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INITFOCUS on DIALOG as WS_VISIBLE

You can do the same for OK. Then, depending on what you want to happen, you need to test the value for ESCAPE on DIALOG or on OK.

On a side note, it's not very good practice to put a NOP on a subroutine that's expected to be executed on errors. Instead, try to write it like this:
Procedure LaunchPad()
If DialogProc is Nothing Then
MsgBox "It was not possible to load " + path + "!"
Exit Sub
End If

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I'm trying to set up a dev environment for our site. It's a super simple site built using Angular 1.5, Angular Material and we're using Webpack 2.
It's hosted at heroku so I have a free site that will just work (like it already does, but for port 80).
I'm looking to host a second dev environment on a VPS (for a remote team), but I'm unsure if I want it to be hosted on the same VPS or a separate VPS.

Ideally, the dev environment would be the same as the heroku one (meaning, local to local), but my dev VPS is on a separate network that has no inbound connectivity to our servers.
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Python Pandas: Append CSV to an existing DataFrame

I have a list of csv files that I would like to append data from the newly added file to an existing DataFrame so that if the new file is missing, the original data will be updated. I'm not having any luck in accomplishing this.
Let's say I have an already existent dataframe and I want to append data from my newly created csv file. I thought it would be as simple as:
import pandas as pd
import os.path as sp
from pathlib import Path
file_path = Path('my_file.csv')
new_file = Path('new_file.csv')

# Dataframe that I want to append data from my newly created file (new_file) to
df = pd.DataFrame({'col1':[1,2,3],
'col2':[4,5,6],
'col3':[7,8,9]})

# Directory with my original data set (data_dir).
df = df.append(pd.read_csv(new_file).dropna(), ignore_index=True)

Instead of appending the new csv file, it is appending the new file (new_file) to itself.
Any help is greatly appreciated!

A:

If you have the option of importing the data to the dataframe before you create the new csv file you could do the following:
df = pd.DataFrame(data=pd.read_csv('new_file.csv'), index=pd.Index(['col1', 'col2'], name='index'))

A:

While the accepted answer is correct, it is possible to leave the data out of the pandas data structure entirely, and pass it directly to the function doing the.append of the data, if this is also your desired outcome.
df.append('new_file.csv', ignore_index=True)

Note: