Donas Y Churros N 11 Caprichos Y Antojos 🎆



 
 
 
 
 
 
 

Donas Y Churros N 11 Caprichos Y Antojos

Donas Y Churros N 11 Caprichos Y Antojos
Donas Y Churros N 11 Caprichos Y Antojos
Donas Y Churros N 11 Caprichos Y Antojos
Donas Y Churros N 11 Caprichos Y Antojos
Donas Y Churros N 11 Caprichos Y Antojos
Donas Y Churros N 11 Caprichos Y Antojos
Donas Y Churros N 11 Caprichos Y Antojos
Donas Y Churros N 11 Caprichos Y Antojos
Donas Y Churros N 11 Caprichos Y Antojos
Donas Y Churros N 11 Caprichos Y Antojos
Donas Y Churros N 11 Caprichos Y Antojos
Donas Y Churros N 11 Caprichos Y Antojos
Donas Y Churros N 11 Caprichos Y Antojos
Donas Y Churros N 11 Caprichos Y Antojos
Donas Y Churros N 11 Caprichos Y Antojos
Donas Y Churros N 11 Caprichos Y Antojos
Donas Y Churros N 11 Caprichos Y Antojos
Donas Y Churros N 11 Caprichos Y Antojos
Donas Y Churros N 11 Caprichos Y Antojos
Donas Y Churros N 11 Caprichos Y Antojos
Donas Y Churros N 11 Caprichos Y Antojos
Donas Y Churros N 11 Caprichos Y Antojos
Donas Y Churros N 11 Caprichos Y Antojos
Donas Y Churros N 11 Caprichos Y Antojos
Donas Y Churros N 11 Caprichos Y Antojos
Donas Y Churros N 11 Caprichos Y Antojos
Donas Y Churros N 11 Caprichos Y Antojos
Donas Y Churros N 11 Caprichos Y Antojos
Donas Y Churros N 11 Caprichos Y Antojos
Donas Y Churros N 11 Caprichos Y Antojos
Donas Y Churros N 11 Caprichos Y Antojos
Donas Y Churros N 11 Caprichos Y Antojos

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A:

import re
import pandas as pd

df = pd.DataFrame(data=open(r’/home/user/correo/2016/files/fiches.csv’).readlines(), columns=[‘txt’])

texto = df.txt.str.extract(‘(?P.+) (?P.*?\\.[^.]*?) (?P[^.]*?) (?P.+?)’, flags=re.I).dropna()

df = df.drop([‘txt’], 1)

data = [ re.sub(r’\s\s*\w{5}\s\s*’, r’ ‘, i.encode(‘utf8’).decode(‘utf8’).lower())
for i in texto.tolist()]

df = pd.DataFrame(data=data, columns=[‘txt’])

for var in df.txt.unique():
print(var.str.encode(‘utf8’).decode(‘utf8′).lower())

EDIT:
yields
brazilian soccer results
11 jan. 12 shows. 13 html. 14 zodiacfacts. 15 sagittarius. 16 enormous. 17 confidence. 18 meeeeeee. 19 80. 20 000. 21 chef. 22 salad. 23 calling. 24 hungry.
I updated the code
import re
import pandas as pd

df = pd.DataFrame(data=open(r’/home/user/correo/2016/files/fiches.csv’).readlines(), columns=[‘txt’])

texto = df.txt.str.extract(‘(?P.+) (?P.*?\\.[^.]*?) (?P[^.]*?) (?P.+?)’, flags=re.I).dropna()

df = df.drop([‘txt’], 1)

data = [ re.sub(r’\s\s*\w{5}\s\s*’, r’ ‘, i.encode(‘utf8’).decode(‘utf8’).lower())
0cc13bf012

.html.gif.jpg.png.swf.tif.zip Donas y Churros N 11 Caprichos y Antojos – Caprichos y Antojos Especial 14 Magazine – Canal de noticias e internet.
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File Info.. is very simple and easy to use.

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A:

I’m not sure about why it’s happening, but try the following:
Private Sub btn_Load_Click(ByVal sender As System.Object, ByVal e As System.EventArgs) Handles btn_Load.Click

txt_Donas.Multiline = False
txt_Donas.BorderStyle = BorderStyle.FixedSingle

End Sub

This will make the textbox only edit when the user clicks inside it, and not when the dialog is loaded.
The border style has nothing to do with the multiline property.
EDIT
The issue is that you should not be using a multiline textbox in a dialog form. If you click inside the textbox, it will look for a new line, which is already inside the dialog, thus the text enters the textbox. Try using a single line textbox instead.
If you do not want to do this, you can try to use the following code to make it ignore the Enter key:
Private Sub txt_Donas_KeyDown(ByVal sender As Object, ByVal e As KeyEventArgs) Handles txt_Donas.KeyDown

If e.KeyCode = Keys.Enter Then
e.Handled = True
End If

End Sub

On the “What’s your name” TextBox:
Protected Sub txt_Donas_TextChanged(ByVal sender As Object, ByVal e As System.EventArgs) Handles txt_Donas.TextChanged

If e.NewText.Length > 0 Then
e.Handled = True
End If

End Sub

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Friday, May 19, 2009

The Rite of Replacement: The Ordinary Form of the Mass

What’s