Creating a Curriculum Vitae with Jupyter, Pandas and Matplotlib

Applying for a data scientist job offer? Tired of writing the same old curriculum vitae?

Why not showing your data visualization skills directly in your application?

Generate Data

Instead of pressing your data about education, employment and skills in a word-like document, put it in tables instead.

E.g. use open office to create and edit csv-files

For this example I’ve created two files: skills.csv and jobs.csv

Work experience

import matplotlib.pyplot as plt
import pandas as pd 

jobs = pd.read_csv('./jobs.csv')
jobs

Index	Employer	Duration / Month
0	Landestheater Detmold	18
1	Harman Becker	48
2	mgm technology partners	19
3	self-employed	17
4	e.solutions	70

pie = jobs.plot.pie(y='Duration / Month', labels=None, autopct='%1.0f%%')
plt.title('Work experience', weight='bold', size=14)
plt.legend(labels=jobs['Employer'], title="Employers", 
           bbox_to_anchor=(1.2, 0.5), loc="center right", 
           fontsize=10, 
           bbox_transform=plt.gcf().transFigure)
plt.subplots_adjust(left=0.0, bottom=0.1, right=0.85)
plt.gca().axis("equal")
plt.show()
plt.clf()
plt.close()

Skill-Competency-Matrix

The idea of the skill-compentency-matrix is to show your competence in your skills in a two-dimensional plot: how long have you been practicing these skills and how confident are you in them.

skills = pd.read_csv('./skills.csv')
skills

	Skill	Type	Number of month practiced	Competency Level
0	Python	Programming Language	36	92
1	Java	Programming Language	25	74
2	C++	Programming Language	48	56
3	JavaScript	Programming Language	36	76
4	jQuery	Framework	32	81
5	HTML	Programming Language	40	95
6	CSS	Programming Language	24	63
7	KnockoutJS	Framework	6	50
8	SQL	Programming Language	43	78
9	Jira	Tool	60	88
10	Confluence	Tool	56	75
11	PyCharm	Tool	34	86
12	Eclipse	Tool	66	68
13	Visual Studio	Tool	50	45
14	Polarion QA	Tool	36	74
15	Selenium	Framework	32	83
16	jUnit	Framework	25	66
17	Flask	Framework	33	94
18	Vector CANoe	Tool	18	57
19	scikit-learn	Framework	5	15
20	Numpy	Framework	6	42
21	Pandas	Framework	6	25
22	matplotlib	Framework	6	20
23	openCV	Framework	2	10

groups = ["Programming Language", "Framework", "Tool"]
fig, ax = plt.subplots()
plt.style.use('ggplot')
fig.set_size_inches(10, 8)

for group in groups:
    skill = skills[skills.Type == group]
    ax.plot(skill['Number of month practiced'], 
    skill['Competency Level'], marker='o', linestyle='', ms=12, label=group)
    for i, txt in enumerate(skill.Skill):
        ax.annotate(txt, (skill['Number of month practiced'].iat[i],
        skill['Competency Level'].iat[i]), 
        xytext=(10,-5), 
        textcoords='offset points',)
ax.legend()
ax.set_xlim(0, 100)
plt.xlabel('Number of month practiced')
plt.ylabel('Competency Level')
plt.title("Skill Competency Matrix")
plt.show()

The plot shows a nice overview of my skills acquired over the years: