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Overview and files
project1.zip
Project 1
Please review all the material from the following Lectures before completing this assessment:
Lecture 1 - Financial Analysis with Python: Downloading Stock Prices
Lecture 2 - Python: The Building Blocks
Lecture 3 - Python: Control Flow
Lecture 4 - Working with Modules
Instructions
1. Follow the instructions provided to complete and submit your assessment.
Detailed instructions can be found in the Project description slide
2. All the files required to complete this project are included in the project1.zip file
below.
3. See the slide How to use test functions if you need help using the test functions included in this
project.
4. Once you complete the project, go to the Submit your codes here slide here to submit your code.Project Description
Project 1: Combining Data from Multiple Sources
Introduction
Finance research often requires assembling a data set from different sources. In many cases, the
source data is not formatted such that it can be imported easily into Python for analysis. This
assessment helps you develop the foundational skills of data acquisition, cleaning, and merging. You
will combine stock price information distributed across many files and produce the output as a JSON
file. We ask you to write general code, such that it can adapt easily to different file formats.
Writing general code can be a daunting exercise at first. However, it is in your best interest to practice
writing functions that can adapt to different configurations. Doing so makes your code more robust,
easier to maintain, and upgradeable.
To help you, we have provided a Python scaffold. This file, called zid_project1.py contains all the
functions needed for this project. Each function has a detailed docstring describing what the function
does, the input parameters, and the object it returns.
The remainder of this document provide information on:
The data files you will receive.
Instructions to set up your development environment in PyCharm.
Detailed step-by-step instructions required to complete the assessment. Please follow these
instructions closely. Our ability to evaluate your work requires that you do so.
You should develop your code within PyCharm. Submission, however, will be through Ed. You will
only need to copy your zid_project1.py file into Ed. Unlike the code challenges you have done so
far, Ed will not provide you any feedback on your code. You can still submit multiple times before the
deadline – Only your final submission on Ed will be marked.
The Source Files
All required files are included in a zip folder with the following structure:
project1/
| project_desc.pdf
| README.txt
| TICEKRS.txt
| zid_project1.py <-- This is the only file you need to submit
|___data/
| |_prc.dat <-- Several files of this typezid_project1.py contains the functions you will use in this assessment. Some of the functions
are already written, while others you will need to write. Please see the instructions below for
more information.
README.txt contains information about how the stock data is stored in the ".dat" files. Please
use the information contained the `README.txt` file you received (there are different versions
for different students).
TICKERS.txt contains a list of tickers and their corresponding exchanges, one per line. These
tickers and exchanges may be in upper or lower case.
project_desc.pdf is a PDF version of this document.
data is a sub-folder containing all the data you will need to complete this assessment. Inside
this folder you will find many files. Each_prc.dat contains stock price data for the ticker
. Every ticker in TICKERS.txt will have a corresponding “.dat” file. However, you may
have more “.dat” files than tickers in the TICKERS.txt file. In other words, you may have more
“.dat” files than you will need (but not fewer).
Instructions
To set up your PyCharm for this assessment, please follow the following steps:
Unzip the contents of the zip file onto your computer.
Copy/move the entire project1 folder into your PyCharm toolkit project folder. Afterwards,
your toolkit folder will look like:
toolkit/ <-- Project folder
| toolkit_config.py <-- Already created
| ...
|___project1/ <-- Contents of the zipped folder
| | project_desc.pdf
| | README.txt
| | TICEKRS.txt
| | zid_project1.py
| |
| |___data/
| | |_prc.dat
Complete the user-written functions in zid_project1.py . See the step-by-step instructions in
Completing the Code Scaffold below.
After you have completed the zid_project1.py module in PyCharm, copy and paste the entire
contents of this module to ED. This is the only file you will need to submit to complete this
assessment.
Press “Submit” to submit your project. Your project will not be submitted until you do so.
Completing the Code ScaffoldAfter setting up your PyCharm development environment with the project files (see instructions
above), modify the zid_project1.py module by taking the the steps described below, in sequence.
The completed code will produce a JSON containing the combined contents of several files. You do
not need to submit this JSON file.
Step 1: Set the location of files and folders (3 marks)
Open the zid_project1.py module in PyCharm.
Set the correct expressions for the constants ROOTDIR , DATDIR , and TICPATH as described below.
Importantly, you should not include forward slashes or backslashes when defining these variables (so
no “C:\\User. . . ”, etc. . . ). Instead, you should use the appropriate methods from the os module.
The ROOTDIR variable combines the base location of the toolkit project folder (which is
already specified in your toolkit_config.py module) and the project1 package.
The DATDIR variable combines the location in ROOTDIR above and the data sub-folder. Note
that this is a different variable than the DATADIR included in your toolkit_config.py module.
The name of the DATDIR variable is a combination of “DAT” and “DIR” (not “DATA” + “DIR”), and it
points to a different location in your computer.
The TICPATH variable combines the location in ROOTDIR and the name of the file with the
tickers (“TICKERS.txt”).
Again, all these paths should be created using the appropriate methods from the os module. If you
include any forward or backward slashes in the definition of these variables your code will only run
in your computer. A big part of this assessment is to make sure your code is portable.
The diagram below presents the relation between these variables and their locations. Again, do not
use full paths (like “C:\\Users. . . ”) to create these variables.
toolkit/
| toolkit_config.py <-- You already created this module
| ...
|___project1/ <-- `ROOTDIR` variable poitns to this folder
| | ...
| | TICEKRS.txt <-- `TICPATH` variables |points to this file
| | ...
| | zid_project1.py
| |___data/ <-- `DATDIR` variable |points to this folder
| | | ...
Note: All you have to do for this part is to replace the strings "" with the
appropriate expressions.
Step 2: Set the variables describing the format of the source data (2
marks)This part of the project is very important! Make sure you follow these instructions closely.
Before we start, open one of the “.dat” files in PyCharm. To do that, just navigate to the
toolkit/project1/data/ folder (inside PyCharm) and double click on one of the files. You will notice
the following:
1. There are no column headers. Every line in this file (including the first one) contains data.
2. There is no “separator” between columns (e.g., columns are not separated by comma, tabs, etc. .
. ). Instead, columns have a fixed width – For example, the first 10 characters belong to column
1, the next 8 to column 2, etc. . .
This means we have to create a function to split the lines into columns, so that each “value” is
assigned to its correct “data field”. The first step is to set the correct expressions for the variables
COLUMNS and COLWIDTHS .
The COLUMNS variable must be a list, where each element represents a source column name in
the README.txt file. The order of the elements in this list must match the order of the columns
in the README.txt file. For instance, suppose you have the following information in the
README.txt file:
# ----------------------------------------------------------------------------
# Column information
# ----------------------------------------------------------------------------
Close:
column position: 1
width: 14
Date:
column position: 2
width: 11
In this case, you must set COLUMNS = ['Close', 'Date']
The COLWIDTHS variable must be a dictionary. Each key is a column name in COLUMNS . Each
value is the width of this column in the README.txt file. In the example above, you would set
COLSWIDTH = {'Close': 14, 'Date': 11} .
Step 3: Complete the get_tics function (15 marks)
Complete the indicated part of the function get_tics . This function reads a file with tickers and
returns a list with formatted tickers. Make sure the function works with the given pth variable and
not the constant TICPATH (i.e., there should be no reference to the TICPATH constant inside this
function). We will test your code using different files. Using TICPATH instead of pth inside `get_tics`
means that your function always returns the same tickers instead of adapting to different possible
ticker lists.
Your function must be consistent with the docstring provided. In particular, please make sure the body of the function is consistent with the “Parameters” and “Returns” sections of the docstring. The
only exception is the optional suggestions provided in the “Hints” section, which you do not need to
follow.
Your module also includes a test function called _test_get_tics . After you finish creating the
get_tics function, it is a good idea to run the _test_get_tics function and look at the output. That
should give you a good indication if your function is performing as expected. You can uncomment the
relevant part of the if __name__ ... code block to run this test function. Like all other test functions
provided, you can modify or delete these functions – they will not be marked.
Step 4: Complete the read_dat function (5 marks)
Complete the indicated part of the function read_dat . This function reads a stock price data file for a
given ticker and returns its contents as a list of lines. Please make sure the body of the function is
consistent with the “Parameters” and “Returns” sections of the docstring. You may choose to follow
the proposed steps in the “Hints” section but that is optional.
Remember not to use literals with full paths like “C:\\Users. . . ” inside the body of the function (or
anywhere in the module). You can use the constants you created in step 1 above (e.g., DATDIR ) and
methods from the os module to create paths.
You can use the corresponding “test” function _test_read_dat to test this function once its
completed.
Step 5: Complete the line_to_dict function (10 marks)
Complete the indicated part of the function line_to_dict . The same instructions provided for the
get_tics and read_dat functions above apply to this function as well.
Step 6: Complete the verify_tickers function (10 marks)
Complete the indicated part of the function verify_tickers . This function takes in a list of tickers to
be verified, and raises an Exception if any of the tickers provided is not a key of the dictionary
returned by the get_tics function. Further details on when to raise an Exception are provided in
the "Notes" section of the docstring.
An Exception is an action that disrupts the normal flow of a program. This action is often
representative of an error being thrown. Exceptions are ways that we can elegantly recover from
errors.
To learn more about raising an Exception , you may refer to the following resource:
https://www.w3schools.com/python/gloss_python_raise.asp
Step 7: Complete the verify_cols function (10 marks)Complete the indicated part of the function verify_cols . This function takes in a list of column
names to be verified, and raises an Exception if any of the column names provided are not found in
COLUMNS . Further details on when to raise an Exception are provided in the "Notes" section of the
docstring.
Step 8: Complete the create_data_dict function (15 marks)
Complete the indicated part of the function create_data_dict . This function is used to transform
the data found in the ".dat" files into a single dictionary.
This function takes in 3 arguments:
1. tic_exchange_dic
A dictionary returned by the get_tics function.
2. tickers_lst
A list containing tickers (as strings) whose data we want to save in the dictionary returned by
create_data_dict .
3. col_lst
A list of the columns (as strings) that we want to save in the dictionary returned by
create_data_dict .
An example of how the returned dictionary should look like when we call
create_data_dict({'aapl':'nasdaq', 'baba':'nyse'}, ['aapl', 'baba'], ['Date',
'Close']) is provided below:
{
'aapl': {
'exchange': 'nasdaq',
'data': [
{
'Date': '2020-01-01',
'Close': '8.0927',
},
{
'Date': '2020-01-01',
'Close': '8.2784',
},
...
]
},
'baba': {
'exchange': 'nyse',
'data': [
{ 'Date': '2017-05-13',
'Close': '3.4939',
},
{
'Date': '2017-05-14',
'Close': '3.5689',
},
...
]
}
}
Each dictionary found in a ticker's data list should only contain the columns specified by
col_list .
The data list for each ticker should contain a dictionary for each line of the ".dat" file for that
ticker.
Note: The numbers used in the above example are entirely arbitrary for illustrative purposes only.
Step 9: Complete the create_json function (5 marks)
Complete the indicated part of the function create_json . This function saves a given dictionary into
JSON file. To learn more about how to write data to a JSON file, take a look at the documentation for
the following methods from the built-in Python package json :
json.dump
json.dumps
Step 10: Open-ended question (25 marks)
Explain why to configure as in step 1 (5 mark).
From step 9, we can obtain a JSON file that contains ticker names, listed exchanges, trading
volume, and stock prices, and compute stock returns from stock prices. Suppose we have an
extra variable to proxy the journalists' views about the firm performance, and we are interested
in evaluating 2 alternative hypotheses:
Whether the articles journalists wrote are based on:
Investors' evaluations of those firms?
Valuable information beyond firm fundamentals?
Suppose we have observed the following:
When the articles contain relatively more negative words,
Stock returns decrease in the short run with no reversal in the long run.
Explain which one of the two hypotheses is more likely to be true. Please evaluate both
hypotheses. (15 marks)
Given the hypothesis you have chosen, evaluate the short-run predictability for the trading volume with reason(s). (5 marks)
Submit your module
Copy and paste the entire content of your zid_project1.py to Ed and press “Submit”. Ed will not
mark your project automatically or give you any feedback. After you submit, we will be able to mark
your project.
Administrative Guidelines, Additional Hints, Marking
Administrative Guidelines
We will enforce the following:
This assessment must be completed individually. Failure to complete the assignment on your
own may result in a full loss of marks.
Late submissions are allowed, but will be penalised according to the rules described in the
course outline.
Hints
Your code should be portable, working in a variety of settings. It should be sufficient to copy your
code from PyCharm to Ed for submission. However, as part of this assessment, you need to make
sure that your code works on our computer as well as on yours.
The following hints should help you correct any portability mistakes:
The contents of your zid_project1.py module must not contain any direct reference to
folders in your computer. Variables that define paths should not contain any forward or
backslashes. Of course, the variables you defined in your toolkit_config.py module (which
you do not have to submit) do contain forward or backslashes (depending on your operating
system). This is one of the reasons why we created this file to begin with.
Similarly, you should not include strings with specific tickers in zid_project1.py module (e.g.,
"TSLA", "AAPL"). For instance, you should not create a variable called tickers and then copy
the specific tickers you received in your TICKERS.txt file. Instead, your code should read the
TICKERS.txt file, produce a list of tickers, and store that in a variable.
When writing functions in the file zid_project1.py :
Do not modify the function names or the parameters.
Only modify the parts indicated by the "" tag.
You do not need to import any other module. Please do not modify the import
statements.
You should not create any additional constants. The constants that exist in the file ( ROOTDIR , DATDIR , TICPATH , COLUMNS , and COLWIDTHS ) should be edited as instructed.
The "test" functions are included to help you test the code as you work through the
project. These functions will not be marked, and you may change them as necessary to
suit your needs. Test functions are clearly identified in the file with names starting with
_test .
Use all the parameters in a function declaration. For example, the function get_tics(pth) has
the single parameter pth . Make sure that your function uses this parameter and not a global
variable.
Only submit the zid_project1.py module. Make sure your code works with this module only.
No other modules can be submitted.
How we will mark your assessment
The following parts of this assessment will be marked:
1. Location of files and folders (3 marks)
2. Set the variables describing the format of the source data (2 marks)
3. Complete the get_tics function (15 marks)
4. Complete the read_dat function (5 marks)
5. Complete the line_to_dict function (10 marks)
6. Complete the verify_tickers function (10 marks)
7. Complete the verify_cols function (10 marks)
8. Complete the create_data_dict function (15 marks)
9. Complete the create_json function (5 marks)
10. Open-ended question (25 marks)
To receive full credit for parts 1 and 2, your variables must:
Have the correct type (e.g., COLWIDTHS must be a dictionary)
Include the correct values (e.g., the order of the columns in COLUMNS must match the one
specified in your README.TXT file,
Follow all the instructions in this file (e.g., no forward or backslashes in TICPATH ).
To receive full credit in parts 3 - 9, your functions must:
Return the correct object type (described in the docstring)
Return the correct information from the TICKERS.txt , README.txt , and “.dat” files you
received.
Not violate any of the rules we specified in this document or in the docstring
If your function opens a file, you must use a context manager.Submit your codes here
Instructions
1. Copy and paste the contents of the complete zid_project1.py file to the zid_project1.py
tab you see on the right.
Only the contents of the zid_project1.py file should be submitted.
Do not rename the zid_project1.py .
2. Press "Submit" to submit your assessment.
You only have to submit your project once.
Notes:
For this assessment, you will NOT be able to run your code in ED
The system will NOT provide you with any feedback. There are no test cases.
All comments in your code will be ignored.
We will post an announcement after we finish marking the assessment.
An error occurred.
Try watching this video on www.youtube.com, or enable JavaScript if it is disabled in your browser.How to use test functions
The test functions we created will typically print the output of the function they are intended to test.
I included a use case below to illustrate a typical workflow. Although the examples use Ed's "run
boxes" to execute the programs, you should do all the testing in PyCharm.
Suppose you had to create a function to format strings in a particular way. You would be given
something like this:
def fmt_str(s):
""" Formats a string to conform with the following rules (in order):
1. No leading or trailing spaces
2. Remaining white spaces replaced by '_'
3. All characters should be lower case
Parameters
----------
s : str
Returns
-------
str
Formatted string
"""
pass
def _test_fmt_str():
""" Test function for `fmt_str`
"""
s = ' Test String '
res = fmt_str(s)
print(res)
if __name__ == "__main__":
# Test functions
# _test_fmt_str()
The first step is to complete (at least part) of the function _fmt_str .
def fmt_str(s):
""" Formats a string to conform with the following rules (in order):
1. No leading or trailing spaces
2. Remaining white spaces replaced by '_'
3. All characters should be lower case Parameters
----------
s : str
Returns
-------
str
Formatted string
"""
# no leading or trailing spaces
res = s.strip() # ** STEP 1 **
def _test_fmt_str():
""" Test function for `fmt_str`
"""
s = ' Test String '
res = fmt_str(s)
print(res)
if __name__ == "__main__":
# Test functions
# _test_fmt_str()
Then, you should uncomment the test function call statement under the if __name__ ... code
block and execute the program:
def fmt_str(s):
""" Formats a string to conform with the following rules (in order):
1. No leading or trailing spaces
2. Remaining white spaces replaced by '_'
3. All characters should be lower case
Parameters
----------
s : str
Returns
-------
str
Formatted string
"""
# no leading or trailing spaces
res = s.strip() # ** STEP 1 **
def _test_fmt_str():
""" Test function for `fmt_str`
"""
s = ' Test String '
res = fmt_str(s)
print(res)if __name__ == "__main__":
# Test functions
_test_fmt_str() # ** STEP 2 **
If you run the code above, you will notice that the test function printed None . This is because we
forgot to include a return statement in the function. Let's revise the first step:
def fmt_str(s):
""" Formats a string to conform with the following rules (in order):
1. No leading or trailing spaces
2. Remaining white spaces replaced by '_'
3. All characters should be lower case
Parameters
----------
s : str
Returns
-------
str
Formatted string
"""
# no leading or trailing spaces
res = s.strip() # ** STEP 1a **
return res # ** STEP 1b **
def _test_fmt_str():
""" Test function for `fmt_str`
"""
s = ' Test String '
res = fmt_str(s)
print(res)
if __name__ == "__main__":
# Test functions
_test_fmt_str() # ** STEP 2 **
The function will print the test string with no leading or trailing spaces. However, there are still white
spaces inside the string, and some characters are still capitalised.
The goal now is to keep changing the fmt_str function until it produces the desired output:
def fmt_str(s):
""" Formats a string to conform with the following rules (in order):
1. No leading or trailing spaces
2. Remaining white spaces replaced by '_' 3. All characters should be lower case
Parameters
----------
s : str
Returns
-------
str
Formatted string
"""
# no leading or trailing spaces
res = s.strip() # ** STEP 1a **
res = res.replace(' ', '_') # ** STEP 3a **
res = res.lower() # ** STEP 3b **
return res # ** STEP 1b **
def _test_fmt_str():
""" Test function for `fmt_str`
"""
s = ' Test String '
res = fmt_str(s)
print(res)
if __name__ == "__main__":
# Test functions
_test_fmt_str() # ** STEP 2 **
Once you are satisfied with the function, you can comment the _test_fmt_str() you uncommented
in step 2.
Some test functions depend on the output of other functions. For instance, suppose you also had to
create another function called split_str , which would split strings using and underscore as a
separator ("_"). Below is the new version of the module:
def fmt_str(s):
""" Formats a string to conform with the following rules (in order):
1. No leading or trailing spaces
2. Remaining white spaces replaced by '_'
3. All characters should be lower case
Parameters
----------
s : str
Returns
------- str
Formatted string
"""
pass
def split_str(s):
""" Splits the string using "_" as separator.
If no "_" is found, returns a list with a single element, the string `s`'
Parameters
----------
s : str
Returns
-------
list
"""
pass
def _test_fmt_str():
""" Test function for `fmt_str`
"""
s = ' Test String '
res = fmt_str(s)
print(res)
def _test_split_str():
""" Test function for `split_str`
"""
s = ' Test String '
s = fmt_str(s) # This function is not the one being tested!!!
lst = split_str(s)
print(lst)
if __name__ == "__main__":
# Test functions
#_test_fmt_str()
#_test_split_str()
What happens if (for some reason), you would like to write the split_str function before the
fmt_str ? In that case, you need to change the _test_split_str function so it does not depend on
the output of fmt_str . You can easily do that because the docstring of split_str determines the
type of its parameters:
def fmt_str(s):
""" Formats a string to conform with the following rules (in order): 1. No leading or trailing spaces
2. Remaining white spaces replaced by '_'
3. All characters should be lower case
Parameters
----------
s : str
Returns
-------
str
Formatted string
"""
pass
def split_str(s):
""" Splits the string using "_" as separator.
If no "_" is found, returns a list with a single element, the string `s`'
Parameters
----------
s : str
Returns
-------
list
"""
pass
def _test_fmt_str():
""" Test function for `fmt_str`
"""
s = ' Test String '
res = fmt_str(s)
print(res)
def _test_split_str():
""" Test function for `split_str`
"""
# ** NEW STEP 1 STARTS HERE
# (1a) Comment `fmt_str` function call
#s = ' Test String '
#s = fmt_str(s)
# (1b) Create a new test case
s = 'test_string'
# ** NEW STEP 1 ENDS HERE
lst = split_str(s)
print(lst)if __name__ == "__main__":
# Test functions
#_test_fmt_str()
#_test_split_str()
Now, we can write the function split_str before we finish writing fmt_str . This is not
recommended but it's useful if you get stuck completing one of the intermediary functions:
def fmt_str(s):
""" Formats a string to conform with the following rules (in order):
1. No leading or trailing spaces
2. Remaining white spaces replaced by '_'
3. All characters should be lower case
Parameters
----------
s : str
Returns
-------
str
Formatted string
"""
pass
def split_str(s):
""" Splits the string using "_" as separator.
If no "_" is found, returns a list with a single element, the string `s`'
Parameters
----------
s : str
Returns
-------
list
"""
return s.split('_') # ** NEW STEP 2 **
def _test_fmt_str():
""" Test function for `fmt_str`
"""
s = ' Test String '
res = fmt_str(s)
print(res)
def _test_split_str(): """ Test function for `split_str`
"""
# ** NEW STEP 1 STARTS HERE
# (1a) Comment `fmt_str` function call
#s = ' Test String '
#s = fmt_str(s)
# (1b) Create a new test case
s = 'test_string'
# ** NEW STEP 1 ENDS HERE
lst = split_str(s)
print(lst)
if __name__ == "__main__":
# Test functions
#_test_fmt_str()
_test_split_str() # ** NEW STEP 3 **
Overview and files
project1.zip
Project 1
Please review all the material from the following Lectures before completing this assessment:
Lecture 1 - Financial Analysis with Python: Downloading Stock Prices
Lecture 2 - Python: The Building Blocks
Lecture 3 - Python: Control Flow
Lecture 4 - Working with Modules
Instructions
1. Follow the instructions provided to complete and submit your assessment.
Detailed instructions can be found in the Project description slide
2. All the files required to complete this project are included in the project1.zip file
below.
3. See the slide How to use test functions if you need help using the test functions included in this
project.
4. Once you complete the project, go to the Submit your codes here slide here to submit your code.Project Description
Project 1: Combining Data from Multiple Sources
Introduction
Finance research often requires assembling a data set from different sources. In many cases, the
source data is not formatted such that it can be imported easily into Python for analysis. This
assessment helps you develop the foundational skills of data acquisition, cleaning, and merging. You
will combine stock price information distributed across many files and produce the output as a JSON
file. We ask you to write general code, such that it can adapt easily to different file formats.
Writing general code can be a daunting exercise at first. However, it is in your best interest to practice
writing functions that can adapt to different configurations. Doing so makes your code more robust,
easier to maintain, and upgradeable.
To help you, we have provided a Python scaffold. This file, called zid_project1.py contains all the
functions needed for this project. Each function has a detailed docstring describing what the function
does, the input parameters, and the object it returns.
The remainder of this document provide information on:
The data files you will receive.
Instructions to set up your development environment in PyCharm.
Detailed step-by-step instructions required to complete the assessment. Please follow these
instructions closely. Our ability to evaluate your work requires that you do so.
You should develop your code within PyCharm. Submission, however, will be through Ed. You will
only need to copy your zid_project1.py file into Ed. Unlike the code challenges you have done so
far, Ed will not provide you any feedback on your code. You can still submit multiple times before the
deadline – Only your final submission on Ed will be marked.
The Source Files
All required files are included in a zip folder with the following structure:
project1/
| project_desc.pdf
| README.txt
| TICEKRS.txt
| zid_project1.py <-- This is the only file you need to submit
|___data/
| |
are already written, while others you will need to write. Please see the instructions below for
more information.
README.txt contains information about how the stock data is stored in the ".dat" files. Please
use the information contained the `README.txt` file you received (there are different versions
for different students).
TICKERS.txt contains a list of tickers and their corresponding exchanges, one per line. These
tickers and exchanges may be in upper or lower case.
project_desc.pdf is a PDF version of this document.
data is a sub-folder containing all the data you will need to complete this assessment. Inside
this folder you will find many files. Each
have more “.dat” files than tickers in the TICKERS.txt file. In other words, you may have more
“.dat” files than you will need (but not fewer).
Instructions
To set up your PyCharm for this assessment, please follow the following steps:
Unzip the contents of the zip file onto your computer.
Copy/move the entire project1 folder into your PyCharm toolkit project folder. Afterwards,
your toolkit folder will look like:
toolkit/ <-- Project folder
| toolkit_config.py <-- Already created
| ...
|___project1/ <-- Contents of the zipped folder
| | project_desc.pdf
| | README.txt
| | TICEKRS.txt
| | zid_project1.py
| |
| |___data/
| | |
Complete the user-written functions in zid_project1.py . See the step-by-step instructions in
Completing the Code Scaffold below.
After you have completed the zid_project1.py module in PyCharm, copy and paste the entire
contents of this module to ED. This is the only file you will need to submit to complete this
assessment.
Press “Submit” to submit your project. Your project will not be submitted until you do so.
Completing the Code ScaffoldAfter setting up your PyCharm development environment with the project files (see instructions
above), modify the zid_project1.py module by taking the the steps described below, in sequence.
The completed code will produce a JSON containing the combined contents of several files. You do
not need to submit this JSON file.
Step 1: Set the location of files and folders (3 marks)
Open the zid_project1.py module in PyCharm.
Set the correct expressions for the constants ROOTDIR , DATDIR , and TICPATH as described below.
Importantly, you should not include forward slashes or backslashes when defining these variables (so
no “C:\\User. . . ”, etc. . . ). Instead, you should use the appropriate methods from the os module.
The ROOTDIR variable combines the base location of the toolkit project folder (which is
already specified in your toolkit_config.py module) and the project1 package.
The DATDIR variable combines the location in ROOTDIR above and the data sub-folder. Note
that this is a different variable than the DATADIR included in your toolkit_config.py module.
The name of the DATDIR variable is a combination of “DAT” and “DIR” (not “DATA” + “DIR”), and it
points to a different location in your computer.
The TICPATH variable combines the location in ROOTDIR and the name of the file with the
tickers (“TICKERS.txt”).
Again, all these paths should be created using the appropriate methods from the os module. If you
include any forward or backward slashes in the definition of these variables your code will only run
in your computer. A big part of this assessment is to make sure your code is portable.
The diagram below presents the relation between these variables and their locations. Again, do not
use full paths (like “C:\\Users. . . ”) to create these variables.
toolkit/
| toolkit_config.py <-- You already created this module
| ...
|___project1/ <-- `ROOTDIR` variable poitns to this folder
| | ...
| | TICEKRS.txt <-- `TICPATH` variables |points to this file
| | ...
| | zid_project1.py
| |___data/ <-- `DATDIR` variable |points to this folder
| | | ...
Note: All you have to do for this part is to replace the strings "
appropriate expressions.
Step 2: Set the variables describing the format of the source data (2
marks)This part of the project is very important! Make sure you follow these instructions closely.
Before we start, open one of the “.dat” files in PyCharm. To do that, just navigate to the
toolkit/project1/data/ folder (inside PyCharm) and double click on one of the files. You will notice
the following:
1. There are no column headers. Every line in this file (including the first one) contains data.
2. There is no “separator” between columns (e.g., columns are not separated by comma, tabs, etc. .
. ). Instead, columns have a fixed width – For example, the first 10 characters belong to column
1, the next 8 to column 2, etc. . .
This means we have to create a function to split the lines into columns, so that each “value” is
assigned to its correct “data field”. The first step is to set the correct expressions for the variables
COLUMNS and COLWIDTHS .
The COLUMNS variable must be a list, where each element represents a source column name in
the README.txt file. The order of the elements in this list must match the order of the columns
in the README.txt file. For instance, suppose you have the following information in the
README.txt file:
# ----------------------------------------------------------------------------
# Column information
# ----------------------------------------------------------------------------
Close:
column position: 1
width: 14
Date:
column position: 2
width: 11
In this case, you must set COLUMNS = ['Close', 'Date']
The COLWIDTHS variable must be a dictionary. Each key is a column name in COLUMNS . Each
value is the width of this column in the README.txt file. In the example above, you would set
COLSWIDTH = {'Close': 14, 'Date': 11} .
Step 3: Complete the get_tics function (15 marks)
Complete the indicated part of the function get_tics . This function reads a file with tickers and
returns a list with formatted tickers. Make sure the function works with the given pth variable and
not the constant TICPATH (i.e., there should be no reference to the TICPATH constant inside this
function). We will test your code using different files. Using TICPATH instead of pth inside `get_tics`
means that your function always returns the same tickers instead of adapting to different possible
ticker lists.
Your function must be consistent with the docstring provided. In particular, please make sure the body of the function is consistent with the “Parameters” and “Returns” sections of the docstring. The
only exception is the optional suggestions provided in the “Hints” section, which you do not need to
follow.
Your module also includes a test function called _test_get_tics . After you finish creating the
get_tics function, it is a good idea to run the _test_get_tics function and look at the output. That
should give you a good indication if your function is performing as expected. You can uncomment the
relevant part of the if __name__ ... code block to run this test function. Like all other test functions
provided, you can modify or delete these functions – they will not be marked.
Step 4: Complete the read_dat function (5 marks)
Complete the indicated part of the function read_dat . This function reads a stock price data file for a
given ticker and returns its contents as a list of lines. Please make sure the body of the function is
consistent with the “Parameters” and “Returns” sections of the docstring. You may choose to follow
the proposed steps in the “Hints” section but that is optional.
Remember not to use literals with full paths like “C:\\Users. . . ” inside the body of the function (or
anywhere in the module). You can use the constants you created in step 1 above (e.g., DATDIR ) and
methods from the os module to create paths.
You can use the corresponding “test” function _test_read_dat to test this function once its
completed.
Step 5: Complete the line_to_dict function (10 marks)
Complete the indicated part of the function line_to_dict . The same instructions provided for the
get_tics and read_dat functions above apply to this function as well.
Step 6: Complete the verify_tickers function (10 marks)
Complete the indicated part of the function verify_tickers . This function takes in a list of tickers to
be verified, and raises an Exception if any of the tickers provided is not a key of the dictionary
returned by the get_tics function. Further details on when to raise an Exception are provided in
the "Notes" section of the docstring.
An Exception is an action that disrupts the normal flow of a program. This action is often
representative of an error being thrown. Exceptions are ways that we can elegantly recover from
errors.
To learn more about raising an Exception , you may refer to the following resource:
https://www.w3schools.com/python/gloss_python_raise.asp
Step 7: Complete the verify_cols function (10 marks)Complete the indicated part of the function verify_cols . This function takes in a list of column
names to be verified, and raises an Exception if any of the column names provided are not found in
COLUMNS . Further details on when to raise an Exception are provided in the "Notes" section of the
docstring.
Step 8: Complete the create_data_dict function (15 marks)
Complete the indicated part of the function create_data_dict . This function is used to transform
the data found in the ".dat" files into a single dictionary.
This function takes in 3 arguments:
1. tic_exchange_dic
A dictionary returned by the get_tics function.
2. tickers_lst
A list containing tickers (as strings) whose data we want to save in the dictionary returned by
create_data_dict .
3. col_lst
A list of the columns (as strings) that we want to save in the dictionary returned by
create_data_dict .
An example of how the returned dictionary should look like when we call
create_data_dict({'aapl':'nasdaq', 'baba':'nyse'}, ['aapl', 'baba'], ['Date',
'Close']) is provided below:
{
'aapl': {
'exchange': 'nasdaq',
'data': [
{
'Date': '2020-01-01',
'Close': '8.0927',
},
{
'Date': '2020-01-01',
'Close': '8.2784',
},
...
]
},
'baba': {
'exchange': 'nyse',
'data': [
{ 'Date': '2017-05-13',
'Close': '3.4939',
},
{
'Date': '2017-05-14',
'Close': '3.5689',
},
...
]
}
}
Each dictionary found in a ticker's data list should only contain the columns specified by
col_list .
The data list for each ticker should contain a dictionary for each line of the ".dat" file for that
ticker.
Note: The numbers used in the above example are entirely arbitrary for illustrative purposes only.
Step 9: Complete the create_json function (5 marks)
Complete the indicated part of the function create_json . This function saves a given dictionary into
JSON file. To learn more about how to write data to a JSON file, take a look at the documentation for
the following methods from the built-in Python package json :
json.dump
json.dumps
Step 10: Open-ended question (25 marks)
Explain why to configure as in step 1 (5 mark).
From step 9, we can obtain a JSON file that contains ticker names, listed exchanges, trading
volume, and stock prices, and compute stock returns from stock prices. Suppose we have an
extra variable to proxy the journalists' views about the firm performance, and we are interested
in evaluating 2 alternative hypotheses:
Whether the articles journalists wrote are based on:
Investors' evaluations of those firms?
Valuable information beyond firm fundamentals?
Suppose we have observed the following:
When the articles contain relatively more negative words,
Stock returns decrease in the short run with no reversal in the long run.
Explain which one of the two hypotheses is more likely to be true. Please evaluate both
hypotheses. (15 marks)
Given the hypothesis you have chosen, evaluate the short-run predictability for the trading volume with reason(s). (5 marks)
Submit your module
Copy and paste the entire content of your zid_project1.py to Ed and press “Submit”. Ed will not
mark your project automatically or give you any feedback. After you submit, we will be able to mark
your project.
Administrative Guidelines, Additional Hints, Marking
Administrative Guidelines
We will enforce the following:
This assessment must be completed individually. Failure to complete the assignment on your
own may result in a full loss of marks.
Late submissions are allowed, but will be penalised according to the rules described in the
course outline.
Hints
Your code should be portable, working in a variety of settings. It should be sufficient to copy your
code from PyCharm to Ed for submission. However, as part of this assessment, you need to make
sure that your code works on our computer as well as on yours.
The following hints should help you correct any portability mistakes:
The contents of your zid_project1.py module must not contain any direct reference to
folders in your computer. Variables that define paths should not contain any forward or
backslashes. Of course, the variables you defined in your toolkit_config.py module (which
you do not have to submit) do contain forward or backslashes (depending on your operating
system). This is one of the reasons why we created this file to begin with.
Similarly, you should not include strings with specific tickers in zid_project1.py module (e.g.,
"TSLA", "AAPL"). For instance, you should not create a variable called tickers and then copy
the specific tickers you received in your TICKERS.txt file. Instead, your code should read the
TICKERS.txt file, produce a list of tickers, and store that in a variable.
When writing functions in the file zid_project1.py :
Do not modify the function names or the parameters.
Only modify the parts indicated by the "
You do not need to import any other module. Please do not modify the import
statements.
You should not create any additional constants. The constants that exist in the file ( ROOTDIR , DATDIR , TICPATH , COLUMNS , and COLWIDTHS ) should be edited as instructed.
The "test" functions are included to help you test the code as you work through the
project. These functions will not be marked, and you may change them as necessary to
suit your needs. Test functions are clearly identified in the file with names starting with
_test .
Use all the parameters in a function declaration. For example, the function get_tics(pth) has
the single parameter pth . Make sure that your function uses this parameter and not a global
variable.
Only submit the zid_project1.py module. Make sure your code works with this module only.
No other modules can be submitted.
How we will mark your assessment
The following parts of this assessment will be marked:
1. Location of files and folders (3 marks)
2. Set the variables describing the format of the source data (2 marks)
3. Complete the get_tics function (15 marks)
4. Complete the read_dat function (5 marks)
5. Complete the line_to_dict function (10 marks)
6. Complete the verify_tickers function (10 marks)
7. Complete the verify_cols function (10 marks)
8. Complete the create_data_dict function (15 marks)
9. Complete the create_json function (5 marks)
10. Open-ended question (25 marks)
To receive full credit for parts 1 and 2, your variables must:
Have the correct type (e.g., COLWIDTHS must be a dictionary)
Include the correct values (e.g., the order of the columns in COLUMNS must match the one
specified in your README.TXT file,
Follow all the instructions in this file (e.g., no forward or backslashes in TICPATH ).
To receive full credit in parts 3 - 9, your functions must:
Return the correct object type (described in the docstring)
Return the correct information from the TICKERS.txt , README.txt , and “.dat” files you
received.
Not violate any of the rules we specified in this document or in the docstring
If your function opens a file, you must use a context manager.Submit your codes here
Instructions
1. Copy and paste the contents of the complete zid_project1.py file to the zid_project1.py
tab you see on the right.
Only the contents of the zid_project1.py file should be submitted.
Do not rename the zid_project1.py .
2. Press "Submit" to submit your assessment.
You only have to submit your project once.
Notes:
For this assessment, you will NOT be able to run your code in ED
The system will NOT provide you with any feedback. There are no test cases.
All comments in your code will be ignored.
We will post an announcement after we finish marking the assessment.
An error occurred.
Try watching this video on www.youtube.com, or enable JavaScript if it is disabled in your browser.How to use test functions
The test functions we created will typically print the output of the function they are intended to test.
I included a use case below to illustrate a typical workflow. Although the examples use Ed's "run
boxes" to execute the programs, you should do all the testing in PyCharm.
Suppose you had to create a function to format strings in a particular way. You would be given
something like this:
def fmt_str(s):
""" Formats a string to conform with the following rules (in order):
1. No leading or trailing spaces
2. Remaining white spaces replaced by '_'
3. All characters should be lower case
Parameters
----------
s : str
Returns
-------
str
Formatted string
"""
pass
def _test_fmt_str():
""" Test function for `fmt_str`
"""
s = ' Test String '
res = fmt_str(s)
print(res)
if __name__ == "__main__":
# Test functions
# _test_fmt_str()
The first step is to complete (at least part) of the function _fmt_str .
def fmt_str(s):
""" Formats a string to conform with the following rules (in order):
1. No leading or trailing spaces
2. Remaining white spaces replaced by '_'
3. All characters should be lower case Parameters
----------
s : str
Returns
-------
str
Formatted string
"""
# no leading or trailing spaces
res = s.strip() # ** STEP 1 **
def _test_fmt_str():
""" Test function for `fmt_str`
"""
s = ' Test String '
res = fmt_str(s)
print(res)
if __name__ == "__main__":
# Test functions
# _test_fmt_str()
Then, you should uncomment the test function call statement under the if __name__ ... code
block and execute the program:
def fmt_str(s):
""" Formats a string to conform with the following rules (in order):
1. No leading or trailing spaces
2. Remaining white spaces replaced by '_'
3. All characters should be lower case
Parameters
----------
s : str
Returns
-------
str
Formatted string
"""
# no leading or trailing spaces
res = s.strip() # ** STEP 1 **
def _test_fmt_str():
""" Test function for `fmt_str`
"""
s = ' Test String '
res = fmt_str(s)
print(res)if __name__ == "__main__":
# Test functions
_test_fmt_str() # ** STEP 2 **
If you run the code above, you will notice that the test function printed None . This is because we
forgot to include a return statement in the function. Let's revise the first step:
def fmt_str(s):
""" Formats a string to conform with the following rules (in order):
1. No leading or trailing spaces
2. Remaining white spaces replaced by '_'
3. All characters should be lower case
Parameters
----------
s : str
Returns
-------
str
Formatted string
"""
# no leading or trailing spaces
res = s.strip() # ** STEP 1a **
return res # ** STEP 1b **
def _test_fmt_str():
""" Test function for `fmt_str`
"""
s = ' Test String '
res = fmt_str(s)
print(res)
if __name__ == "__main__":
# Test functions
_test_fmt_str() # ** STEP 2 **
The function will print the test string with no leading or trailing spaces. However, there are still white
spaces inside the string, and some characters are still capitalised.
The goal now is to keep changing the fmt_str function until it produces the desired output:
def fmt_str(s):
""" Formats a string to conform with the following rules (in order):
1. No leading or trailing spaces
2. Remaining white spaces replaced by '_' 3. All characters should be lower case
Parameters
----------
s : str
Returns
-------
str
Formatted string
"""
# no leading or trailing spaces
res = s.strip() # ** STEP 1a **
res = res.replace(' ', '_') # ** STEP 3a **
res = res.lower() # ** STEP 3b **
return res # ** STEP 1b **
def _test_fmt_str():
""" Test function for `fmt_str`
"""
s = ' Test String '
res = fmt_str(s)
print(res)
if __name__ == "__main__":
# Test functions
_test_fmt_str() # ** STEP 2 **
Once you are satisfied with the function, you can comment the _test_fmt_str() you uncommented
in step 2.
Some test functions depend on the output of other functions. For instance, suppose you also had to
create another function called split_str , which would split strings using and underscore as a
separator ("_"). Below is the new version of the module:
def fmt_str(s):
""" Formats a string to conform with the following rules (in order):
1. No leading or trailing spaces
2. Remaining white spaces replaced by '_'
3. All characters should be lower case
Parameters
----------
s : str
Returns
------- str
Formatted string
"""
pass
def split_str(s):
""" Splits the string using "_" as separator.
If no "_" is found, returns a list with a single element, the string `s`'
Parameters
----------
s : str
Returns
-------
list
"""
pass
def _test_fmt_str():
""" Test function for `fmt_str`
"""
s = ' Test String '
res = fmt_str(s)
print(res)
def _test_split_str():
""" Test function for `split_str`
"""
s = ' Test String '
s = fmt_str(s) # This function is not the one being tested!!!
lst = split_str(s)
print(lst)
if __name__ == "__main__":
# Test functions
#_test_fmt_str()
#_test_split_str()
What happens if (for some reason), you would like to write the split_str function before the
fmt_str ? In that case, you need to change the _test_split_str function so it does not depend on
the output of fmt_str . You can easily do that because the docstring of split_str determines the
type of its parameters:
def fmt_str(s):
""" Formats a string to conform with the following rules (in order): 1. No leading or trailing spaces
2. Remaining white spaces replaced by '_'
3. All characters should be lower case
Parameters
----------
s : str
Returns
-------
str
Formatted string
"""
pass
def split_str(s):
""" Splits the string using "_" as separator.
If no "_" is found, returns a list with a single element, the string `s`'
Parameters
----------
s : str
Returns
-------
list
"""
pass
def _test_fmt_str():
""" Test function for `fmt_str`
"""
s = ' Test String '
res = fmt_str(s)
print(res)
def _test_split_str():
""" Test function for `split_str`
"""
# ** NEW STEP 1 STARTS HERE
# (1a) Comment `fmt_str` function call
#s = ' Test String '
#s = fmt_str(s)
# (1b) Create a new test case
s = 'test_string'
# ** NEW STEP 1 ENDS HERE
lst = split_str(s)
print(lst)if __name__ == "__main__":
# Test functions
#_test_fmt_str()
#_test_split_str()
Now, we can write the function split_str before we finish writing fmt_str . This is not
recommended but it's useful if you get stuck completing one of the intermediary functions:
def fmt_str(s):
""" Formats a string to conform with the following rules (in order):
1. No leading or trailing spaces
2. Remaining white spaces replaced by '_'
3. All characters should be lower case
Parameters
----------
s : str
Returns
-------
str
Formatted string
"""
pass
def split_str(s):
""" Splits the string using "_" as separator.
If no "_" is found, returns a list with a single element, the string `s`'
Parameters
----------
s : str
Returns
-------
list
"""
return s.split('_') # ** NEW STEP 2 **
def _test_fmt_str():
""" Test function for `fmt_str`
"""
s = ' Test String '
res = fmt_str(s)
print(res)
def _test_split_str(): """ Test function for `split_str`
"""
# ** NEW STEP 1 STARTS HERE
# (1a) Comment `fmt_str` function call
#s = ' Test String '
#s = fmt_str(s)
# (1b) Create a new test case
s = 'test_string'
# ** NEW STEP 1 ENDS HERE
lst = split_str(s)
print(lst)
if __name__ == "__main__":
# Test functions
#_test_fmt_str()
_test_split_str() # ** NEW STEP 3 **