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 |
|---|---|---|---|---|---|
7741878-15 | apply `numpy.linalg.norm` to each row of a matrix `a` | numpy.apply_along_axis(numpy.linalg.norm, 1, a) | [
"numpy.reference.generated.numpy.apply_along_axis"
] | numpy.apply_along_axis(numpy.linalg.norm, 1, VAR_STR) | conala |
10895028-20 | append dict `{'f': var6, 'g': var7, 'h': var8}` to value of key `e` in dict `jsobj['a']['b']` | jsobj['a']['b']['e'].append({'f': var6, 'g': var7, 'h': var8}) | [
"numpy.reference.generated.numpy.append"
] | jsobj['a']['b']['VAR_STR'].append({VAR_STR}) | conala |
21104592-91 | read json `elevations` to pandas dataframe `df` | pd.read_json(elevations) | [
"pandas.reference.api.pandas.read_json"
] | pd.read_json(VAR_STR) | conala |
12324456-53 | keep a list `dataList` of lists sorted as it is created by second element | dataList.sort(key=lambda x: x[1]) | [
"python.library.stdtypes#list.sort"
] | VAR_STR.sort(key=lambda x: x[1]) | conala |
10213994-42 | sorting a list of tuples `list_of_tuples` where each tuple is reversed | sorted(list_of_tuples, key=lambda tup: tup[::-1]) | [
"python.library.functions#sorted"
] | sorted(VAR_STR, key=lambda tup: tup[::-1]) | conala |
10213994-17 | sorting a list of tuples `list_of_tuples` by second key | sorted(list_of_tuples, key=lambda tup: tup[1]) | [
"python.library.functions#sorted"
] | sorted(VAR_STR, key=lambda tup: tup[1]) | conala |
5251663-9 | check if any values in a list `input_list` is a list | any(isinstance(el, list) for el in input_list) | [
"python.library.functions#isinstance",
"python.library.functions#any"
] | any(isinstance(el, list) for el in VAR_STR) | conala |
4877844-81 | check if string 'x' is in list `['x', 'd', 'a', 's', 'd', 's']` | 'x' in ['x', 'd', 'a', 's', 'd', 's'] | [] | 'VAR_STR' in ['VAR_STR', 'd', 'a', 's', 'd', 's'] | conala |
40016359-9 | Get the first and last 3 elements of list `l` | l[:3] + l[-3:] | [] | VAR_STR[:3] + VAR_STR[-3:] | conala |
1038824-12 | remove a substring ".com" from the end of string `url` | if url.endswith('.com'):
url = url[:(-4)] | [
"python.library.stdtypes#str.endswith"
] | if VAR_STR.endswith('VAR_STR'):
VAR_STR = VAR_STR[:-4] | conala |
1038824-99 | remove a substring ".com" from the end of string `url` | url = re.sub('\\.com$', '', url) | [
"python.library.re#re.sub"
] | VAR_STR = re.sub('\\.com$', '', VAR_STR) | conala |
1038824-76 | remove a substring ".com" from the end of string `url` | print(url.replace('.com', '')) | [
"python.library.stdtypes#str.replace"
] | print(VAR_STR.replace('VAR_STR', '')) | conala |
1038824-70 | remove a substring `suffix` from the end of string `text` | if (not text.endswith(suffix)):
return text
return text[:(len(text) - len(suffix))] | [
"python.library.functions#len"
] | if not VAR_STR.endswith(VAR_STR):
return VAR_STR
return VAR_STR[:len(VAR_STR) - len(VAR_STR)] | conala |
40319433-71 | find the euclidean distance between two 3-d arrays `A` and `B` | np.sqrt(((A - B) ** 2).sum(-1)) | [
"numpy.reference.generated.numpy.sqrt",
"python.library.functions#sum"
] | np.sqrt(((VAR_STR - VAR_STR) ** 2).sum(-1)) | conala |
2094176-57 | split string `a` using new-line character '\n' as separator | a.rstrip().split('\n') | [
"python.library.stdtypes#str.rstrip",
"python.library.stdtypes#str.split"
] | VAR_STR.rstrip().split('VAR_STR') | conala |
2094176-44 | split a string `a` with new line character | a.split('\n')[:-1] | [
"python.library.stdtypes#str.split"
] | VAR_STR.split('\n')[:-1] | conala |
4979542-63 | unpack the arguments out of list `params` to function `some_func` | some_func(*params) | [] | VAR_STR(*VAR_STR) | conala |
8383213-96 | python regex for hyphenated words in `text` | re.findall('\\w+(?:-\\w+)+', text) | [
"python.library.re#re.findall"
] | re.findall('\\w+(?:-\\w+)+', VAR_STR) | conala |
31029560-17 | plot a bar graph from the column 'color' in the DataFrame 'df' | df.colour.value_counts().plot(kind='bar') | [
"pandas.reference.api.pandas.dataframe.value_counts",
"pandas.reference.api.pandas.dataframe.plot"
] | VAR_STR.colour.value_counts().plot(kind='bar') | conala |
31029560-68 | plot categorical data in series `df` with kind `bar` using pandas and matplotlib | df.groupby('colour').size().plot(kind='bar') | [
"pandas.reference.api.pandas.dataframe.groupby",
"pandas.reference.api.pandas.dataframe.plot",
"pandas.reference.api.pandas.dataframe.size"
] | VAR_STR.groupby('colour').size().plot(kind='VAR_STR') | conala |
18319101-1 | generate random upper-case ascii string of 12 characters length | print(''.join(choice(ascii_uppercase) for i in range(12))) | [
"python.library.functions#range",
"python.library.random#random.choice",
"python.library.stdtypes#str.join"
] | print(''.join(choice(ascii_uppercase) for i in range(12))) | conala |
7934620-36 | python: dots in the name of variable in a format string | """Name: {0[person.name]}""".format({'person.name': 'Joe'}) | [
"python.library.functions#format"
] | """Name: {0[person.name]}""".format({'person.name': 'Joe'}) | conala |
13954840-33 | open the file 'words.txt' in 'rU' mode | f = open('words.txt', 'rU') | [
"python.library.urllib.request#open"
] | f = open('VAR_STR', 'VAR_STR') | conala |
39602824-29 | Replace each value in column 'prod_type' of dataframe `df` with string 'responsive' | df['prod_type'] = 'responsive' | [] | VAR_STR['VAR_STR'] = 'VAR_STR' | conala |
16994696-65 | python get time stamp on file `file` in '%m/%d/%Y' format | time.strftime('%m/%d/%Y', time.gmtime(os.path.getmtime(file))) | [
"python.library.time#time.gmtime",
"python.library.time#time.strftime",
"python.library.os.path#os.path.getmtime"
] | time.strftime('VAR_STR', time.gmtime(os.path.getmtime(VAR_STR))) | conala |
23887881-8 | duplicate data in pandas dataframe `x` for 5 times | pd.concat([x] * 5, ignore_index=True) | [
"pandas.reference.api.pandas.concat"
] | pd.concat([VAR_STR] * 5, ignore_index=True) | conala |
23887881-70 | Get a repeated pandas data frame object `x` by `5` times | pd.concat([x] * 5) | [
"pandas.reference.api.pandas.concat"
] | pd.concat([VAR_STR] * 5) | conala |
6278847-2 | kill a process `make.exe` from python script on windows | os.system('taskkill /im make.exe') | [
"python.library.os#os.system"
] | os.system('taskkill /im make.exe') | conala |
22240602-20 | check if all elements in list `mylist` are the same | len(set(mylist)) == 1 | [
"python.library.functions#len",
"python.library.stdtypes#set"
] | len(set(VAR_STR)) == 1 | conala |
8209568-32 | draw a grid line on every tick of plot `plt` | plt.grid(True) | [
"matplotlib._as_gen.mpl_toolkits.axisartist.axislines.axes#mpl_toolkits.axisartist.axislines.Axes.grid"
] | VAR_STR.grid(True) | conala |
11303238-52 | find recurring patterns in a string '42344343434' | re.findall('^(.+?)((.+)\\3+)$', '42344343434')[0][:-1] | [
"python.library.re#re.findall"
] | re.findall('^(.+?)((.+)\\3+)$', 'VAR_STR')[0][:-1] | conala |
6294179-66 | How to find all occurrences of an element in a list? | indices = [i for i, x in enumerate(my_list) if x == 'whatever'] | [
"python.library.functions#enumerate"
] | indices = [i for i, x in enumerate(my_list) if x == 'whatever'] | conala |
15183084-19 | create a dictionary using two lists`x` and `y` | dict(zip(x, y)) | [
"python.library.functions#zip",
"python.library.stdtypes#dict"
] | dict(zip(VAR_STR, VAR_STR)) | conala |
3430372-86 | get full path of current directory | os.path.dirname(os.path.abspath(__file__)) | [
"python.library.os.path#os.path.dirname",
"python.library.os.path#os.path.abspath"
] | os.path.dirname(os.path.abspath(__file__)) | conala |
11811392-43 | generate a list from a pandas dataframe `df` with the column name and column values | df.values.tolist() | [
"pandas.reference.api.pandas.series.tolist"
] | VAR_STR.values.tolist() | conala |
12310141-33 | check if all lists in list `L` have three elements of integer 1 | all(x.count(1) == 3 for x in L) | [
"python.library.functions#all",
"python.library.stdtypes#str.count"
] | all(x.count(1) == 3 for x in VAR_STR) | conala |
5048841-98 | Sort list `my_list` in alphabetical order based on the values associated with key 'name' of each dictionary in the list | my_list.sort(key=operator.itemgetter('name')) | [
"python.library.operator#operator.itemgetter",
"python.library.stdtypes#list.sort"
] | VAR_STR.sort(key=operator.itemgetter('VAR_STR')) | conala |
24076297-68 | display first 5 characters of string 'aaabbbccc' | """{:.5}""".format('aaabbbccc') | [
"python.library.functions#format"
] | """{:.5}""".format('VAR_STR') | conala |
16374540-19 | Convert a list `['A:1', 'B:2', 'C:3', 'D:4']` to dictionary | dict(map(lambda s: s.split(':'), ['A:1', 'B:2', 'C:3', 'D:4'])) | [
"python.library.functions#map",
"python.library.stdtypes#dict",
"python.library.stdtypes#str.split"
] | dict(map(lambda s: s.split(':'), [VAR_STR])) | conala |
13571134-46 | recursively go through all subdirectories and files in `rootdir` | for (root, subFolders, files) in os.walk(rootdir):
pass | [
"python.library.os#os.walk"
] | for root, subFolders, files in os.walk(VAR_STR):
pass | conala |
6618515-54 | sort list `X` based on values from another list `Y` | [x for y, x in sorted(zip(Y, X))] | [
"python.library.functions#zip",
"python.library.functions#sorted"
] | [x for y, x in sorted(zip(VAR_STR, VAR_STR))] | conala |
6618515-6 | sorting list 'X' based on values from another list 'Y' | [x for y, x in sorted(zip(Y, X))] | [
"python.library.functions#zip",
"python.library.functions#sorted"
] | [x for y, x in sorted(zip(VAR_STR, VAR_STR))] | conala |
640001-87 | remove parentheses and text within it in string `filename` | re.sub('\\([^)]*\\)', '', filename) | [
"python.library.re#re.sub"
] | re.sub('\\([^)]*\\)', '', VAR_STR) | conala |
14853243-64 | find all `owl:Class` tags by parsing xml with namespace | root.findall('{http://www.w3.org/2002/07/owl#}Class') | [
"python.library.re#re.findall"
] | root.findall('{http://www.w3.org/2002/07/owl#}Class') | conala |
6740865-68 | print a unicode string `text` | print(text.encode('windows-1252')) | [
"python.library.stdtypes#str.encode"
] | print(VAR_STR.encode('windows-1252')) | conala |
41192805-11 | Concatenate dataframe `df_1` to dataframe `df_2` sorted by values of the column 'y' | pd.concat([df_1, df_2.sort_values('y')]) | [
"pandas.reference.api.pandas.concat",
"pandas.reference.api.pandas.dataframe.sort_values"
] | pd.concat([VAR_STR, VAR_STR.sort_values('VAR_STR')]) | conala |
15014276-86 | sum values greater than 0 in dictionary `d` | sum(v for v in list(d.values()) if v > 0) | [
"python.library.functions#sum",
"python.library.functions#list",
"python.library.stdtypes#dict.values"
] | sum(v for v in list(VAR_STR.values()) if v > 0) | conala |
18131367-54 | Get all the items from a list of tuple 'l' where second item in tuple is '1'. | [x for x in l if x[1] == 1] | [] | [x for x in VAR_STR if x[1] == 1] | conala |
12030074-25 | generate list of numbers in specific format using string formatting precision. | [('%.2d' % i) for i in range(16)] | [
"python.library.functions#range"
] | [('%.2d' % i) for i in range(16)] | conala |
41133414-48 | strip everything up to and including the character `&` from url `url`, strip the character `=` from the remaining string and concatenate `.html` to the end | url.split('&')[-1].replace('=', '') + '.html' | [
"python.library.stdtypes#str.replace",
"python.library.stdtypes#str.split"
] | VAR_STR.split('VAR_STR')[-1].replace('VAR_STR', '') + 'VAR_STR' | conala |
1058712-18 | select a random element from array `[1, 2, 3]` | random.choice([1, 2, 3]) | [
"python.library.random#random.choice"
] | random.choice([VAR_STR]) | conala |
22520932-13 | remove all non-alphabet chars from string `s` | """""".join([i for i in s if i.isalpha()]) | [
"python.library.stdtypes#str.isalpha",
"python.library.stdtypes#str.join"
] | """""".join([i for i in VAR_STR if i.isalpha()]) | conala |
23797491-57 | convert date strings in pandas dataframe column`df['date']` to pandas timestamps using the format '%d%b%Y' | df['date'] = pd.to_datetime(df['date'], format='%d%b%Y') | [
"pandas.reference.api.pandas.to_datetime"
] | df['date'] = pd.to_datetime(df['date'], format='VAR_STR') | conala |
21822054-79 | force bash interpreter '/bin/bash' to be used instead of shell | os.system('GREPDB="echo 123"; /bin/bash -c "$GREPDB"') | [
"python.library.os#os.system"
] | os.system('GREPDB="echo 123"; /bin/bash -c "$GREPDB"') | conala |
21822054-28 | Run a command `echo hello world` in bash instead of shell | os.system('/bin/bash -c "echo hello world"') | [
"python.library.os#os.system"
] | os.system('/bin/bash -c "echo hello world"') | conala |
18358938-63 | get index values of pandas dataframe `df` as list | df.index.values.tolist() | [
"pandas.reference.api.pandas.index.tolist"
] | VAR_STR.index.values.tolist() | conala |
30241279-15 | run app `app` on host '192.168.0.58' and port 9000 in Flask | app.run(host='192.168.0.58', port=9000, debug=False) | [
"python.library.pdb#pdb.run"
] | VAR_STR.run(host='VAR_STR', port=9000, debug=False) | conala |
727507-53 | print unicode string `ex\xe1mple` in uppercase | print('ex\xe1mple'.upper()) | [
"python.library.stdtypes#str.upper"
] | print('VAR_STR'.upper()) | conala |
40639071-13 | Get the sum of values to the power of their indices in a list `l` | sum(j ** i for i, j in enumerate(l, 1)) | [
"python.library.functions#enumerate",
"python.library.functions#sum"
] | sum(j ** i for i, j in enumerate(VAR_STR, 1)) | conala |
14162026-97 | get the first row, second column; second row, first column, and first row third column values of numpy array `arr` | arr[[0, 1, 1], [1, 0, 2]] | [] | VAR_STR[[0, 1, 1], [1, 0, 2]] | conala |
28538536-94 | Delete mulitple columns `columnheading1`, `columnheading2` in pandas data frame `yourdf` | yourdf.drop(['columnheading1', 'columnheading2'], axis=1, inplace=True) | [
"pandas.reference.api.pandas.dataframe.drop"
] | VAR_STR.drop(['VAR_STR', 'VAR_STR'], axis=1, inplace=True) | conala |
40079728-79 | Django get first 10 records of model `User` ordered by criteria 'age' of model 'pet' | User.objects.order_by('-pet__age')[:10] | [] | VAR_STR.objects.order_by('-pet__age')[:10] | conala |
8924173-17 | print bold text 'Hello' | print('\x1b[1m' + 'Hello') | [] | print('\x1b[1m' + 'VAR_STR') | conala |
3781851-15 | run python script 'script2.py' from another python script, passing in 1 as an argument | os.system('script2.py 1') | [
"python.library.os#os.system"
] | os.system('script2.py 1') | conala |
18504967-17 | create new column `A_perc` in dataframe `df` with row values equal to the value in column `A` divided by the value in column `sum` | df['A_perc'] = df['A'] / df['sum'] | [] | VAR_STR['VAR_STR'] = VAR_STR['VAR_STR'] / VAR_STR['VAR_STR'] | conala |
11697709-100 | list duplicated elements in two lists `listA` and `listB` | list(set(listA) & set(listB)) | [
"python.library.stdtypes#set",
"python.library.functions#list"
] | list(set(VAR_STR) & set(VAR_STR)) | conala |
10365225-64 | extract digits in a simple way from a python string | map(int, re.findall('\\d+', s)) | [
"python.library.re#re.findall",
"python.library.functions#map"
] | map(int, re.findall('\\d+', s)) | conala |
11430863-98 | find overlapping matches from a string `hello` using regex | re.findall('(?=(\\w\\w))', 'hello') | [
"python.library.re#re.findall"
] | re.findall('(?=(\\w\\w))', 'VAR_STR') | conala |
25991612-67 | Python / Remove special character from string | re.sub('[^a-zA-Z0-9-_*.]', '', my_string) | [
"python.library.re#re.sub"
] | re.sub('[^a-zA-Z0-9-_*.]', '', my_string) | conala |
2597099-85 | Sort list `keys` based on its elements' dot-seperated numbers | keys.sort(key=lambda x: map(int, x.split('.'))) | [
"python.library.functions#map",
"python.library.stdtypes#list.sort",
"python.library.stdtypes#str.split"
] | VAR_STR.sort(key=lambda x: map(int, x.split('.'))) | conala |
2597099-42 | Sort a list of integers `keys` where each value is in string format | keys.sort(key=lambda x: [int(y) for y in x.split('.')]) | [
"python.library.functions#int",
"python.library.stdtypes#list.sort",
"python.library.stdtypes#str.split"
] | VAR_STR.sort(key=lambda x: [int(y) for y in x.split('.')]) | conala |
1874194-65 | get the tuple in list `a_list` that has the largest item in the second index | max_item = max(a_list, key=operator.itemgetter(1)) | [
"python.library.operator#operator.itemgetter",
"python.library.functions#max"
] | max_item = max(VAR_STR, key=operator.itemgetter(1)) | conala |
1874194-25 | find tuple in list of tuples `a_list` with the largest second element | max(a_list, key=operator.itemgetter(1)) | [
"python.library.operator#operator.itemgetter",
"python.library.functions#max"
] | max(VAR_STR, key=operator.itemgetter(1)) | conala |
16196712-48 | wait for shell command `p` evoked by subprocess.Popen to complete | p.wait() | [
"python.library.os#os.wait"
] | VAR_STR.wait() | conala |
42462530-4 | replace white spaces in dataframe `df` with '_' | df.replace(' ', '_', regex=True) | [
"pandas.reference.api.pandas.dataframe.replace"
] | VAR_STR.replace(' ', 'VAR_STR', regex=True) | conala |
30628176-5 | switch positions of each two adjacent characters in string `a` | print(''.join(''.join(i) for i in zip(a2, a1)) + a[-1] if len(a) % 2 else '') | [
"python.library.functions#zip",
"python.library.functions#len",
"python.library.stdtypes#str.join"
] | print(''.join(''.join(i) for i in zip(a2, a1)) + VAR_STR[-1] if len(VAR_STR) %
2 else '') | conala |
4289331-11 | Python: Extract numbers from a string | [int(s) for s in re.findall('\\b\\d+\\b', "he33llo 42 I'm a 32 string 30")] | [
"python.library.re#re.findall",
"python.library.functions#int"
] | [int(s) for s in re.findall('\\b\\d+\\b', "he33llo 42 I'm a 32 string 30")] | conala |
4241757-59 | remove extra white spaces & tabs from a string `s` | """ """.join(s.split()) | [
"python.library.stdtypes#str.join",
"python.library.stdtypes#str.split"
] | """ """.join(VAR_STR.split()) | conala |
4810537-49 | clear terminal screen on windows | os.system('cls') | [
"python.library.os#os.system"
] | os.system('cls') | conala |
4810537-55 | clear the terminal screen in Linux | os.system('clear') | [
"python.library.os#os.system"
] | os.system('clear') | conala |
23306653-53 | get value of key `post code` associated with first index of key `places` of dictionary `data` | print(data['places'][0]['post code']) | [] | print(VAR_STR['VAR_STR'][0]['VAR_STR']) | conala |
4111412-34 | get a list of indices of non zero elements in a list `a` | [i for i, e in enumerate(a) if e != 0] | [
"python.library.functions#enumerate"
] | [i for i, e in enumerate(VAR_STR) if e != 0] | conala |
17589590-99 | Define a list with string values `['a', 'c', 'b', 'obj']` | ['a', 'c', 'b', 'obj'] | [] | [VAR_STR] | conala |
38273353-74 | repeat every character for 7 times in string 'map' | """""".join(map(lambda x: x * 7, 'map')) | [
"python.library.functions#map",
"python.library.stdtypes#str.join"
] | """""".join(VAR_STR(lambda x: x * 7, 'VAR_STR')) | conala |
817087-38 | call a function with argument list `args` | func(*args) | [
"python.library.functools#functools.partial.func"
] | func(*VAR_STR) | conala |
14764126-22 | restart a computer after `900` seconds using subprocess | subprocess.call(['shutdown', '/r', '/t', '900']) | [
"python.library.subprocess#subprocess.call"
] | subprocess.call(['shutdown', '/r', '/t', 'VAR_STR']) | conala |
14764126-20 | shutdown a computer using subprocess | subprocess.call(['shutdown', '/s']) | [
"python.library.subprocess#subprocess.call"
] | subprocess.call(['shutdown', '/s']) | conala |
14764126-37 | abort a computer shutdown using subprocess | subprocess.call(['shutdown', '/a ']) | [
"python.library.subprocess#subprocess.call"
] | subprocess.call(['shutdown', '/a ']) | conala |
14764126-39 | logoff computer having windows operating system using python | subprocess.call(['shutdown', '/l ']) | [
"python.library.subprocess#subprocess.call"
] | subprocess.call(['shutdown', '/l ']) | conala |
14764126-27 | shutdown and restart a computer running windows from script | subprocess.call(['shutdown', '/r']) | [
"python.library.subprocess#subprocess.call"
] | subprocess.call(['shutdown', '/r']) | conala |
6996603-67 | delete an empty directory | os.rmdir() | [
"python.library.os#os.rmdir"
] | os.rmdir() | conala |
6996603-65 | recursively delete all contents in directory `path` | shutil.rmtree(path, ignore_errors=False, onerror=None) | [
"python.library.shutil#shutil.rmtree"
] | shutil.rmtree(VAR_STR, ignore_errors=False, onerror=None) | conala |
6996603-99 | recursively remove folder `name` | os.removedirs(name) | [
"python.library.os#os.removedirs"
] | os.removedirs(VAR_STR) | conala |
18695605-99 | convert pandas DataFrame `df` to a dictionary using `id` field as the key | df.set_index('id').to_dict() | [
"pandas.reference.api.pandas.dataframe.set_index",
"pandas.reference.api.pandas.dataframe.to_dict"
] | VAR_STR.set_index('VAR_STR').to_dict() | conala |
18695605-31 | convert pandas dataframe `df` with fields 'id', 'value' to dictionary | df.set_index('id')['value'].to_dict() | [
"pandas.reference.api.pandas.dataframe.set_index",
"pandas.reference.api.pandas.dataframe.to_dict"
] | VAR_STR.set_index('VAR_STR')['VAR_STR'].to_dict() | conala |
8556076-78 | create list `new_list` containing the last 10 elements of list `my_list` | new_list = my_list[-10:] | [] | VAR_STR = VAR_STR[-10:] | conala |
8556076-43 | get the last 10 elements from a list `my_list` | my_list[-10:] | [] | VAR_STR[-10:] | conala |
33218968-14 | Run 'test2.py' file with python location 'path/to/python' and arguments 'neededArgumetGoHere' as a subprocess | call(['path/to/python', 'test2.py', 'neededArgumetGoHere']) | [
"python.library.subprocess#subprocess.call"
] | call(['VAR_STR', 'VAR_STR', 'VAR_STR']) | conala |
1101508-32 | parse date string '2009/05/13 19:19:30 -0400' using format '%Y/%m/%d %H:%M:%S %z' | datetime.strptime('2009/05/13 19:19:30 -0400', '%Y/%m/%d %H:%M:%S %z') | [
"python.library.datetime#datetime.datetime.strptime"
] | datetime.strptime('VAR_STR', 'VAR_STR') | conala |
34023918-59 | make new column 'C' in panda dataframe by adding values from other columns 'A' and 'B' | df['C'] = df['A'] + df['B'] | [] | df['VAR_STR'] = df['VAR_STR'] + df['VAR_STR'] | 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.