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print the number of occurences of not `none` in a list `lst` in Python 2 | print(len([x for x in lst if x is not None])) |
lookup dictionary key `key1` in Django template `json` | {{json.key1}} |
emove duplicates from list `myset` | mynewlist = list(myset) |
get unique values from the list `['a', 'b', 'c', 'd']` | set(['a', 'b', 'c', 'd']) |
et size of `figure` to landscape A4 i.e. `11.69, 8.27` inche | figure(figsize=(11.69, 8.27)) |
get every thing after last `/` | url.rsplit('/', 1) |
get everything after last slash in a url stored in variable 'url' | url.rsplit('/', 1)[-1] |
pen file '5_1.txt' in directory `direct` | x_file = open(os.path.join(direct, '5_1.txt'), 'r') |
eate a list with the characters of a string `5+6` | list('5+6') |
atenate a list of numpy arrays `input_list` together into a flattened list of value | np.concatenate(input_list).ravel().tolist() |
vert dictionary `dict` into a flat l | print([y for x in list(dict.items()) for y in x]) |
Convert a dictionary `dict` into a list with key and values as list items. | [y for x in list(dict.items()) for y in x] |
get a random record from model 'MyModel' using django's orm | MyModel.objects.order_by('?').first() |
hange current working directory to directory 'chapter3' | os.chdir('chapter3') |
hange current working directory | os.chdir('C:\\Users\\username\\Desktop\\headfirstpython\\chapter3') |
hange current working directory | os.chdir('.\\chapter3') |
eate a flat dictionary by summing values associated with similar keys in each dictionary of list `dictlist` | dict((key, sum(d[key] for d in dictList)) for key in dictList[0]) |
pandas data frame `df` using values from columns `c1` and `c2` in ascending order | df.sort(['c1', 'c2'], ascending=[True, True]) |
Converting string lists `s` to float l | floats = [float(x) for x in s.split()] |
Converting string lists `s` to float l | floats = map(float, s.split()) |
et labels `[1, 2, 3, 4, 5]` on axis X in plot `plt` | plt.xticks([1, 2, 3, 4, 5]) |
ead line by line from std | for line in fileinput.input():
pass |
ead line by line from std | for line in sys.stdin:
pass |
heck if string `one` exists in the values of dictionary `d` | 'one' in list(d.values()) |
Check if value 'one' is among the values of dictionary `d` | 'one' in iter(d.values()) |
all parent class `Instructor` of child class constructor | super(Instructor, self).__init__(name, year) |
eate a dictionary using two lists`x` and `y` | dict(zip(x, y)) |
a list of dictionaries `a` by dictionary values in descending order | sorted(a, key=lambda i: list(i.values())[0], reverse=True) |
g a list of dictionary `a` by values in descending order | sorted(a, key=dict.values, reverse=True) |
Use multiple groupby and agg operations `sum`, `count`, `std` for pandas data frame `df` | df.groupby(level=0).agg(['sum', 'count', 'std']) |
for a dictionary `a`, set default value for key `somekey` as list and append value `bob` in that key | a.setdefault('somekey', []).append('bob') |
m values in list of dictionaries `example_list` with key 'gold' | sum(item['gold'] for item in example_list) |
get a sum of all values from key `gold` in a list of dictionary `example_list` | sum([item['gold'] for item in example_list]) |
Get all the values in key `gold` summed from a list of dictionary `myLIst` | sum(item['gold'] for item in myLIst) |
writing string 'text to write\n' to file `f` | f.write('text to write\n') |
Write a string `My String` to a file `file` including new line character | file.write('My String\n') |
find consecutive segments from a column 'A' in a pandas data frame 'df' | df.reset_index().groupby('A')['index'].apply(np.array) |
get a relative path of file 'my_file' into variable `fn` | fn = os.path.join(os.path.dirname(__file__), 'my_file') |
etrieve an element from a set `s` without removing | e = next(iter(s)) |
execute a command in the command prompt to list directory contents of the c drive `c:\\' | os.system('dir c:\\') |
Make a auto scrolled window to the end of the list in gtk | self.treeview.connect('size-allocate', self.treeview_changed) |
heck if 3 is inside list `[1, 2, 3]` | 3 in [1, 2, 3] |
Represent DateTime object '10/05/2012' with format '%d/%m/%Y' into format '%Y%m%d' | datetime.datetime.strptime('10/05/2012', '%d/%m/%Y').strftime('%Y-%m-%d') |
vert a string literal `s` with values `\\` to raw string literal | s = s.replace('\\', '\\\\') |
get output of script `proc` | print(proc.communicate()[0]) |
eate a pandas data frame from list of nested dictionaries `my_list` | pd.concat([pd.DataFrame(l) for l in my_list], axis=1).T |
delete all columns in DataFrame `df` that do not hold a nonzero value in its record | df.loc[:, ((df != 0).any(axis=0))] |
a multidimensional array `a` by column with index 1 | sorted(a, key=lambda x: x[1]) |
plit string `s` to list conversion by ',' | [x.strip() for x in s.split(',')] |
Get a list of items in the list `container` with attribute equal to `value` | items = [item for item in container if item.attribute == value] |
eate a file 'filename' with each tuple in the list `mylist` written to a line | open('filename', 'w').write('\n'.join('%s %s' % x for x in mylist)) |
Get multiple matched strings using regex pattern `(?:review: )?(http://url.com/(\\d+))\\s?` | pattern = re.compile('(?:review: )?(http://url.com/(\\d+))\\s?', re.IGNORECASE) |
ead a text file 'very_Important.txt' into a string variable `str` | str = open('very_Important.txt', 'r').read() |
Return values for column `C` after group by on column `A` and `B` in dataframe `df` | df.groupby(['A', 'B'])['C'].unique() |
ead file `fname` line by line into a list `content` | with open(fname) as f:
content = f.readlines() |
ead file 'filename' line by line into a list `lines` | with open('filename') as f:
lines = f.readlines() |
ead file 'filename' line by line into a list `lines` | lines = [line.rstrip('\n') for line in open('filename')] |
ead file file.txt line by line into a list `array` | with open('file.txt', 'r') as ins:
array = []
for line in ins:
array.append(line) |
vert the dataframe column 'col' from string types to datetime type | df['col'] = pd.to_datetime(df['col']) |
get a list of the keys in each dictionary in a dictionary of dictionaries `foo` | [k for d in list(foo.values()) for k in d] |
get user input using message 'Enter name here: ' and insert it to the first placeholder in string 'Hello, {0}, how do you do?' | print('Hello, {0}, how do you do?'.format(input('Enter name here: '))) |
eate 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: How can I use the apply() function for a single column? | df['a'] = df['a'].apply(lambda x: x + 1) |
get the platform OS name | platform.system() |
list `a` in ascending order based on its elements' float value | a = sorted(a, key=lambda x: float(x)) |
finding words in string `s` after keyword 'name' | re.search('name (.*)', s) |
Find all records from collection `collection` without extracting mongo id `_id` | db.collection.find({}, {'_id': False}) |
Get all the second values from a list of lists `A` | [row[1] for row in A] |
extract first column from a multidimensional array `a` | [row[0] for row in a] |
list `['10', '3', '2']` in ascending order based on the integer value of its eleme | sorted(['10', '3', '2'], key=int) |
heck if file `filename` is descendant of directory '/the/dir/' | os.path.commonprefix(['/the/dir/', os.path.realpath(filename)]) == '/the/dir/' |
heck if any element of list `substring_list` are in string `string` | any(substring in string for substring in substring_list) |
pandas dataframe from a list of tuple | df = pandas.DataFrame(data, columns=['R_Number', 'C_Number', 'Avg', 'Std']) |
find and replace 2nd occurrence of word 'cat' by 'Bull' in a sentence 's' | re.sub('^((?:(?!cat).)*cat(?:(?!cat).)*)cat', '\\1Bull', s) |
find and replace 2nd occurrence of word 'cat' by 'Bull' in a sentence 's' | re.sub('^((.*?cat.*?){1})cat', '\\1Bull', s) |
list of strings in list `the_list` by integer suffix | sorted(the_list, key=lambda k: int(k.split('_')[1])) |
list of strings `the_list` by integer suffix before _ | sorted(the_list, key=lambda x: int(x.split('_')[1])) |
ke a list of lists in which each list `g` are the elements from list `test` which have the same characters up to the first `_` character | [list(g) for _, g in itertools.groupby(test, lambda x: x.split('_')[0])] |
w to group similar items in a list? | [list(g) for _, g in itertools.groupby(test, lambda x: x.partition('_')[0])] |
Load the url `http://www.google.com` in selenium webdriver `driver` | driver.get('http://www.google.com') |
g python's datetime module, get the year that utc11 is currently | (datetime.datetime.utcnow() - datetime.timedelta(hours=11)).year |
Get the difference between two lists `[1, 2, 2, 2, 3]` and `[1, 2]` that may have duplicate value | Counter([1, 2, 2, 2, 3]) - Counter([1, 2]) |
emove tags from a string `mystring` | re.sub('<[^>]*>', '', mystring) |
encode string `data` as `hex` | data.encode('hex') |
filter `Users` by field `userprofile` with level greater than or equal to `0` | User.objects.filter(userprofile__level__gte=0) |
BeautifulSoup find a tag whose id ends with string 'para' | soup.findAll(id=re.compile('para$')) |
elect `div` tags whose `id`s begin with `value_xxx_c_1_f_8_a_` | soup.select('div[id^="value_xxx_c_1_f_8_a_"]') |
delete an item `thing` in a list `some_list` if it ex | cleaned_list = [x for x in some_list if x is not thing] |
print Please enter something: to console, and read user input to `var` | var = input('Please enter something: ') |
ppend 4 to list `foo` | foo.append(4) |
ppend a list [8, 7] to list `foo` | foo.append([8, 7]) |
ert 77 to index 2 of list `x` | x.insert(2, 77) |
emove white space padding around a saved image `test.png` in matplotlib | plt.savefig('test.png', bbox_inches='tight') |
atenate lists `listone` and `listtwo` | (listone + listtwo) |
erate items in lists `listone` and `listtwo` | for item in itertools.chain(listone, listtwo):
pass |
eate dataframe `males` containing data of dataframe `df` where column `Gender` is equal to 'Male' and column `Year` is equal to 2014 | males = df[(df[Gender] == 'Male') & (df[Year] == 2014)] |
print backslash | print('\\') |
eplace '' in pandas dataframe `df` with `np.nan` | df.replace('-', np.nan) |
delete column 'column_name' from dataframe `df` | df = df.drop('column_name', 1) |
delete 1st, 2nd and 4th columns from dataframe `df` | df.drop(df.columns[[0, 1, 3]], axis=1) |