import requests # you need this module to make an API call
import pandas as pd

api_url = "http://api.open-notify.org/astros.json" # this url gives use the astronaut data

response = requests.get(api_url) # Call the API using the get method and store the
                                # output of the API call in a variable called response.

if response.ok:             # if all is well() no errors, no network timeouts)
    data = response.json()  # store the result in json format in a variable called data
                            # the variable data is of type dictionary.

print(data)   # print the data just to check the output or for debugging

{'number': 10, 'people': [{'name': 'Oleg Artemyev', 'craft': 'ISS'}, {'name': 'Denis Matveev', 'craft': 'ISS'}, {'name': 'Sergey Korsakov', 'craft': 'ISS'}, {'name': 'Kjell Lindgren', 'craft': 'ISS'}, {'name': 'Bob Hines', 'craft': 'ISS'}, {'name': 'Samantha Cristoforetti', 'craft': 'ISS'}, {'name': 'Jessica Watkins', 'craft': 'ISS'}, {'name': 'Cai Xuzhe', 'craft': 'Tiangong'}, {'name': 'Chen Dong', 'craft': 'Tiangong'}, {'name': 'Liu Yang', 'craft': 'Tiangong'}], 'message': 'success'}

print(data.get('number'))

10

astronauts = data.get('people')
print("There are {} astronauts on ISS".format(len(astronauts)))
print("And their names are :")
for astronaut in astronauts:
    print(astronaut.get('name'))

There are 10 astronauts on ISS
And their names are :
Oleg Artemyev
Denis Matveev
Sergey Korsakov
Kjell Lindgren
Bob Hines
Samantha Cristoforetti
Jessica Watkins
Cai Xuzhe
Chen Dong
Liu Yang

#Import required libraries
import pandas as pd
import json

api_url="http://127.0.0.1:5000/data"
def get_number_of_jobs_T(technology):
    #your code goes here
    number_of_jobs = 0
    payload={"Key Skills":technology}
    response=requests.get(api_url,params=payload)
    if response.ok:             # if all is well() no errors, no network timeouts)
        data = response.json()  # store the result in json format in a variable called data
                                # the variable data is of type dictionary.
        number_of_jobs= number_of_jobs + len(data)
    return technology,number_of_jobs

get_number_of_jobs_T("Python")

('Python', 1173)

def get_number_of_jobs_L(location):
    
    #your coe goes here
    number_of_jobs = 0
    payload={"Location":location}
    response=requests.get(api_url,params=payload)
    if response.ok:             # if all is well() no errors, no network timeouts)
        data = response.json()  # store the result in json format in a variable called data
                                # the variable data is of type dictionary.
        number_of_jobs= number_of_jobs + len(data)
    return location,number_of_jobs

#your code goes here
get_number_of_jobs_L("Washington DC")

('Washington DC', 5316)

#your code goes here
location = ["Los Angeles","New York","San Francisco","Washington DC","Seattle","Austin","Detroit"]

# your code goes here
from openpyxl import Workbook        # import Workbook class from module openpyxl

# your code goes here
wb=Workbook()                        # create a workbook object

ws=wb.active                         # use the active worksheet
ws.append(['City','Number of Jobs'])   # add a row with two columns 'City' and 'Number of Jobs'

#your code goes here
for i in range(len(location)):
    n = get_number_of_jobs_L(location[i])
    ws.append(n)     # add a row with two columns 'location' and 'get_number_of_jobs_L(location)' value

#your code goes here
wb.save("job-postings-location.xlsx")            # save the workbook into a file called countries.xlsx
print("Successfully Saved")

Successfully Saved

# your code goes here
wb=Workbook()                        # create a workbook object
ws=wb.active                         # use the active worksheet
technology = ["C","C#","C++","Java","JavaScript","Python","Scala","Oracle","SQL Server","MySQL Server","PostgreSQL","MongoDB"]
ws.append(['Technology','Number of Jobs'])   # add a row with two columns 'Technology' and 'Number of Jobs'
#your code goes here
for i in range(len(technology)):
    n = get_number_of_jobs_T(technology[i])
    ws.append(n)     # add a row with two columns 'technology' and 'get_number_of_jobs_L(technology)' value
wb.save("job-postings-technology.xlsx")            # save the workbook into a file called job-postings-technology.xlsx
print("Successfully Saved")

Successfully Saved

import pandas as pd
import seaborn as sns
import numpy as np

# use the inline backend to generate the plots within the browser
%matplotlib inline 

import matplotlib as mpl
import matplotlib.pyplot as plt

mpl.style.use('ggplot') # optional: for ggplot-like style

# check for latest version of Matplotlib
# print ('Matplotlib version: ', mpl.__version__) # >= 2.0.0

df = pd.read_excel("job-postings-location.xlsx")


df = df.set_index("City")
# df["count"]=df["count"].astype('int')
df = df.sort_values("Number of Jobs",axis = 0, ascending = True)

fig, ax = plt.subplots(figsize=(12,6))
# df.rename(columns={'count':'Total People Opinion'}, inplace=True)

df.plot(kind='barh', legend = False, ax=ax, color='dodgerblue')
ax.set_xlabel('Number of Jobs',color='black',fontfamily="Montserrat",fontsize=14)
ax.set_ylabel('City',color='black',fontfamily="Montserrat",fontsize=14)
ax.set_title('Number of Jobs in US',color='black',fontfamily="Montserrat",fontsize=20,loc='left')
ax.set_facecolor('whitesmoke')
ax.tick_params(axis='x', colors='black')    #setting up X-axis tick color to black
ax.tick_params(axis='y', colors='black')    #setting up Y-axis tick color to black
plt.rcParams["font.family"] = "Montserrat"
plt.grid(visible=None)


# annotate value labels to each country
for i in range(len(df)): #enamurate returns tuple
    # print(df["Total People Opinion"][i])
    value = df["Number of Jobs"][i]
    label = format(int(value), ',') # format int with commas

# place text at the end of bar (subtracting 700 from x, and 0.1 from y to make it fit within the bar)
    plt.annotate(label, xy=(value-300, i-0.1), color='snow')
plt.savefig("us_jobs.png")
plt.show()

import pandas as pd
import seaborn as sns
import numpy as np

# use the inline backend to generate the plots within the browser
%matplotlib inline 

import matplotlib as mpl
import matplotlib.pyplot as plt

mpl.style.use('ggplot') # optional: for ggplot-like style

# check for latest version of Matplotlib
# print ('Matplotlib version: ', mpl.__version__) # >= 2.0.0

df = pd.read_csv("popular-languages.csv")


df = df.set_index("Language")
df = df.sort_values("Average Annual Salary",axis = 0, ascending = True)

# df["count"]=df["count"].astype('int')


fig, ax = plt.subplots(figsize=(12,6))

df.plot(kind='barh', legend = False, ax=ax, color='mediumturquoise')
ax.set_xlabel('Average Annual Salary',color='black',fontfamily="Montserrat",fontsize=14)
ax.set_ylabel('Language',color='black',fontfamily="Montserrat",fontsize=14)
ax.set_title('Average Annual Salary in US',color='black',fontfamily="Montserrat",fontsize=20,loc='left')
ax.set_facecolor('whitesmoke')

ax.tick_params(axis='x', colors='black')    #setting up X-axis tick color to black
ax.tick_params(axis='y', colors='black')    #setting up Y-axis tick color to black

plt.rcParams["font.family"] = "Montserrat"
plt.grid(visible=None)


# annotate value labels to each country
for i in range(len(df)): #enamurate returns tuple
    # print(df["Total People Opinion"][i])
    value = df["Average Annual Salary"][i]
    label = format(int(value), ',') # format int with commas

# place text at the end of bar (subtracting 700 from x, and 0.1 from y to make it fit within the bar)
    plt.annotate("$"+label, xy=(value-10000, i-0.1), color='black')
plt.savefig("annual_salary.png")
plt.show()

Collecting Job Data Using APIs (Personal Project)¶

Collecting Job Data Using APIs¶

Objectives¶

Instructions¶

Dataset Used in this Assignment¶

Warm-Up Exercise¶

Lab: Collect Jobs Data using Jobs API¶

Objective: Determine the number of jobs currently open for various technologies and for various locations¶

Write a function to get the number of jobs for the Python technology.

The keys in the json are¶

Write a function to find number of jobs in US for a location of your choice¶

Store the results in an excel file¶

In the similar way, you can try for below given technologies and results can be stored in an excel sheet.¶