Na0s/sft-ready-neulab-conala · Datasets at Hugging Face

prompt stringlengths 4 181	completion stringlengths 2 232
list `lst` based on each element's number of occurrence	sorted(lst, key=lambda x: (-1 * c[x], lst.index(x)))
Get the value with the maximum length in each column in array `foo`	[max(len(str(x)) for x in line) for line in zip(*foo)]
get the count of each unique value in column `Country` of dataframe `df` and store in column `Sum of Accidents`	df.Country.value_counts().reset_index(name='Sum of Accidents')
alculat the difference between each row and the row previous to it in dataframe `data`	data.set_index('Date').diff()
ppend values `[3, 4]` to a set `a`	a.update([3, 4])
et every twostride far element to 1 starting from second element in array `a`	a[1::2] = -1
Get rank of rows from highest to lowest of dataframe `df`, grouped by value in column `group`, according to value in column `value`	df.groupby('group')['value'].rank(ascending=False)
vert js date object 'Tue, 22 Nov 2011 06:00:00 GMT' to python datetime	datetime.strptime('Tue, 22 Nov 2011 06:00:00 GMT', '%a, %d %b %Y %H:%M:%S %Z')
Convert a binary value '1633837924' to string	struct.pack('<I', 1633837924)
ppend string `foo` to list `list`	list.append('foo')
ert string `foo` at position `0` of list `list`	list.insert(0, 'foo')
vert keys in dictionary `thedict` into case insensitive	theset = set(k.lower() for k in thedict)
pad 'dog' up to a length of 5 characters with 'x'	"""{s:{c}^{n}}""".format(s='dog', n=5, c='x')
heck if type of variable `s` is a string	isinstance(s, str)
heck if type of a variable `s` is string	isinstance(s, str)
Convert list of dictionaries `L` into a flat dictionary	dict(pair for d in L for pair in list(d.items()))
erge a list of dictionaries in list `L` into a single dic	{k: v for d in L for k, v in list(d.items())}
a pandas data frame according to column `Peak` in ascending and `Weeks` in descending order	df.sort_values(['Peak', 'Weeks'], ascending=[True, False], inplace=True)
a pandas data frame by column `Peak` in ascending and `Weeks` in descending order	df.sort(['Peak', 'Weeks'], ascending=[True, False], inplace=True)
he code contained in string print('Hello')	eval("print('Hello')")
eating a list of dictionaries [{'A': 1, 'C': 4, 'B': 2, 'D': 4}, {'A': 1, 'C': 4, 'B': 1, 'D': 5}]	[{'A': 1, 'C': 4, 'B': 2, 'D': 4}, {'A': 1, 'C': 4, 'B': 1, 'D': 5}]
Creating a list of dictionaries in pytho	[{'A': 1, 'C': 4, 'B': 2, 'D': 4}, {'A': 1, 'C': 4, 'B': 1, 'D': 5}]
get all possible combination of items from 2dimensional list `a`	list(itertools.product(*a))
Get sum of values of columns 'Y1961', 'Y1962', 'Y1963' after group by on columns Country and Item_code in dataframe `df`.	df.groupby(['Country', 'Item_Code'])[['Y1961', 'Y1962', 'Y1963']].sum()
eate list `done` containing permutations of each element in list `[a, b, c, d]` with variable `x` as tuple	done = [(el, x) for el in [a, b, c, d]]
emove Nan values from array `x`	x = x[numpy.logical_not(numpy.isnan(x))]
emove first directory from path '/First/Second/Third/Fourth/Fifth'	os.path.join(*x.split(os.path.sep)[2:])
Replace `;` with `:` in a string `line`	line = line.replace(';', ':')
all bash command 'tar c my_dir \| md5sum' with pipe	subprocess.call('tar c my_dir \| md5sum', shell=True)
Convert a hex string `437c2123 ` according to ascii value.	"""437c2123""".decode('hex')
Get a list of all fields in class `User` that are marked `required`	[k for k, v in User._fields.items() if v.required]
emove column by index `[:, 0:2]` in dataframe `df`	df = df.ix[:, 0:2]
hange a string of integers `x` separated by spaces to a list of	x = map(int, x.split())
vert a string of integers `x` separated by spaces to a list of integer	x = [int(i) for i in x.split()]
find element by css selector input[onclick*='1 Bedroom Deluxe']	driver.find_element_by_css_selector("input[onclick*='1 Bedroom Deluxe']")
Python / Remove special character from string	re.sub('[^a-zA-Z0-9-_*.]', '', my_string)
display a pdf file that has been downloaded as `my_pdf.pdf`	webbrowser.open('file:///my_pdf.pdf')
eplace backslashes in string `result` with empty string ''	result = result.replace('\\', '')
emove backslashes from string `result`	result.replace('\\', '')
eplace value '' in any column of pandas dataframe to NaN	df.replace('-', 'NaN')
vert datetime object to date object in pytho	datetime.datetime.now().date()
w do I convert datetime to date (in Python)?	datetime.datetime.now().date()
get all subelements of an element `a` in an elementtree	[elem.tag for elem in a.iter()]
get all subelements of an element tree `a` excluding the root eleme	[elem.tag for elem in a.iter() if elem is not a]
w can I split and parse a string in Python?	"""2.7.0_bf4fda703454""".split('_')
ve dictionaries in list `lst` to the end of the list if value of key 'language' in each dictionary is not equal to 'en'	sorted(lst, key=lambda x: x['language'] != 'en')
heck if all values of a dictionary `your_dict` are zero `0`	all(value == 0 for value in list(your_dict.values()))
produce a pivot table as dataframe using column 'Y' in datafram `df` to form the axes of the resulting dataframe	df.pivot_table('Y', rows='X', cols='X2')
all `doSomething()` in a tryexcept without handling the exceptio	try: doSomething() except: pass
all `doSomething()` in a tryexcept without handling the exceptio	try: doSomething() except Exception: pass
get a sum of 4d array `M`	M.sum(axis=0).sum(axis=0)
Convert a datetime object `dt` to microtime	time.mktime(dt.timetuple()) + dt.microsecond / 1000000.0
elect all rows in dataframe `df` where the values of column 'columnX' is bigger than or equal to `x` and smaller than or equal to `y`	df[(x <= df['columnX']) & (df['columnX'] <= y)]
a list of lists `L` by index 2 of the inner l	sorted(L, key=itemgetter(2))
a list of lists `l` by index 2 of the inner l	l.sort(key=(lambda x: x[2]))
list `l` by index 2 of the item	sorted(l, key=(lambda x: x[2]))
a list of lists `list_to_sort` by indices 2,0,1 of the inner l	sorted_list = sorted(list_to_sort, key=itemgetter(2, 0, 1))
find rows of 2d array in 3d numpy array 'arr' if the row has value '[[0, 3], [3, 0]]'	np.argwhere(np.all(arr == [[0, 3], [3, 0]], axis=(1, 2)))
From multiIndexed dataframe `data` select columns `a` and `c` within each higher order column `one` and `two`	data.loc[:, (list(itertools.product(['one', 'two'], ['a', 'c'])))]
elect only specific columns 'a' and 'c' from a dataframe 'data' with multiindex colum	data.loc[:, ([('one', 'a'), ('one', 'c'), ('two', 'a'), ('two', 'c')])]
h a sharp, followed by letters (including accent characters) in string `str1` using a regex	hashtags = re.findall('#(\\w+)', str1, re.UNICODE)
Rename file from `src` to `dst`	os.rename(src, dst)
Get all texts and tags from a tag `strong` from etree tag `some_tag` using lxml	print(etree.tostring(some_tag.find('strong')))
Serialize dictionary `data` and its keys to a JSON formatted string	json.dumps({str(k): v for k, v in data.items()})
parse UTF8 encoded HTML response `response` to BeautifulSoup objec	soup = BeautifulSoup(response.read().decode('utf-8'))
delete file `filename`	os.remove(filename)
get the next value greatest to `2` from a list of numbers `num_list`	min([x for x in num_list if x > 2])
Replace each value in column 'prod_type' of dataframe `df` with string 'responsive'	df['prod_type'] = 'responsive'
list `lst` with positives coming before negatives with values sorted respectively	sorted(lst, key=lambda x: (x < 0, x))
get the date 6 months from today	six_months = (date.today() + relativedelta(months=(+ 6)))
get the date 1 month from today	(date(2010, 12, 31) + relativedelta(months=(+ 1)))
get the date 2 months from today	(date(2010, 12, 31) + relativedelta(months=(+ 2)))
alculate the date six months from the current date	print((datetime.date.today() + datetime.timedelta(((6 * 365) / 12))).isoformat())
get a list of keys of dictionary `things` sorted by the value of nested dictionary key 'weight'	sorted(list(things.keys()), key=lambda x: things[x]['weight'], reverse=True)
get all the values from a numpy array `a` excluding index 3	a[np.arange(len(a)) != 3]
delete all elements from a list `x` if a function `fn` taking value as parameter returns `0`	[x for x in lst if fn(x) != 0]
et dataframe `df` index using column 'month'	df.set_index('month')
ead lines from a csv file `./urlseu.csv` into a list of lists `arr`	arr = [line.split(',') for line in open('./urls-eu.csv')]
list comprehension that produces integers between 11 and 19	[i for i in range(100) if i > 10 if i < 20]
Get only digits from a string `strs`	"""""".join([c for c in strs if c.isdigit()])
plit a string `yas` based on tab '\t'	re.split('\\t+', yas.rstrip('\t'))
alar multiply matrix `a` by `b`	(a.T * b).T
emove trailing newline in string test string\n	'test string\n'.rstrip()
emove trailing newline in string 'test string \n\n'	'test string \n\n'.rstrip('\n')
emove newline in string `s`	s.strip()
emove newline in string `s` on the right side	s.rstrip()
emove newline in string `s` on the left side	s.lstrip()
emove newline in string 'Mac EOL\r'	'Mac EOL\r'.rstrip('\r\n')
emove newline in string 'Windows EOL\r\n' on the right side	'Windows EOL\r\n'.rstrip('\r\n')
emove newline in string 'Unix EOL\n' on the right side	'Unix EOL\n'.rstrip('\r\n')
emove newline in string Hello\n\n\n on the right side	'Hello\n\n\n'.rstrip('\n')
plit string `text` into chunks of 16 characters each	re.findall('.{,16}\\b', text)
Get a list comprehension in list of lists `X`	[[X[i][j] for j in range(len(X[i]))] for i in range(len(X))]
vert unicode string '\xd0\xbc\xd0\xb0\xd1\x80\xd0\xba\xd0\xb0' to byte string	'\xd0\xbc\xd0\xb0\xd1\x80\xd0\xba\xd0\xb0'.encode('latin-1')
plit dataframe `df` where the value of column `a` is equal to 'B'	df.groupby((df.a == 'B').shift(1).fillna(0).cumsum())
ave json output from a url ‘http://search.twitter.com/search.json?q=hi’ to file ‘hi.json’ in Python 2	urllib.request.urlretrieve('http://search.twitter.com/search.json?q=hi', 'hi.json')
Find indices of elements equal to zero from numpy array `x`	numpy.where((x == 0))[0]
flush output of python pr	sys.stdout.flush()
vert `i` to string	str(i)
vert `a` to string	a.__str__()

list `lst` based on each element's number of occurrence

sorted(lst, key=lambda x: (-1 * c[x], lst.index(x)))

Get the value with the maximum length in each column in array `foo`

[max(len(str(x)) for x in line) for line in zip(*foo)]

get the count of each unique value in column `Country` of dataframe `df` and store in column `Sum of Accidents`

df.Country.value_counts().reset_index(name='Sum of Accidents')

alculat the difference between each row and the row previous to it in dataframe `data`

data.set_index('Date').diff()

ppend values `[3, 4]` to a set `a`

a.update([3, 4])

et every twostride far element to 1 starting from second element in array `a`

a[1::2] = -1

Get rank of rows from highest to lowest of dataframe `df`, grouped by value in column `group`, according to value in column `value`

df.groupby('group')['value'].rank(ascending=False)

vert js date object 'Tue, 22 Nov 2011 06:00:00 GMT' to python datetime

datetime.strptime('Tue, 22 Nov 2011 06:00:00 GMT', '%a, %d %b %Y %H:%M:%S %Z')

Convert a binary value '1633837924' to string

struct.pack('<I', 1633837924)

ppend string `foo` to list `list`

list.append('foo')

ert string `foo` at position `0` of list `list`

list.insert(0, 'foo')

vert keys in dictionary `thedict` into case insensitive

theset = set(k.lower() for k in thedict)

pad 'dog' up to a length of 5 characters with 'x'

"""{s:{c}^{n}}""".format(s='dog', n=5, c='x')

heck if type of variable `s` is a string

isinstance(s, str)

heck if type of a variable `s` is string

isinstance(s, str)

Convert list of dictionaries `L` into a flat dictionary

dict(pair for d in L for pair in list(d.items()))

erge a list of dictionaries in list `L` into a single dic

{k: v for d in L for k, v in list(d.items())}

a pandas data frame according to column `Peak` in ascending and `Weeks` in descending order

df.sort_values(['Peak', 'Weeks'], ascending=[True, False], inplace=True)

a pandas data frame by column `Peak` in ascending and `Weeks` in descending order

df.sort(['Peak', 'Weeks'], ascending=[True, False], inplace=True)

he code contained in string print('Hello')

eval("print('Hello')")

eating a list of dictionaries [{'A': 1, 'C': 4, 'B': 2, 'D': 4}, {'A': 1, 'C': 4, 'B': 1, 'D': 5}]

[{'A': 1, 'C': 4, 'B': 2, 'D': 4}, {'A': 1, 'C': 4, 'B': 1, 'D': 5}]

Creating a list of dictionaries in pytho

[{'A': 1, 'C': 4, 'B': 2, 'D': 4}, {'A': 1, 'C': 4, 'B': 1, 'D': 5}]

get all possible combination of items from 2dimensional list `a`

list(itertools.product(*a))

Get sum of values of columns 'Y1961', 'Y1962', 'Y1963' after group by on columns Country and Item_code in dataframe `df`.

df.groupby(['Country', 'Item_Code'])[['Y1961', 'Y1962', 'Y1963']].sum()

eate list `done` containing permutations of each element in list `[a, b, c, d]` with variable `x` as tuple

done = [(el, x) for el in [a, b, c, d]]

emove Nan values from array `x`

x = x[numpy.logical_not(numpy.isnan(x))]

emove first directory from path '/First/Second/Third/Fourth/Fifth'

os.path.join(*x.split(os.path.sep)[2:])

Replace `;` with `:` in a string `line`

line = line.replace(';', ':')

all bash command 'tar c my_dir | md5sum' with pipe

subprocess.call('tar c my_dir | md5sum', shell=True)

Convert a hex string `437c2123 ` according to ascii value.

"""437c2123""".decode('hex')

Get a list of all fields in class `User` that are marked `required`

[k for k, v in User._fields.items() if v.required]

emove column by index `[:, 0:2]` in dataframe `df`

df = df.ix[:, 0:2]

hange a string of integers `x` separated by spaces to a list of

x = map(int, x.split())

vert a string of integers `x` separated by spaces to a list of integer

x = [int(i) for i in x.split()]

find element by css selector input[onclick*='1 Bedroom Deluxe']

driver.find_element_by_css_selector("input[onclick*='1 Bedroom Deluxe']")

Python / Remove special character from string

re.sub('[^a-zA-Z0-9-_*.]', '', my_string)

display a pdf file that has been downloaded as `my_pdf.pdf`

webbrowser.open('file:///my_pdf.pdf')

eplace backslashes in string `result` with empty string ''

result = result.replace('\\', '')

emove backslashes from string `result`

result.replace('\\', '')

eplace value '' in any column of pandas dataframe to NaN

df.replace('-', 'NaN')

vert datetime object to date object in pytho

datetime.datetime.now().date()

w do I convert datetime to date (in Python)?

datetime.datetime.now().date()

get all subelements of an element `a` in an elementtree

[elem.tag for elem in a.iter()]

get all subelements of an element tree `a` excluding the root eleme

[elem.tag for elem in a.iter() if elem is not a]

w can I split and parse a string in Python?

"""2.7.0_bf4fda703454""".split('_')

ve dictionaries in list `lst` to the end of the list if value of key 'language' in each dictionary is not equal to 'en'

sorted(lst, key=lambda x: x['language'] != 'en')

heck if all values of a dictionary `your_dict` are zero `0`

all(value == 0 for value in list(your_dict.values()))

produce a pivot table as dataframe using column 'Y' in datafram `df` to form the axes of the resulting dataframe

df.pivot_table('Y', rows='X', cols='X2')

all `doSomething()` in a tryexcept without handling the exceptio

try: doSomething() except: pass

all `doSomething()` in a tryexcept without handling the exceptio

try: doSomething() except Exception: pass

get a sum of 4d array `M`

M.sum(axis=0).sum(axis=0)

Convert a datetime object `dt` to microtime

time.mktime(dt.timetuple()) + dt.microsecond / 1000000.0

elect all rows in dataframe `df` where the values of column 'columnX' is bigger than or equal to `x` and smaller than or equal to `y`

df[(x <= df['columnX']) & (df['columnX'] <= y)]

a list of lists `L` by index 2 of the inner l

sorted(L, key=itemgetter(2))

a list of lists `l` by index 2 of the inner l

l.sort(key=(lambda x: x[2]))

list `l` by index 2 of the item

sorted(l, key=(lambda x: x[2]))

a list of lists `list_to_sort` by indices 2,0,1 of the inner l

sorted_list = sorted(list_to_sort, key=itemgetter(2, 0, 1))

find rows of 2d array in 3d numpy array 'arr' if the row has value '[[0, 3], [3, 0]]'

np.argwhere(np.all(arr == [[0, 3], [3, 0]], axis=(1, 2)))

From multiIndexed dataframe `data` select columns `a` and `c` within each higher order column `one` and `two`

data.loc[:, (list(itertools.product(['one', 'two'], ['a', 'c'])))]

elect only specific columns 'a' and 'c' from a dataframe 'data' with multiindex colum

data.loc[:, ([('one', 'a'), ('one', 'c'), ('two', 'a'), ('two', 'c')])]

h a sharp, followed by letters (including accent characters) in string `str1` using a regex

hashtags = re.findall('#(\\w+)', str1, re.UNICODE)

Rename file from `src` to `dst`

os.rename(src, dst)

Get all texts and tags from a tag `strong` from etree tag `some_tag` using lxml

print(etree.tostring(some_tag.find('strong')))

Serialize dictionary `data` and its keys to a JSON formatted string

json.dumps({str(k): v for k, v in data.items()})

parse UTF8 encoded HTML response `response` to BeautifulSoup objec

soup = BeautifulSoup(response.read().decode('utf-8'))

delete file `filename`

os.remove(filename)

get the next value greatest to `2` from a list of numbers `num_list`

min([x for x in num_list if x > 2])

Replace each value in column 'prod_type' of dataframe `df` with string 'responsive'

df['prod_type'] = 'responsive'

list `lst` with positives coming before negatives with values sorted respectively

sorted(lst, key=lambda x: (x < 0, x))

get the date 6 months from today

six_months = (date.today() + relativedelta(months=(+ 6)))

get the date 1 month from today

(date(2010, 12, 31) + relativedelta(months=(+ 1)))

get the date 2 months from today

(date(2010, 12, 31) + relativedelta(months=(+ 2)))

alculate the date six months from the current date

print((datetime.date.today() + datetime.timedelta(((6 * 365) / 12))).isoformat())

get a list of keys of dictionary `things` sorted by the value of nested dictionary key 'weight'

sorted(list(things.keys()), key=lambda x: things[x]['weight'], reverse=True)

get all the values from a numpy array `a` excluding index 3

a[np.arange(len(a)) != 3]

delete all elements from a list `x` if a function `fn` taking value as parameter returns `0`

[x for x in lst if fn(x) != 0]

et dataframe `df` index using column 'month'

df.set_index('month')

ead lines from a csv file `./urlseu.csv` into a list of lists `arr`

arr = [line.split(',') for line in open('./urls-eu.csv')]

list comprehension that produces integers between 11 and 19

[i for i in range(100) if i > 10 if i < 20]

Get only digits from a string `strs`

"""""".join([c for c in strs if c.isdigit()])

plit a string `yas` based on tab '\t'

re.split('\\t+', yas.rstrip('\t'))

alar multiply matrix `a` by `b`

(a.T * b).T

emove trailing newline in string test string\n

'test string\n'.rstrip()

emove trailing newline in string 'test string \n\n'

'test string \n\n'.rstrip('\n')

emove newline in string `s`

s.strip()

emove newline in string `s` on the right side

s.rstrip()

emove newline in string `s` on the left side

s.lstrip()

emove newline in string 'Mac EOL\r'

'Mac EOL\r'.rstrip('\r\n')

emove newline in string 'Windows EOL\r\n' on the right side

'Windows EOL\r\n'.rstrip('\r\n')

emove newline in string 'Unix EOL\n' on the right side

'Unix EOL\n'.rstrip('\r\n')

emove newline in string Hello\n\n\n on the right side

'Hello\n\n\n'.rstrip('\n')

plit string `text` into chunks of 16 characters each

re.findall('.{,16}\\b', text)

Get a list comprehension in list of lists `X`

[[X[i][j] for j in range(len(X[i]))] for i in range(len(X))]

vert unicode string '\xd0\xbc\xd0\xb0\xd1\x80\xd0\xba\xd0\xb0' to byte string

'\xd0\xbc\xd0\xb0\xd1\x80\xd0\xba\xd0\xb0'.encode('latin-1')

plit dataframe `df` where the value of column `a` is equal to 'B'

df.groupby((df.a == 'B').shift(1).fillna(0).cumsum())

ave json output from a url ‘http://search.twitter.com/search.json?q=hi’ to file ‘hi.json’ in Python 2

urllib.request.urlretrieve('http://search.twitter.com/search.json?q=hi', 'hi.json')

Find indices of elements equal to zero from numpy array `x`

numpy.where((x == 0))[0]

flush output of python pr

sys.stdout.flush()

vert `i` to string

str(i)

vert `a` to string

a.__str__()