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SVN checkout ignore folder
...rsion/project/trunk my_checkout --depth immediates
This will check files and directories from your project trunk into 'my_checkout', but not recurse into those directories. Eg:
$ cd my_checkout && ls
bar/ baz foo xyzzy/
Then to get the contents of 'bar' down:
$ cd bar && svn u...
How can I disable a button in a jQuery dialog from a function?
... collection from the dialog, loop through that to find which one you need, and then set the disabled attribute as I showed above.
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iOS5 Storyboard error: Storyboards are unavailable on iOS 4.3 and prior
I've built a small app using storyboards and it ran great. Just before final testing I decided to try it out to see if it runs on iOS 4.3. I clicked on the gray 5.0 in the project settings and selected 4.3.
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Changing navigation bar color in Swift
...r?.tabBar.tintColor = UIColor.yellow
On the last two, replace brownColor and yellowColor with the color of your choice.
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How to select unique records by SQL
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With the distinct keyword with single and multiple column names, you get distinct records:
SELECT DISTINCT column 1, column 2, ...
FROM table_name;
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mysql error 1364 Field doesn't have a default values
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Set a default value for Created_By (eg: empty VARCHAR) and the trigger will update the value anyways.
create table try (
name varchar(8),
CREATED_BY varchar(40) DEFAULT '' not null
);
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Python json.loads shows ValueError: Extra data
I am getting some data from a JSON file "new.json", and I want to filter some data and store it into a new JSON file. Here is my code:
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Return multiple columns from pandas apply()
I have a pandas DataFrame, df_test . It contains a column 'size' which represents size in bytes. I've calculated KB, MB, and GB using the following code:
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Determine the data types of a data frame's columns
I'm using R and have loaded data into a dataframe using read.csv() . How do I determine the data type of each column in the data frame?
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Pandas: drop a level from a multi-level column index?
... If the index you are trying to drop is on the left (row) side and not the top (column) side, you can change "columns" to "index" and use the same method: >>> df.index = df.index.droplevel(1)
– Idodo
Nov 28 '18 at 12:13
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