1.

Package is a directory that contains a __init__.py file which may include multiple objects; it can be downloaded and installed by installer. Libraries are bundle of codes that have specific functionalities and can be reused later in a project; libraries are naturally installed in python and don’t need to be downloaded. Click on Python Interpreter in PyCharm preference and click on the “+” sign to install package. import pandas as pd. Using abbreviation is more convenient when conducting later coding. If only certain function of a library is needed, we can import specific function. For examplefrom datetime import datetime would import only datetime function from datetime library.

2.

Data frame is a table with labeled columns of different data. “Pandas” library is most useful with data frames. Use the read_() command from pandas library to specify the library and path to file to locate a file in the operating system. Since data is stored in different types, we need to specify which type of data we re reading (html, csv, etc.). To inform pandas that we are using a tab-separated file instead of a default comma-separated file, use the command new_object = library_name.function_name(path_to_file_object, sep = '\t')

Use the command data.describe() to decribe the data. For “gapminder.csv” file, there are 6 columns and 1704 rows.

To return a list of just the column names, use list(data.columns), or the.describe() command.

3.

The year variable has a regular 5 year interval. Data from year 2012 and 2017 should be added to make it more current. A total of 284 data should be added.

4.

The country with lowest life expectancy is Rwanda with a life expectancy of 23.599 in 1992. This is because of the genocide activities against the Tutsis in the 1990s which killed up to a million and left Rwanda one of the poorest and sickest countries in the world at that time.

5.

In 2007, the GDP of these fou countries are:

In 2002, the GDP of these fou countries are:

Spain has greatest increase in total GDP: 1.77403e+11

6.

”==” indicates that the statement of one variable equalling to a certain value is true. For example, data['continent']=='Asia' means this is the data subset of the continent Asia.

“&” is the “and” symbol that is used when both statements are true in a given programming context. For example, when looking for the latest data of from a Asia, use the command data_asia = data[(data['continent']=='Asia') & (data['year'] == data['year'].max())]

” ^ “ is the exclusive or symbol. The computer would only return true if only one statement is true while the other one is flase. It would return false if both statement are true or both are false. For example, (1 + 1 == 2) ^ ("cat" == "dog")would return true but (1 + 1 > 2) ^ ("cat" == "dog") would return false.

7.

.loc()command is label-based. We need to specify the name of the rows or the columns to get the data. For example, display(data.loc[100:200])would return date from row 100 to row 200. display(data.loc[data.year >= 1997]) .iloc()command is integer index-based. We need to specify the integer index of the desired data and we need to provide the starting_index and ending_index+1 to get the desired data subset

# 8.
An API refers to Application Programming Interface. It is an intermediary that allows different applications to exchange data and functionalities in order to process requests. The following steps are how to construct a request to a remote server in order to pull data, write it to a local file and then import it to current work session.  

```python
import request
url = "https://api.covidtracking.com/v1/states/daily.csv"
from datetime import datetime as dt

After importing request and specify the url we want to use, store the data in a new subfolder if this folder is not yet exist.

import os
data_folder = 'data' if not os.path.exists(data_folder): os.makedirs(data_folder)

construct the file name:

file_name_short = 'ctp_' + str(dt.now(tz = pytz.utc)).replace(' ', '_') + '.csv'
file_name = os.path.join(data_folder, file_name_short)

now we can retrieve our data using the url and open our output file for writing in binary mode:

r = requests.get(url)
with open(file_name, 'wb') as f:
    f.write(r.content)

Finally, we import our newly created file as pandas data frame:

import pandas as pd
df = pd.read_csv(file_name)

9.

The apply.()function allows users to apply a function to all values in a given series of data; it can simplify the use of loops or functions. “.apply()” can apply a function to each row/column in a dataframe. By using “.apply()” command that works for the entire series, we don’t have to type out the the whole function again and run it with different values of the variables, which not only saves time for coding and for the program to run, but also lower the risk of making additional mistakes.

10.

We can simply type out the name of desired columns to subset the original data frame. Considering the “gapminder.csv” file, print(data[['country', 'continent', 'year', 'lifeExp', 'pop']]) and print(data.iloc(: , 0:5))can both be applied to extract “country”, “continent”, “year”, “lifeExp” and “pop” columns.