high paying low stress jobs

for time pass I parsed a slideshow from time.com about an article on high paying low stress job. some seaborn plots to describe the data - 'Stress tolerance is measured by the Bureau of Labor Statistics and Occupational Information Network, with lower scores indicating less stress on the job.' I need to check their website...

high paying low stress jobs¶

• taken from an article from time.com

In [1]:

import requests
import bs4

In [2]:

from string import punctuation
exclude = set(punctuation)

In [3]:

import pandas as pd
import seaborn as sns
import matplotlib.pyplot as plt
%matplotlib inline
sns.set()

In [4]:

url="http://time.com/4081673/high-paying-low-stress-jobs/"

In [5]:

rs = requests.get(url)

In [6]:

rs.status_code

Out[6]:

200

In [7]:

#rs.content

In [8]:

# with open('high_paying_low_stress_jobs.html', 'wb') as fd:
#     for chunk in rs.iter_content():
#         fd.write(chunk)
    

In [9]:

# Make a soup obj
soup = bs4.BeautifulSoup(rs.text,'lxml')

In [10]:

h2 = soup.find_all('h2', {'class':'article-item-title'})
p1 =soup.find_all('p', {'class':'p1'})
p2 = soup.find_all('p', {'class':'p2'})
p4 = soup.find_all('p', {'class':'p4'})

In [11]:

# information
soup.find_all('p',{'class':'p3'})[0].get_text()

Out[11]:

'Stress tolerance is measured by the Bureau of Labor Statistics and Occupational Information Network, with lower scores indicating less stress on the job.'

In [12]:

bd = soup.find_all('section', {'class':'article-item-body'})

There are 24 Jobs listed on times¶

• Jobs
• Stress Tolerance
• Average Salary
• Remarks are parsed into differnt list and then to a pandas data frame

In [13]:

jobs=[]
for i in h2:
    jobs.append( i.get_text())

In [14]:

stress = []
aas = []
remarks =[]
for e,i in enumerate(bd):
    ii = i.get_text() 
    for i in ii.split('\n'):
        if i.startswith("Stress tolerance:"):
            st = float( i.split(": ")[1] )
            stress.append(st)
        elif i.startswith("Average"):
            aa = i.split(": ")[1]
            aa = int( ''.join(ch for ch in aa if ch not in exclude) )
            aas.append(aa)
        elif i.startswith("What"):
            rem = i.split(": ")[1]
            remarks.append(rem)
        else:pass

In [15]:

df = pd.DataFrame(data={'J':jobs, 'ST':stress, 'Sal':aas, 'Remarks':remarks})

In [16]:

df.head()

Out[16]:

	J	Remarks	ST	Sal
0	Materials Scientists	Research and study substances at the atomic an...	53.0	94350
1	Mathematicians	Conduct research in fundamental mathematics or...	57.2	104350
2	Geographers	Study the nature and use of areas of Earth’s s...	58.0	75610
3	Economists	Economists study the production and distributi...	58.7	105290
4	Statisticians	Use statistical methods to collect and analyze...	59.0	84010

In [17]:

df.describe()

Out[17]:

	ST	Sal
count	24.000000	24.000000
mean	62.683333	104860.416667
std	4.117795	25309.101212
min	53.000000	75440.000000
25%	60.800000	91607.500000
50%	62.250000	103060.000000
75%	65.125000	110230.000000
max	70.300000	201030.000000

In [18]:

# making a new dataframe
df2 =  df[['J','ST','Sal']]
df2.set_index(df2.J, inplace=True,drop=True)
del df2['J']

In [19]:

df2.head()

Out[19]:

	ST	Sal
J
Materials Scientists	53.0	94350
Mathematicians	57.2	104350
Geographers	58.0	75610
Economists	58.7	105290
Statisticians	59.0	84010

In [20]:

g = sns.jointplot("ST","Sal", data=df2, kind="reg", color="r", size=6)

/home/rosaak/.virtualenvs/p3/lib/python3.5/site-packages/statsmodels/nonparametric/kdetools.py:20: VisibleDeprecationWarning: using a non-integer number instead of an integer will result in an error in the future
  y = X[:m/2+1] + np.r_[0,X[m/2+1:],0]*1j

In [21]:

ax = sns.regplot('Sal','ST',data=df2)

In [22]:

df2 = df2.sort_values(by = 'Sal')
ax = sns.barplot(x=df2.Sal, y=df2.index, data=df2 )

In [23]:

df2 = df2.sort_values(by ='ST')
ax = sns.barplot(x=df2.ST, y=df2.index, data=df2 )

In [24]:

# getting the data frame where Stress Tolerence is > 65
df3 = df[df.ST >65].sort_values('Sal')
    

In [25]:

df3

Out[25]:

	J	Remarks	ST	Sal
18	Hydrologists	Study how water moves across and through Earth...	65.5	81930
21	Art Directors	Art directors are responsible for the visual s...	69.0	97850
22	Marine Engineers and Naval Architects	Design, build, and maintain ships, including a...	69.6	99160
20	Computer Hardware Engineers	Research, design, develop, or test computer or...	67.0	110650
23	Optometrists	Optometrists perform eye exams to check for vi...	70.3	113010
19	Orthodontists	Examine, diagnose, and treat dental misalignme...	67.0	201030

In [26]:

for e,i in enumerate( df3.index, start=1):
    print(e, df3.loc[i][0],":\t",df3.loc[i][1], end='\n\n')

1 Hydrologists :  Study how water moves across and through Earth’s crust. They can use their expertise to solve problems in the areas of water quality or availability.

2 Art Directors :  Art directors are responsible for the visual style and images in magazines, newspapers, product packaging, and movie and television productions.

3 Marine Engineers and Naval Architects :  Design, build, and maintain ships, including aircraft carriers, submarines, sailboats, and tankers. Marine engineers work on the mechanical systems, such as propulsion and steering. Naval architects work on the basic design, including the form and stability of hulls.

4 Computer Hardware Engineers :  Research, design, develop, or test computer or computer-related equipment for commercial, industrial, military, or scientific use.

5 Optometrists :  Optometrists perform eye exams to check for vision problems and diseases. They prescribe eyeglasses or contact lenses as needed.

6 Orthodontists :  Examine, diagnose, and treat dental misalignments and oral cavity anomalies, design appliances to realign teeth and jaws.