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Agsoft Personel Bordro Takip Program serial numbers, cracks and keygens are. Pc Utilityvso-program multilanguage serial number maker.Q:
Native Android contacts
I’m developing an android app and need a little help. I need to get the contacts from Android’s native Contacts app.
After this, I need to list all of the fields of these contacts, like mname, mnumber etc.
So far I found the ContactsContract and tried some examples. I did a lot of searching on the internet, but couldn’t find anything useful.
Does anyone know how to do this, or at least point me in the right direction?
A:
You can read the following :
It’s very easy to do. I have been using it for a while in my application.
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…read moreQ:
Converting DataFrame to a JavaScript Array
I have a DataFrame with some data that I would like to convert into an array in Javascript.
from:
+—-+——+
|sid | vid |
+—-+——+
| 1 | abc |
| 2 | def |
+—-+——+
to:
[
[‘1’, ‘abc’],
[‘2’, ‘def’]
]
is there a way to do this in pandas?
A:
IIUC, you could use Python’s json module. The easiest way to install it would be pip install ( so then you could use it like so:
import json
import pandas as pd
df = pd.DataFrame({“vid”:[“abc”,”def”],”sid”:[1,2]})
arr = json.loads(df.to_json(orient=’records’))
You could also convert directly from a DataFrame to a dictionary:
df.to_dict(orient=’records’)
This converts to a dictionary with the data frame’s data as the keys and the row names as values. For example, print(df.to_dict(orient=’records’)):
{‘sid’: [1], ‘vid’: [‘abc’, ‘def’]}
‘s conjecture) we have a characterization of classical homology groups of a finite topological space by the classical homology of its Grothendieck group. This statement of the result by Grothendieck is the “dual reformulation” of that by Serre.
[^5]: In order to simplify the discussion, we slightly modify the definition. Usually, Hochschild homology is
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