I have a database generated by a survey to evaluate university professors. What I want is a python script that takes the information from that database, generates a graphing table for each user, creates graphs for each user, and then renders it in a template to export it to a pdf.
What does the database look like?
User Professor_evaluated Category Question Answer
_________________________________________________________________
Mike Professor Criss respect 1 3
Mike Professor Criss respect 2 4
Mike Professor Criss wisdom 3 5
Mike Professor Criss wisdom 4 3
Charles Professor Criss respect 1 3
Charles Professor Criss respect 2 4
Charles Professor Criss wisdom 3 5
Charles Professor Criss wisdom 4 3
Each teacher has several categories assigned to be evaluated (respect, wisdom, etc.) and in turn each category has associated questions. In other words, a category has several questions. Each row of the DB is the answer to a question from a student evaluating a teacher
What do I need?
I need to create a script for automatically generate pdf reports that summarizes this information through charts, for example a chart with the overall score of each teacher, another chart with the score of each teacher by category, another chart with the average of each student, etc..Finally, every teacher would have a report.I want a report like this
What is my question?
my question is about which python packages and modules I would need to do this task. And what would be the general process of doing so. I don't need the code, because I know the answer is very general, but the knowledge of how I could do it.
For example: you would first need to process the information with pandas, to create a table that summarizes the information you want to graph, then plot it, then create a template of your report with XYZ module and then export it to pdf with XYZ module.
There are a lot of options for creating a pdf in python. Some of these options are ReportLab, pydf2, pdfdocument and FPDF.
The FPDF library is fairly stragihtforward to use and is what I've used in this example. FPDF Documentation can be found here.
It's perhaps also good to think about what python modules you might want to use to create graphs and tables. In my example, I use matplotlib (link to docs) and I also use Pandas to create a dataframe using pandas.dataframe()
.
I've posted a rather lengthy but fully reproducible example below, using pandas, matplotlib and fpdf. The data are a subset of what the OP provided in the question. I loop through the dataframe in my example to create the table, but there are alternative and perhaps more efficient ways to do this.
import pandas as pd
import matplotlib
from pylab import title, figure, xlabel, ylabel, xticks, bar, legend, axis, savefig
from fpdf import FPDF
df = pd.DataFrame()
df['Question'] = ["Q1", "Q2", "Q3", "Q4"]
df['Charles'] = [3, 4, 5, 3]
df['Mike'] = [3, 3, 4, 4]
title("Professor Criss's Ratings by Users")
xlabel('Question Number')
ylabel('Score')
c = [2.0, 4.0, 6.0, 8.0]
m = [x - 0.5 for x in c]
xticks(c, df['Question'])
bar(m, df['Mike'], width=0.5, color="#91eb87", label="Mike")
bar(c, df['Charles'], width=0.5, color="#eb879c", label="Charles")
legend()
axis([0, 10, 0, 8])
savefig('barchart.png')
pdf = FPDF()
pdf.add_page()
pdf.set_xy(0, 0)
pdf.set_font('arial', 'B', 12)
pdf.cell(60)
pdf.cell(75, 10, "A Tabular and Graphical Report of Professor Criss's Ratings by Users Charles and Mike", 0, 2, 'C')
pdf.cell(90, 10, " ", 0, 2, 'C')
pdf.cell(-40)
pdf.cell(50, 10, 'Question', 1, 0, 'C')
pdf.cell(40, 10, 'Charles', 1, 0, 'C')
pdf.cell(40, 10, 'Mike', 1, 2, 'C')
pdf.cell(-90)
pdf.set_font('arial', '', 12)
for i in range(0, len(df)):
pdf.cell(50, 10, '%s' % (df['Question'].iloc[i]), 1, 0, 'C')
pdf.cell(40, 10, '%s' % (str(df.Mike.iloc[i])), 1, 0, 'C')
pdf.cell(40, 10, '%s' % (str(df.Charles.iloc[i])), 1, 2, 'C')
pdf.cell(-90)
pdf.cell(90, 10, " ", 0, 2, 'C')
pdf.cell(-30)
pdf.image('barchart.png', x = None, y = None, w = 0, h = 0, type = '', link = '')
pdf.output('test.pdf', 'F')
Expected test.pdf:
Update (April 2020): I made an edit to the original answer in April 2020 to replace use of pandas.DataFrame.ix()
since this is deprecated. In my example I was able to replace it's use with pandas.DataFrame.iloc
and the output is the same as before.