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What are the advantages of using nullptr?

... handle nullptr argument!!! 1. In C++, NULL is defined as #define NULL 0, so it is basically int, that is why f(int) is called. share | improve this answer | follow ...
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How to connect to Mysql Server inside VirtualBox Vagrant?

... can I connect to that server outside the vm? I already forward the port 3306 of the Vagrantfile , but when I try to connect to the mysql server, it`s resposts with the error: 'reading initial communication packet' ...
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How to split a delimited string into an array in awk?

... Have you tried: echo "12|23|11" | awk '{split($0,a,"|"); print a[3],a[2],a[1]}' share | improve this answer | follow | ...
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How to convert an integer to a string in any base?

...tring.digits + string.ascii_letters def int2base(x, base): if x < 0: sign = -1 elif x == 0: return digs[0] else: sign = 1 x *= sign digits = [] while x: digits.append(digs[int(x % base)]) x = int(x / base) if sign < 0: ...
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Flatten nested dictionaries, compressing keys

...t(items) >>> flatten({'a': 1, 'c': {'a': 2, 'b': {'x': 5, 'y' : 10}}, 'd': [1, 2, 3]}) {'a': 1, 'c_a': 2, 'c_b_x': 5, 'd': [1, 2, 3], 'c_b_y': 10} share | improve this answer | ...
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Common MySQL fields and their appropriate data types

... answered Dec 10 '08 at 0:57 da5idda5id 8,83288 gold badges3636 silver badges5050 bronze badges ...
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How to crop an image using PIL?

I want to crop image in the way by removing first 30 rows and last 30 rows from the given image. I have searched but did not get the exact solution. Does somebody have some suggestions? ...
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Change one value based on another value in pandas

... for you. import pandas df = pandas.read_csv("test.csv") df.loc[df.ID == 103, 'FirstName'] = "Matt" df.loc[df.ID == 103, 'LastName'] = "Jones" As mentioned in the comments, you can also do the assignment to both columns in one shot: df.loc[df.ID == 103, ['FirstName', 'LastName']] = 'Matt', 'Jone...
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binning data in python with scipy/numpy

... easier to use numpy.digitize(): import numpy data = numpy.random.random(100) bins = numpy.linspace(0, 1, 10) digitized = numpy.digitize(data, bins) bin_means = [data[digitized == i].mean() for i in range(1, len(bins))] An alternative to this is to use numpy.histogram(): bin_means = (numpy.histo...
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PHP cURL vs file_get_contents

... answered Jun 16 '12 at 16:00 XeoncrossXeoncross 49k7070 gold badges234234 silver badges340340 bronze badges ...