question_id
stringlengths 7
12
| nl
stringlengths 4
200
| cmd
stringlengths 2
232
| oracle_man
sequence | canonical_cmd
stringlengths 2
228
| cmd_name
stringclasses 1
value |
|---|---|---|---|---|---|
20048987-61 | print a floating point number 2.345e-67 without any truncation | print('{:.100f}'.format(2.345e-67)) | [
"python.library.functions#format"
] | print('{:.100f}'.format(2.345e-67)) | conala |
4574509-95 | remove duplicate characters from string 'ffffffbbbbbbbqqq' | re.sub('([a-z])\\1+', '\\1', 'ffffffbbbbbbbqqq') | [
"python.library.re#re.sub"
] | re.sub('([a-z])\\1+', '\\1', 'VAR_STR') | conala |
1059559-41 | split string "a;bcd,ef g" on delimiters ';' and ',' | """a;bcd,ef g""".replace(';', ' ').replace(',', ' ').split() | [
"python.library.stdtypes#str.replace"
] | """VAR_STR""".replace('VAR_STR', ' ').replace('VAR_STR', ' ').split() | conala |
17424182-56 | extract all rows from dataframe `data` where the value of column 'Value' is True | data[data['Value'] == True] | [] | VAR_STR[VAR_STR['VAR_STR'] == True] | conala |
9505526-67 | split string `s` into strings of repeating elements | print([a for a, b in re.findall('((\\w)\\2*)', s)]) | [
"python.library.re#re.findall"
] | print([a for a, b in re.findall('((\\w)\\2*)', VAR_STR)]) | conala |
761804-99 | trim string " Hello " | ' Hello '.strip() | [
"python.library.stdtypes#str.strip"
] | """ Hello """.strip() | conala |
761804-12 | trim string `myString ` | myString.strip() | [
"python.library.stdtypes#str.strip"
] | VAR_STR.strip() | conala |
761804-69 | Trimming a string " Hello " | ' Hello '.strip() | [
"python.library.stdtypes#str.strip"
] | """ Hello """.strip() | conala |
761804-7 | Trimming a string " Hello" | ' Hello'.strip() | [
"python.library.stdtypes#str.strip"
] | """ Hello""".strip() | conala |
761804-31 | Trimming a string "Bob has a cat" | 'Bob has a cat'.strip() | [
"python.library.stdtypes#str.strip"
] | """VAR_STR""".strip() | conala |
761804-4 | Trimming a string " Hello " | ' Hello '.strip() | [
"python.library.stdtypes#str.strip"
] | """ Hello """.strip() | conala |
761804-26 | Trimming a string `str` | str.strip() | [
"python.library.stdtypes#str.strip"
] | VAR_STR.strip() | conala |
761804-11 | Trimming "\n" from string `myString` | myString.strip('\n') | [
"python.library.stdtypes#str.strip"
] | VAR_STR.strip('VAR_STR') | conala |
761804-12 | left trimming "\n\r" from string `myString` | myString.lstrip('\n\r') | [
"python.library.stdtypes#str.strip"
] | VAR_STR.lstrip('VAR_STR') | conala |
761804-51 | right trimming "\n\t" from string `myString` | myString.rstrip('\n\t') | [
"python.library.stdtypes#str.rstrip"
] | VAR_STR.rstrip('VAR_STR') | conala |
761804-50 | Trimming a string " Hello\n" by space | ' Hello\n'.strip(' ') | [
"python.library.stdtypes#str.strip"
] | """ Hello
""".strip(' ') | conala |
3518778-98 | read csv file 'my_file.csv' into numpy array | my_data = genfromtxt('my_file.csv', delimiter=',') | [
"numpy.reference.generated.numpy.genfromtxt"
] | my_data = genfromtxt('VAR_STR', delimiter=',') | conala |
3518778-46 | read csv file 'myfile.csv' into array | df = pd.read_csv('myfile.csv', sep=',', header=None) | [
"pandas.reference.api.pandas.read_csv"
] | df = pd.read_csv('VAR_STR', sep=',', header=None) | conala |
3518778-91 | read csv file 'myfile.csv' into array | np.genfromtxt('myfile.csv', delimiter=',') | [
"numpy.reference.generated.numpy.genfromtxt"
] | np.genfromtxt('VAR_STR', delimiter=',') | conala |
3518778-42 | read csv file 'myfile.csv' into array | np.genfromtxt('myfile.csv', delimiter=',', dtype=None) | [
"numpy.reference.generated.numpy.genfromtxt"
] | np.genfromtxt('VAR_STR', delimiter=',', dtype=None) | conala |
22702760-34 | multiply column 'A' and column 'B' by column 'C' in datafram `df` | df[['A', 'B']].multiply(df['C'], axis='index') | [
"numpy.reference.generated.numpy.multiply"
] | VAR_STR[['VAR_STR', 'VAR_STR']].multiply(VAR_STR['VAR_STR'], axis='index') | conala |
10525301-35 | Normalize string `str` from 'cp1252' code to 'utf-8' code | print(str.encode('cp1252').decode('utf-8').encode('cp1252').decode('utf-8')) | [
"python.library.stdtypes#str.encode",
"pandas.reference.api.pandas.series.str.decode"
] | print(VAR_STR.encode('VAR_STR').decode('VAR_STR').encode('VAR_STR').decode('VAR_STR')) | conala |
3294889-83 | Iterating over a dictionary `d` using for loops | for (key, value) in d.items():
pass | [
"python.library.stdtypes#dict.items"
] | for key, value in VAR_STR.items():
pass | conala |
3294889-61 | Iterating over a dictionary `d` using for loops | for (key, value) in list(d.items()):
pass | [
"python.library.functions#list",
"python.library.stdtypes#dict.items"
] | for key, value in list(VAR_STR.items()):
pass | conala |
3294889-5 | Iterating key and items over dictionary `d` | for (letter, number) in list(d.items()):
pass | [
"python.library.functions#list",
"python.library.stdtypes#dict.items"
] | for letter, number in list(VAR_STR.items()):
pass | conala |
3294889-67 | Iterating key and items over dictionary `d` | for (k, v) in list(d.items()):
pass | [
"python.library.functions#list",
"python.library.stdtypes#dict.items"
] | for k, v in list(VAR_STR.items()):
pass | conala |
3294889-59 | get keys and items of dictionary `d` | list(d.items()) | [
"python.library.functions#list",
"python.library.stdtypes#dict.items"
] | list(VAR_STR.items()) | conala |
3294889-5 | get keys and items of dictionary `d` as a list | list(d.items()) | [
"python.library.functions#list",
"python.library.stdtypes#dict.items"
] | list(VAR_STR.items()) | conala |
3294889-54 | Iterating key and items over dictionary `d` | for (k, v) in list(d.items()):
pass | [
"python.library.functions#list",
"python.library.stdtypes#dict.items"
] | for k, v in list(VAR_STR.items()):
pass | conala |
3294889-3 | Iterating key and items over dictionary `d` | for (letter, number) in list(d.items()):
pass | [
"python.library.functions#list",
"python.library.stdtypes#dict.items"
] | for letter, number in list(VAR_STR.items()):
pass | conala |
3294889-25 | Iterating key and items over dictionary `d` | for (letter, number) in list(d.items()):
pass | [
"python.library.functions#list",
"python.library.stdtypes#dict.items"
] | for letter, number in list(VAR_STR.items()):
pass | conala |
7356042-14 | Create 2D numpy array from the data provided in 'somefile.csv' with each row in the file having same number of values | X = numpy.loadtxt('somefile.csv', delimiter=',') | [
"numpy.reference.generated.numpy.loadtxt"
] | X = numpy.loadtxt('VAR_STR', delimiter=',') | conala |
1946181-83 | control the keyboard and mouse with dogtail in linux | dogtail.rawinput.click(100, 100) | [] | dogtail.rawinput.click(100, 100) | conala |
2040038-20 | sort datetime objects `birthdays` by `month` and `day` | birthdays.sort(key=lambda d: (d.month, d.day)) | [
"python.library.stdtypes#list.sort"
] | VAR_STR.sort(key=lambda d: (d.VAR_STR, d.VAR_STR)) | conala |
275018-37 | remove trailing newline in string "test string\n" | 'test string\n'.rstrip() | [
"python.library.stdtypes#str.rstrip"
] | """VAR_STR""".rstrip() | conala |
275018-63 | remove trailing newline in string 'test string \n\n' | 'test string \n\n'.rstrip('\n') | [
"python.library.stdtypes#str.rstrip"
] | """VAR_STR""".rstrip('\n') | conala |
275018-98 | remove newline in string `s` | s.strip() | [
"python.library.stdtypes#str.strip"
] | VAR_STR.strip() | conala |
275018-8 | remove newline in string `s` on the right side | s.rstrip() | [
"python.library.stdtypes#str.rstrip"
] | VAR_STR.rstrip() | conala |
275018-64 | remove newline in string `s` on the left side | s.lstrip() | [
"python.library.stdtypes#str.lstrip"
] | VAR_STR.lstrip() | conala |
275018-9 | remove newline in string 'Mac EOL\r' | 'Mac EOL\r'.rstrip('\r\n') | [
"python.library.stdtypes#str.rstrip"
] | """VAR_STR""".rstrip('\r\n') | conala |
275018-25 | remove newline in string 'Windows EOL\r\n' on the right side | 'Windows EOL\r\n'.rstrip('\r\n') | [
"python.library.stdtypes#str.rstrip"
] | """VAR_STR""".rstrip('\r\n') | conala |
275018-43 | remove newline in string 'Unix EOL\n' on the right side | 'Unix EOL\n'.rstrip('\r\n') | [
"python.library.stdtypes#str.rstrip"
] | """VAR_STR""".rstrip('\r\n') | conala |
275018-58 | remove newline in string "Hello\n\n\n" on the right side | 'Hello\n\n\n'.rstrip('\n') | [
"python.library.stdtypes#str.rstrip"
] | """VAR_STR""".rstrip('\n') | conala |
15530399-12 | split string `text` by the occurrences of regex pattern '(?<=\\?|!|\\.)\\s{0,2}(?=[A-Z]|$)' | re.split('(?<=\\?|!|\\.)\\s{0,2}(?=[A-Z]|$)', text) | [
"python.library.re#re.split"
] | re.split('VAR_STR', VAR_STR) | conala |
186857-59 | split a string `s` by ';' and convert to a dictionary | dict(item.split('=') for item in s.split(';')) | [
"python.library.stdtypes#dict",
"python.library.stdtypes#str.split"
] | dict(item.split('=') for item in VAR_STR.split('VAR_STR')) | conala |
17117912-75 | create a list where each element is a value of the key 'Name' for each dictionary `d` in the list `thisismylist` | [d['Name'] for d in thisismylist] | [] | [VAR_STR['VAR_STR'] for VAR_STR in VAR_STR] | conala |
17117912-14 | create a list of tuples with the values of keys 'Name' and 'Age' from each dictionary `d` in the list `thisismylist` | [(d['Name'], d['Age']) for d in thisismylist] | [] | [(VAR_STR['VAR_STR'], VAR_STR['VAR_STR']) for VAR_STR in VAR_STR] | conala |
8650415-85 | Reverse key-value pairs in a dictionary `map` | dict((v, k) for k, v in map.items()) | [
"python.library.stdtypes#dict",
"python.library.stdtypes#dict.items"
] | dict((v, k) for k, v in VAR_STR.items()) | conala |
19153328-63 | assign value in `group` dynamically to class property `attr` | setattr(self, attr, group) | [
"python.library.functions#setattr"
] | setattr(self, VAR_STR, VAR_STR) | conala |
17627531-50 | sort list of date strings 'd' | sorted(d, key=lambda x: datetime.datetime.strptime(x, '%m-%Y')) | [
"python.library.datetime#datetime.datetime.strptime",
"python.library.functions#sorted"
] | sorted(VAR_STR, key=lambda x: datetime.datetime.strptime(x, '%m-%Y')) | conala |
6159313-36 | test if either of strings `a` or `b` are members of the set of strings, `['b', 'a', 'foo', 'bar']` | set(['a', 'b']).issubset(['b', 'a', 'foo', 'bar']) | [
"python.library.stdtypes#set",
"python.library.stdtypes#frozenset.issubset"
] | set(['VAR_STR', 'VAR_STR']).issubset(['VAR_STR', 'VAR_STR', 'foo', 'bar']) | conala |
6159313-37 | Check if all the values in a list `['a', 'b']` are present in another list `['b', 'a', 'foo', 'bar']` | all(x in ['b', 'a', 'foo', 'bar'] for x in ['a', 'b']) | [
"python.library.functions#all"
] | all(x in [VAR_STR] for x in [VAR_STR]) | conala |
17306755-9 | format float `3.5e+20` to `$3.5 \\times 10^{20}$` and set as title of matplotlib plot `ax` | ax.set_title('$%s \\times 10^{%s}$' % ('3.5', '+20')) | [
"matplotlib.legend_api#matplotlib.legend.Legend.set_title"
] | VAR_STR.set_title('$%s \\times 10^{%s}$' % ('3.5', '+20')) | conala |
24659239-4 | set text color as `red` and background color as `#A3C1DA` in qpushbutton | setStyleSheet('QPushButton {background-color: #A3C1DA; color: red;}') | [] | setStyleSheet('QPushButton {background-color: #A3C1DA; color: red;}') | conala |
12201577-67 | convert an rgb image 'messi5.jpg' into grayscale `img` | img = cv2.imread('messi5.jpg', 0) | [
"matplotlib.image_api#matplotlib.image.imread"
] | VAR_STR = cv2.imread('VAR_STR', 0) | conala |
4411811-39 | create list `levels` containing 3 empty dictionaries | levels = [{}, {}, {}] | [] | VAR_STR = [{}, {}, {}] | conala |
1713594-63 | parse string '01-Jan-1995' into a datetime object using format '%d-%b-%Y' | datetime.datetime.strptime('01-Jan-1995', '%d-%b-%Y') | [
"python.library.datetime#datetime.datetime.strptime"
] | datetime.datetime.strptime('VAR_STR', 'VAR_STR') | conala |
7768859-33 | Convert integer elements in list `wordids` to strings | [str(wi) for wi in wordids] | [
"python.library.stdtypes#str"
] | [str(wi) for wi in VAR_STR] | conala |
16099694-63 | get a list `cleaned` that contains all non-empty elements in list `your_list` | cleaned = [x for x in your_list if x] | [] | VAR_STR = [x for x in VAR_STR if x] | conala |
17038426-88 | split a string `yas` based on tab '\t' | re.split('\\t+', yas.rstrip('\t')) | [
"python.library.re#re.split",
"python.library.stdtypes#str.rstrip"
] | re.split('\\t+', VAR_STR.rstrip('VAR_STR')) | conala |
34197047-67 | sorting the lists in list of lists `data` | [sorted(item) for item in data] | [
"python.library.functions#sorted"
] | [sorted(item) for item in VAR_STR] | conala |
22741068-41 | remove identical items from list `my_list` and sort it alphabetically | sorted(set(my_list)) | [
"python.library.functions#sorted",
"python.library.stdtypes#set"
] | sorted(set(VAR_STR)) | conala |
35017035-30 | convert a list of lists `a` into list of tuples of appropriate elements form nested lists | zip(*a) | [
"python.library.functions#zip"
] | zip(*VAR_STR) | conala |
7595148-31 | converting hex string `s` to its integer representations | [ord(c) for c in s.decode('hex')] | [
"python.library.functions#ord",
"python.library.stdtypes#bytearray.decode"
] | [ord(c) for c in VAR_STR.decode('hex')] | conala |
41386443-67 | create pandas data frame `df` from txt file `filename.txt` with column `Region Name` and separator `;` | df = pd.read_csv('filename.txt', sep=';', names=['Region Name']) | [
"pandas.reference.api.pandas.read_csv"
] | VAR_STR = pd.read_csv('VAR_STR', sep='VAR_STR', names=['VAR_STR']) | conala |
14657241-69 | get a list of all the duplicate items in dataframe `df` using pandas | pd.concat(g for _, g in df.groupby('ID') if len(g) > 1) | [
"pandas.reference.api.pandas.dataframe.groupby",
"pandas.reference.api.pandas.concat",
"python.library.functions#len"
] | pd.concat(g for _, g in VAR_STR.groupby('ID') if len(g) > 1) | conala |
930865-13 | sort objects in model `Profile` based on Theirs `reputation` attribute | sorted(Profile.objects.all(), key=lambda p: p.reputation) | [
"python.library.functions#sorted",
"python.library.functions#all"
] | sorted(VAR_STR.objects.all(), key=lambda p: p.VAR_STR) | conala |
20585920-51 | for a dictionary `a`, set default value for key `somekey` as list and append value `bob` in that key | a.setdefault('somekey', []).append('bob') | [
"python.library.stdtypes#dict.setdefault",
"numpy.reference.generated.numpy.append"
] | VAR_STR.setdefault('VAR_STR', []).append('VAR_STR') | conala |
3984539-10 | replace white spaces in string ' a\n b\n c\nd e' with empty string '' | re.sub('(?m)^[^\\S\\n]+', '', ' a\n b\n c\nd e') | [
"python.library.re#re.sub"
] | re.sub('(?m)^[^\\S\\n]+', 'VAR_STR', ' a\n b\n c\nd e') | conala |
3984539-99 | remove white spaces from all the lines using a regular expression in string 'a\n b\n c' | re.sub('(?m)^\\s+', '', 'a\n b\n c') | [
"python.library.re#re.sub"
] | re.sub('(?m)^\\s+', '', 'VAR_STR') | conala |
17141558-7 | sort dataframe `df` based on column 'b' in ascending and column 'c' in descending | df.sort_values(['b', 'c'], ascending=[True, False], inplace=True) | [
"pandas.reference.api.pandas.dataframe.sort_values"
] | VAR_STR.sort_values(['VAR_STR', 'VAR_STR'], ascending=[True, False], inplace=True) | conala |
17141558-84 | sort dataframe `df` based on column 'a' in ascending and column 'b' in descending | df.sort_values(['a', 'b'], ascending=[True, False]) | [
"pandas.reference.api.pandas.dataframe.sort_values"
] | VAR_STR.sort_values(['VAR_STR', 'VAR_STR'], ascending=[True, False]) | conala |
17141558-74 | sort a pandas data frame with column `a` in ascending and `b` in descending order | df1.sort(['a', 'b'], ascending=[True, False], inplace=True) | [
"python.library.stdtypes#list.sort"
] | df1.sort(['VAR_STR', 'VAR_STR'], ascending=[True, False], inplace=True) | conala |
17141558-89 | sort a pandas data frame by column `a` in ascending, and by column `b` in descending order | df.sort(['a', 'b'], ascending=[True, False]) | [
"pandas.reference.api.pandas.index.sort"
] | df.sort(['VAR_STR', 'VAR_STR'], ascending=[True, False]) | conala |
1447575-49 | create a symlink directory `D:\\testdirLink` for directory `D:\\testdir` with unicode support using ctypes library | kdll.CreateSymbolicLinkW('D:\\testdirLink', 'D:\\testdir', 1) | [] | kdll.CreateSymbolicLinkW('VAR_STR', 'VAR_STR', 1) | conala |
861190-38 | Sort a list of dictionaries `mylist` by keys "weight" and "factor" | mylist.sort(key=operator.itemgetter('weight', 'factor')) | [
"python.library.operator#operator.itemgetter",
"python.library.stdtypes#list.sort"
] | VAR_STR.sort(key=operator.itemgetter('VAR_STR', 'VAR_STR')) | conala |
861190-31 | ordering a list of dictionaries `mylist` by elements 'weight' and 'factor' | mylist.sort(key=lambda d: (d['weight'], d['factor'])) | [
"python.library.stdtypes#list.sort"
] | VAR_STR.sort(key=lambda d: (d['VAR_STR'], d['VAR_STR'])) | conala |
8081545-50 | convert tuple elements in list `[(1,2),(3,4),(5,6),]` into lists | map(list, zip(*[(1, 2), (3, 4), (5, 6)])) | [
"python.library.functions#zip",
"python.library.functions#map"
] | map(list, zip(*[(1, 2), (3, 4), (5, 6)])) | conala |
8081545-98 | convert list of tuples to multiple lists in Python | map(list, zip(*[(1, 2), (3, 4), (5, 6)])) | [
"python.library.functions#zip",
"python.library.functions#map"
] | map(list, zip(*[(1, 2), (3, 4), (5, 6)])) | conala |
8081545-96 | convert list of tuples to multiple lists in Python | zip(*[(1, 2), (3, 4), (5, 6)]) | [
"python.library.functions#zip"
] | zip(*[(1, 2), (3, 4), (5, 6)]) | conala |
4965159-23 | execute os command `my_cmd` | os.system(my_cmd) | [
"python.library.os#os.system"
] | os.system(VAR_STR) | conala |
4793617-92 | derive the week start for the given week number and year ‘2011, 4, 0’ | datetime.datetime.strptime('2011, 4, 0', '%Y, %U, %w') | [
"python.library.datetime#datetime.datetime.strptime"
] | datetime.datetime.strptime('2011, 4, 0', '%Y, %U, %w') | conala |
21350605-24 | python selenium click on button '.button.c_button.s_button' | driver.find_element_by_css_selector('.button.c_button.s_button').click() | [] | driver.find_element_by_css_selector('VAR_STR').click() | conala |
21350605-24 | python selenium click on button | driver.find_element_by_css_selector('.button .c_button .s_button').click() | [] | driver.find_element_by_css_selector('.button .c_button .s_button').click() | conala |
30190459-31 | read CSV file 'my.csv' into a dataframe `df` with datatype of float for column 'my_column' considering character 'n/a' as NaN value | df = pd.read_csv('my.csv', dtype={'my_column': np.float64}, na_values=['n/a']) | [
"pandas.reference.api.pandas.read_csv"
] | VAR_STR = pd.read_csv('VAR_STR', dtype={'VAR_STR': np.float64}, na_values=['VAR_STR']) | conala |
30190459-15 | convert nan values to ‘n/a’ while reading rows from a csv `read_csv` with pandas | df = pd.read_csv('my.csv', na_values=['n/a']) | [
"pandas.reference.api.pandas.read_csv"
] | df = pd.VAR_STR('my.csv', na_values=['n/a']) | conala |
13076560-88 | get indexes of all true boolean values from a list `bool_list` | [i for i, elem in enumerate(bool_list, 1) if elem] | [
"python.library.functions#enumerate"
] | [i for i, elem in enumerate(VAR_STR, 1) if elem] | conala |
3159155-97 | get a list `no_integers` of all the items in list `mylist` that are not of type `int` | no_integers = [x for x in mylist if not isinstance(x, int)] | [
"python.library.functions#isinstance"
] | VAR_STR = [x for x in VAR_STR if not isinstance(x, VAR_STR)] | conala |
5618878-38 | concatenating values in `list1` to a string | str1 = ''.join(list1) | [
"python.library.stdtypes#str.join"
] | str1 = ''.join(VAR_STR) | conala |
5618878-35 | concatenating values in list `L` to a string, separate by space | ' '.join((str(x) for x in L)) | [
"python.library.stdtypes#str",
"python.library.stdtypes#str.join"
] | """ """.join(str(x) for x in VAR_STR) | conala |
5618878-66 | concatenating values in `list1` to a string | str1 = ''.join((str(e) for e in list1)) | [
"python.library.stdtypes#str",
"python.library.stdtypes#str.join"
] | str1 = ''.join(str(e) for e in VAR_STR) | conala |
5618878-26 | concatenating values in list `L` to a string | makeitastring = ''.join(map(str, L)) | [
"python.library.functions#map",
"python.library.stdtypes#str.join"
] | makeitastring = ''.join(map(str, VAR_STR)) | conala |
14358567-16 | find consecutive segments from a column 'A' in a pandas data frame 'df' | df.reset_index().groupby('A')['index'].apply(np.array) | [
"pandas.reference.api.pandas.dataframe.reset_index",
"pandas.reference.api.pandas.dataframe.apply",
"pandas.reference.api.pandas.dataframe.groupby"
] | VAR_STR.reset_index().groupby('VAR_STR')['index'].apply(np.array) | conala |
26155985-7 | place '\' infront of each non-letter char in string `line` | print(re.sub('[_%^$]', '\\\\\\g<0>', line)) | [
"python.library.re#re.sub"
] | print(re.sub('[_%^$]', '\\\\\\g<0>', VAR_STR)) | conala |
8459231-72 | sort a list of tuples `my_list` by second parameter in the tuple | my_list.sort(key=lambda x: x[1]) | [
"python.library.stdtypes#list.sort"
] | VAR_STR.sort(key=lambda x: x[1]) | conala |
5788891-79 | execute a file './abc.py' with arguments `arg1` and `arg2` in python shell | subprocess.call(['./abc.py', arg1, arg2]) | [
"python.library.subprocess#subprocess.call"
] | subprocess.call(['VAR_STR', VAR_STR, VAR_STR]) | conala |
8569201-37 | find the string matches within parenthesis from a string `s` using regex | m = re.search('\\[(\\w+)\\]', s) | [
"python.library.re#re.search"
] | m = re.search('\\[(\\w+)\\]', VAR_STR) | conala |
19365513-49 | Add row `['8/19/2014', 'Jun', 'Fly', '98765']` to dataframe `df` | df.loc[len(df)] = ['8/19/2014', 'Jun', 'Fly', '98765'] | [
"pandas.reference.api.pandas.dataframe.loc",
"python.library.functions#len"
] | VAR_STR.loc[len(VAR_STR)] = [VAR_STR] | conala |
4182603-40 | decode the string 'stringnamehere' to UTF-8 | stringnamehere.decode('utf-8', 'ignore') | [
"python.library.stdtypes#bytearray.decode"
] | VAR_STR.decode('utf-8', 'ignore') | conala |
6539881-93 | convert string `apple` from iso-8859-1/latin1 to utf-8 | apple.decode('iso-8859-1').encode('utf8') | [
"python.library.stdtypes#str.encode",
"python.library.stdtypes#bytearray.decode"
] | VAR_STR.decode('iso-8859-1').encode('utf8') | conala |
Subsets and Splits
No saved queries yet
Save your SQL queries to embed, download, and access them later. Queries will appear here once saved.