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get value at index `[2, 0]` in dataframe `df` | df.iloc[2, 0] |
hange the font size on plot `matplotlib` to 22 | matplotlib.rcParams.update({'font.size': 22}) |
verting dictionary `d` into a dataframe `pd` with keys as data for column 'Date' and the corresponding values as data for column 'DateValue' | pd.DataFrame(list(d.items()), columns=['Date', 'DateValue']) |
eate a dataframe containing the multiplication of elementwise in dataframe `df` and dataframe `df2` using index name and column labels of dataframe `df` | pd.DataFrame(df.values * df2.values, columns=df.columns, index=df.index) |
extract floating number from string 'Current Level: 13.4 db.' | re.findall('\\d+\\.\\d+', 'Current Level: 13.4 db.') |
extract floating point numbers from a string 'Current Level: 13.2 db or 14.2 or 3' | re.findall('[-+]?\\d*\\.\\d+|\\d+', 'Current Level: -13.2 db or 14.2 or 3') |
pair each element in list `it` 3 times into a tuple | zip(it, it, it) |
lowercase a python dataframe string in column 'x' if it has missing values in dataframe `df` | df['x'].str.lower() |
ppend 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}) |
Concat a list of strings `lst` using string formatting | """""".join(lst) |
m values greater than 0 in dictionary `d` | sum(v for v in list(d.values()) if v > 0) |
flask application `app` in debug mode. | app.run(debug=True) |
drop rows whose index value in list `[1, 3]` in dataframe `df` | df.drop(df.index[[1, 3]], inplace=True) |
eplace nan values in a pandas data frame with the average of colum | df.apply(lambda x: x.fillna(x.mean()), axis=0) |
extract attribute `my_attr` from each object in list `my_list` | [o.my_attr for o in my_list] |
python get time stamp on file `file` in '%m/%d/%Y' form | time.strftime('%m/%d/%Y', time.gmtime(os.path.getmtime(file))) |
heck if dictionary `subset` is a subset of dictionary `superset` | all(item in list(superset.items()) for item in list(subset.items())) |
Convert integer elements in list `wordids` to string | [str(wi) for wi in wordids] |
Reset the indexes of a pandas data frame | df2 = df.reset_index() |
format datetime in `dt` as string in format `'%m/%d/%Y` | dt.strftime('%m/%d/%Y') |
format floating point number `TotalAmount` to be rounded off to two decimal places and have a comma thousands' seperator | print('Total cost is: ${:,.2f}'.format(TotalAmount)) |
m the values in each row of every two adjacent columns in dataframe `df` | df.groupby(np.arange(len(df.columns)) // 2 + 1, axis=1).sum().add_prefix('s') |
eate list `randomList` with 10 random floating point numbers between 0.0 and 1.0 | randomList = [random.random() for _ in range(10)] |
find href value that has string 'follow?page' inside | print(soup.find('a', href=re.compile('.*follow\\?page.*'))) |
mmediately see output of print statement that doesn't end in a newline | sys.stdout.flush() |
get a random key `country` and value `capital` form a dictionary `d` | country, capital = random.choice(list(d.items())) |
plit string `Word to Split` into a list of character | list('Word to Split') |
Create a list containing words that contain vowel letter followed by the same vowel in file 'file.text' | [w for w in open('file.txt') if not re.search('[aeiou]{2}', w)] |
Validate IP address using Regex | pat = re.compile('^\\d{1,3}\\.\\d{1,3}\\.\\d{1,3}\\.\\d{1,3}$') |
execute file 'filename.py' | exec(compile(open('filename.py').read(), 'filename.py', 'exec')) |
SQLAlchemy count the number of rows with distinct values in column `name` of table `Tag` | session.query(Tag).distinct(Tag.name).group_by(Tag.name).count() |
emove null columns in a dataframe `df` | df = df.dropna(axis=1, how='all') |
heck if all lists in list `L` have three elements of integer 1 | all(x.count(1) == 3 for x in L) |
Get a list comparing two lists of tuples `l1` and `l2` if any first value in `l1` matches with first value in `l2` | [x[0] for x in l1 if any(x[0] == y[0] for y in l2)] |
lear the textbox `text` in tkinter | tex.delete('1.0', END) |
Convert long int `myNumber` into date and time represented in the the string format '%Y%m%d %H:%M:%S' | datetime.datetime.fromtimestamp(myNumber).strftime('%Y-%m-%d %H:%M:%S') |
Spawn a process to run python script `myscript.py` in C++ | system('python myscript.py') |
a list `your_list` of class objects by their values for the attribute `anniversary_score` | your_list.sort(key=operator.attrgetter('anniversary_score')) |
list `your_list` by the `anniversary_score` attribute of each objec | your_list.sort(key=lambda x: x.anniversary_score) |
vert a tensor with list of constants `[1, 2, 3]` into a numpy array in tensorflow | print(type(tf.Session().run(tf.constant([1, 2, 3])))) |
vert list `a` from being consecutive sequences of tuples into a single sequence of eleme | list(itertools.chain(*a)) |
Set value for key `a` in dict `count` to `0` if key `a` does not exist or if value is `none` | count.setdefault('a', 0) |
Do group by on `cluster` column in `df` and get its me | df.groupby(['cluster']).mean() |
get number in list `myList` closest in value to number `myNumber` | min(myList, key=lambda x: abs(x - myNumber)) |
heck if any of the items in `search` appear in `string` | any(x in string for x in search) |
earch for occurrences of regex pattern `pattern` in string `url` | print(pattern.search(url).group(1)) |
factorize all string values in dataframe `s` into flo | (s.factorize()[0] + 1).astype('float') |
Get a list `C` by subtracting values in one list `B` from corresponding values in another list `A` | C = [(a - b) for a, b in zip(A, B)] |
derive the week start for the given week number and year ‘2011, 4, 0’ | datetime.datetime.strptime('2011, 4, 0', '%Y, %U, %w') |
vert a list of strings `['1', '1', '1']` to a list of number | map(int, ['1', '-1', '1']) |
eate datetime object from 16sep2012 | datetime.datetime.strptime('16Sep2012', '%d%b%Y') |
pdate fields in Django model `Book` with arguments in dictionary `d` where primary key is equal to `pk` | Book.objects.filter(pk=pk).update(**d) |
pdate the fields in django model `Book` using dictionary `d` | Book.objects.create(**d) |
print a digit `your_number` with exactly 2 digits after decimal | print('{0:.2f}'.format(your_number)) |
generate a 12digit random number | random.randint(100000000000, 999999999999) |
generate a random 12digit number | int(''.join(str(random.randint(0, 9)) for _ in range(12))) |
generate a random 12digit number | """""".join(str(random.randint(0, 9)) for _ in range(12)) |
generate a 12digit random number | '%0.12d' % random.randint(0, 999999999999) |
emove specific elements in a numpy array `a` | numpy.delete(a, index) |
list `trial_list` based on values of dictionary `trail_dict` | sorted(trial_list, key=lambda x: trial_dict[x]) |
ead a single character from std | sys.stdin.read(1) |
get a list of characters in string `x` matching regex pattern `pattern` | print(re.findall(pattern, x)) |
get the context of a search by keyword 'My keywords' in beautifulsoup `soup` | k = soup.find(text=re.compile('My keywords')).parent.text |
vert rows in pandas data frame `df` into l | df.apply(lambda x: x.tolist(), axis=1) |
vert a 1d `A` array to a 2d array `B` | B = np.reshape(A, (-1, 2)) |
app `app` on host '192.168.0.58' and port 9000 in Flask | app.run(host='192.168.0.58', port=9000, debug=False) |
encode unicode string '\xc5\xc4\xd6' to utf8 code | print('\xc5\xc4\xd6'.encode('UTF8')) |
get the first element of each tuple from a list of tuples `G` | [x[0] for x in G] |
egular expression matching all but 'aa' and 'bb' for string `string` | re.findall('-(?!aa-|bb-)([^-]+)', string) |
egular expression matching all but 'aa' and 'bb' | re.findall('-(?!aa|bb)([^-]+)', string) |
emove false entries from a dictionary `hand` | {k: v for k, v in list(hand.items()) if v} |
Get a dictionary from a dictionary `hand` where the values are prese | dict((k, v) for k, v in hand.items() if v) |
list `L` based on the value of variable 'resultType' for each object in list `L` | sorted(L, key=operator.itemgetter('resultType')) |
a list of objects `s` by a member variable 'resultType' | s.sort(key=operator.attrgetter('resultType')) |
a list of objects 'somelist' where the object has member number variable `resultType` | somelist.sort(key=lambda x: x.resultType) |
join multiple dataframes `d1`, `d2`, and `d3` on column 'name' | df1.merge(df2, on='name').merge(df3, on='name') |
generate random Decimal | decimal.Decimal(random.randrange(10000)) / 100 |
list all files of a directory `mypath` | onlyfiles = [f for f in listdir(mypath) if isfile(join(mypath, f))] |
list all files of a directory `mypath` | f = []
for (dirpath, dirnames, filenames) in walk(mypath):
f.extend(filenames)
break |
list all .txt files of a directory /home/adam/ | print(glob.glob('/home/adam/*.txt')) |
list all files of a directory somedirectory | os.listdir('somedirectory') |
execute sql query 'INSERT INTO table VALUES(%s,%s,%s,%s,%s,%s,%s,%s,%s)' with all parameters in list `tup` | cur.executemany('INSERT INTO table VALUES(%s,%s,%s,%s,%s,%s,%s,%s,%s)', tup) |
get keys with same value in dictionary `d` | print([key for key in d if d[key] == 1]) |
get keys with same value in dictionary `d` | print([key for key, value in d.items() if value == 1]) |
Get keys from a dictionary 'd' where the value is '1'. | print([key for key, value in list(d.items()) if value == 1]) |
eate list of 'size' empty string | strs = ['' for x in range(size)] |
generate pdf file `output_filename` from markdown file `input_filename` | with open(input_filename, 'r') as f:
html_text = markdown(f.read(), output_format='html4')
pdfkit.from_string(html_text, output_filename) |
emove duplicate dict in list `l` | [dict(t) for t in set([tuple(d.items()) for d in l])] |
Set time zone `Europe/Istanbul` in Django | TIME_ZONE = 'Europe/Istanbul' |
ppend `date` to list value of `key` in dictionary `dates_dict`, or create key `key` with value `date` in a list if it does not ex | dates_dict.setdefault(key, []).append(date) |
Group the values from django model `Article` with group by value `pub_date` and annotate by `title` | Article.objects.values('pub_date').annotate(article_count=Count('title')) |
lear Tkinter Canvas `canvas` | canvas.delete('all') |
alize a pandas series object `s` with columns `['A', 'B', 'A1R', 'B2', 'AABB4']` | s = pd.Series(['A', 'B', 'A1R', 'B2', 'AABB4']) |
None | datetime.datetime.strptime('2007-03-04T21:08:12', '%Y-%m-%dT%H:%M:%S') |
list `a` using the first dimension of the element as the key to list `b` | a.sort(key=lambda x: b.index(x[0])) |
w to sort a list according to another list? | a.sort(key=lambda x_y: b.index(x_y[0])) |
Save plot `plt` as png file 'filename.png' | plt.savefig('filename.png') |
Save matplotlib graph to image file `filename.png` at a resolution of `300 dpi` | plt.savefig('filename.png', dpi=300) |
get output from process `p1` | p1.communicate()[0] |
w to get output of exe in python script? | output = subprocess.Popen(['mycmd', 'myarg'], stdout=PIPE).communicate()[0] |