Reputation: 217
I have some code that reads a table in a Word document and makes a dataframe from it.
import numpy as np
import pandas as pd
from docx import Document
#### Time for some old fashioned user functions ####
def make_dataframe(f_name, table_loc):
document = Document(f_name)
tables = document.tables[table_loc]
for i, row in enumerate(tables.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)
df = pd.DataFrame.from_dict(data)
return df
SHRD_filename = "SHRD - 12485.docx"
SHDD_filename = "SHDD - 12485.docx"
df_SHRD = make_dataframe(SHRD_filename,30)
df_SHDD = make_dataframe(SHDD_filename,-60)
Because the files are different (for instance the SHRD has 32 tables and the one I am looking for is the second to last, but the SHDD file has 280 tables, and the one I am looking for is 60th from the end. But that may not always be the case.
How do I search through the tables in a document and start working on the one that cell[0,0] = 'Tag Numbers'
.
Upvotes: 2
Views: 3162
Reputation: 36598
You can iterate through the tables and check the text in the first cell. I have modified the output to return a list of dataframes, just in case more than one table is found. It will return an empty list if no table meets the criteria.
def make_dataframe(f_name, first_cell_string='tag number'):
document = Document(f_name)
# create a list of all of the table object with text of the
# first cell equal to `first_cell_string`
tables = [t for t in document.tables
if t.cell(0,0).text.lower().strip()==first_cell_string]
# in the case that more than one table is found
out = []
for table in tables:
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)
out.append(pd.DataFrame.from_dict(data))
return out
Upvotes: 4