I have a txt file which looks like below including 4 rows as an example and each row strings are separated by a ,
.
"India1,India2,myIndia "
"Where,Here,Here "
"Here,Where,India,uyete"
"AFD,TTT"
https://gist.github.com/anonymous/cee79db7029a7d4e46cc4a7e92c59c50
the file can be downloaded from here
I want to extract all unique cells across all , the output2
India1
India2
myIndia
Where
Here
India
uyete
AFD
TTT
I tried to read line by line and print it ìf i call my data as df`
myfile = open("df.txt")
lines = myfile.readlines()
for line in lines:
print lines
Option 1: .csv
, .txt
Files
Native Python is unable to read .xls
files. If you convert your file(s) to .csv
or .txt
, you can use the csv
module within the Standard Library:
# `csv` module, Standard Library
import csv
filepath = "./test.csv"
with open(filepath, "r") as f:
reader = csv.reader(f, delimiter=',')
header = next(reader) # skip 'A', 'B'
items = set()
for line in reader:
line = [word.replace(" ", "") for word in line if word]
line = filter(str.strip, line)
items.update(line)
print(list(items))
# ['uyete', 'NHYG', 'QHD', 'SGDH', 'AFD', 'DNGS', 'lkd', 'TTT']
Option 2: .xls
, .xlsx
Files
If you want to retain the original .xls
format, you have to install a third-party module to handle Excel files.
Install xlrd
from the command prompt:
pip install xlrd
In Python:
# `xlrd` module, third-party
import itertools
import xlrd
filepath = "./test.xls"
with xlrd.open_workbook(filepath) as workbook:
worksheet = workbook.sheet_by_index(0) # assumes first sheet
rows = (worksheet.row_values(i) for i in range(1, worksheet.nrows))
cells = itertools.chain.from_iterable(rows)
items = list({val.replace(" ", "") for val in cells if val})
print(list(items))
# ['uyete', 'NHYG', 'QHD', 'SGDH', 'AFD', 'DNGS', 'lkd', 'TTT']
Option 3: DataFrames
You can handle csv and text files with pandas DataFrames. See documentation for other formats.
import pandas as pd
import numpy as np
# Using data from gist.github.com/anonymous/a822647a00087abc12de3053c700b9a8
filepath = "./test2.txt"
# Determines columns from the first line, so add commas in text file, else may throw an error
df = pd.read_csv(filepath, sep=",", header=None, error_bad_lines=False)
df = df.replace(r"[^A-Za-z0-9]+", np.nan, regex=True) # remove special chars
stack = df.stack()
clean_df = pd.Series(stack.unique())
clean_df
DataFrame Output
0 India1
1 India2
2 myIndia
3 Where
4 Here
5 India
6 uyete
7 AFD
8 TTT
dtype: object
Save as Files
# Save as .txt or .csv without index, optional
# target = "./output.csv"
target = "./output.txt"
clean_df.to_csv(target, index=False)
Note: Results from options 1 & 2 can be converted to unordered, pandas columnar objects too with pd.Series(list(items))
.
Finally: As a Script
Save any of the three options above in a function (stack
) within a file (named restack.py
). Save this script to a directory.
# restack.py
import pandas as pd
import numpy as np
def stack(filepath, save=False, target="./output.txt"):
# Using data from gist.github.com/anonymous/a822647a00087abc12de3053c700b9a8
# Determines columns from the first line, so add commas in text file, else may throw an error
df = pd.read_csv(filepath, sep=",", header=None, error_bad_lines=False)
df = df.replace(r"[^A-Za-z0-9]+", np.nan, regex=True) # remove special chars
stack = df.stack()
clean_df = pd.Series(stack.unique())
if save:
clean_df.to_csv(target, index=False)
print("Your results have been saved to '{}'".format(target))
return clean_df
if __name__ == "__main__":
# Set up input prompts
msg1 = "Enter path to input file e.g. ./test.txt: "
msg2 = "Save results to a file? y/[n]: "
try:
# Python 2
fp = raw_input(msg1)
result = raw_input(msg2)
except NameError:
# Python 3
fp = input(msg1)
result = input(msg2)
if result.startswith("y"):
save = True
else:
save = False
print(stack(fp, save=save))
From its working directory, run the script via commandline. Answer the prompts:
> python restack.py
Enter path to input file e.g. ./test.txt: ./@data/test2.txt
Save results to a file? y/[n]: y
Your results have been saved to './output.txt'
Your results should print in you console and optionally save to a file output.txt
. Adjust any parameters to suit your interests.