I know this is a repeated question but the other answers did not work for me. I have a word file that consists of one table. I want that table as an output of my python program. I'm using python 3.6 and I have installed python -docx as well. Here is my code for the data extraction
from docx.api import Document
document = Document('test_word.docx')
table = document.tables[0]
data = []
keys = None
for i, row in enumerate(table.rows):
text = (cell.text for cell in row.cells)
if i == 0:
keys = tuple(text)
continue
row_data = dict(zip(keys, text))
data.append(row_data)
print (data)
I want the result that exactly looks like the word docx file. Thanks in advance
Your code works fine for me. How about inserting it into a dataframe?
import pandas as pd
from docx.api import Document
document = Document('test_word.docx')
table = document.tables[0]
data = []
keys = None
for i, row in enumerate(table.rows):
text = (cell.text for cell in row.cells)
if i == 0:
keys = tuple(text)
continue
row_data = dict(zip(keys, text))
data.append(row_data)
print (data)
df = pd.DataFrame(data)
How can i display particular row and column in that table? We can extract rows and cols based on index with iloc
# iloc[row,columns]
df.iloc[0,:].tolist() # [5,6,7,8] - row index 0
df.iloc[:,0].tolist() # [5,9,13,17] - column index 0
df.iloc[0,0] # 5 - cell(0,0)
df.iloc[1:,2].tolist() # [11,15,19] - column index 2, but skip first row
and so on...
However, if your columns have names (in this case it is numbers) you can do it like this:
#df["name"].tolist()
df[1].tolist() # [5,6,7,8] - column with name 1
print(df)
prints, which is how the table looks like in my sample doc.
1 2 3 4
0 5 6 7 8
1 9 10 11 12
2 13 14 15 16
3 17 18 19 20
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