations before performing complex data analysis on your own. By the of this module, you’d have all essential knowledge and tools to carry out effective data handling and analysis in Python.