Adding text to PDF using matplotlib

Question

I need to add a pandas dataframe to a pdf and also should write some info about it in the pdf. I have successfully completed in writing a pandas dataframe to a pdf .

Below is my code:

fig,ax=plt.subplots(figsize=(20,10))
ax.axis('tight')
ax.axis('off')
the_table=ax.table(cellText=df.values,colLabels=df.columns,loc='center')

pp=PdfPages("foo.pdf")
pp.savefig(fig,bboc_inches='tight')
pp.close()

The output PDF has a dataframe printed on it.

What should I do to add some more informations on it which is not a dataframe ?(Eg:I want to add Headings,Informations on it which are sentences)

I want to convert to pdf using matplotlib/Fpdf. Using Fpdf I can add sentences but not a table . So I used matplotlib.

Please give me an idea on how to do that. Thanks a lot!

Yeah but whatever co-ordinate I give to it, I am not able to view — keerthi007
– keerthi007, Commented Jul 13, 2020 at 5:47
the paramters x and y are the actual x-axis and y-axis values. So if you give a value that does not exist in the view of your graph, then the text is moved out of view. To clarify, if your graph contains xlim from [0, 10], you need the parameter x to be within this limit — learner
– learner, Commented Jul 13, 2020 at 5:48
Let me know if this worked so that I can put it down as an answer — learner
– learner, Commented Jul 13, 2020 at 6:03

learner · Accepted Answer · 2020-07-13 06:45:04Z

You can place any text using plt.text where the parameters x and y are the actual coordinates in the graph. To place a text correctly, first turn on the axes and then place the text(s), finally turn the axes off using plt.axis('off'). I have attached a sample code below.

import numpy as np
import matplotlib.pyplot as plt

plt.axis('off')

data = [[ 66386, 174296,  75131, 577908,  32015],
        [ 58230, 381139,  78045,  99308, 160454],
        [ 89135,  80552, 152558, 497981, 603535],
        [ 78415,  81858, 150656, 193263,  69638],
        [139361, 331509, 343164, 781380,  52269]]

columns = ('Freeze', 'Wind', 'Flood', 'Quake', 'Hail')
rows = ['%d year' % x for x in (100, 50, 20, 10, 5)]

values = np.arange(0, 2500, 500)
value_increment = 1000

n_rows = len(data)

index = np.arange(len(columns)) + 0.3
bar_width = 0.4

y_offset = np.zeros(len(columns))

cell_text = []
for row in range(n_rows):
    y_offset = y_offset + data[row]
    cell_text.append(['%1.1f' % (x / 1000.0) for x in y_offset])

plt.text(x=0.5, y=0.8, s="Text 1 here")
plt.text(x=0.2, y=0.9, s="Text 2 here")
# Add a table at the bottom of the axes
the_table = plt.table(cellText=cell_text,
                      rowLabels=rows,
                      colLabels=columns,
                      loc='center')


plt.show()

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