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What are the “must have” jQuery plugins? [closed]
...SalvadóChristian C. Salvadó
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How do I get a list o<em>fem> column names <em>fem>rom a psycopg2 cursor?
...SetjmpSetjmp
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65
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Pandas percentage o<em>fem> total with groupby
...u can calculate the percentage in a simpler way -- just groupby the state_o<em>fem><em>fem>ice and divide the sales column by its sum. Copying the beginning o<em>fem> Paul H's answer:
# <em>Fem>rom Paul H
import numpy as np
import pandas as pd
np.random.seed(0)
d<em>fem> = pd.Data<em>Fem>rame({'state': ['CA', 'WA', 'CO', 'AZ'] * 3,
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SQL error “ORA-01722: invalid number”
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gmlacrossegmlacrosse
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6
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When/Why to use Cascading in SQL Server?
When setting up <em>fem>oreign keys in SQL Server, under what circumstances should you have it cascade on delete or update, and what is the reasoning behind it?
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The ALTER TABLE statement con<em>fem>licted with the <em>Fem>OREIGN KEY constraint
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PatsonLeanerPatsonLeaner
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How to change Rails 3 server de<em>fem>ault port in develoment?
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SpencerSpencer
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How do you remove duplicates <em>fem>rom a list whilst preserving order?
Is there a built-in that removes duplicates <em>fem>rom list in Python, whilst preserving order? I know that I can use a set to remove duplicates, but that destroys the original order. I also know that I can roll my own like this:
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Sorting arrays in NumPy by column
...<em>fem>8,<em>fem>8,<em>fem>8,<em>fem>8,<em>fem>8,<em>fem>8,<em>fem>8').sort(order=['<em>fem>9'], axis=0)
1000 loops, best o<em>fem> 3: 1.88 ms per loop
%timeit table[table[:,9].argsort()]
10000 loops, best o<em>fem> 3: 180 µs per loop
import pandas as pd
d<em>fem> = pd.Data<em>Fem>rame(table)
%timeit d<em>fem>.sort_values(9, ascending=True)
1000 loops, best o<em>fem> 3: 400 µs per loop
So...
API to automatically upload apk to Google Play? [closed]
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bksavillebksaville
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