message_type stringclasses 2 values | message stringlengths 2 232 ⌀ | message_id int64 0 1 | conversation_id int64 0 2.38k |
|---|---|---|---|
instruction | return the column for value 38.15 in dataframe `df` | 0 | 150 |
output | df.ix[:, (df.loc[0] == 38.15)].columns | 1 | 150 |
instruction | merge 2 dataframes `df1` and `df2` with same values in a column 'revenue' with and index 'date' | 0 | 151 |
output | df2['revenue'] = df2.CET.map(df1.set_index('date')['revenue']) | 1 | 151 |
instruction | load a json data `json_string` into variable `json_data` | 0 | 152 |
output | json_data = json.loads(json_string) | 1 | 152 |
instruction | convert radians 1 to degrees | 0 | 153 |
output | math.cos(math.radians(1)) | 1 | 153 |
instruction | count the number of integers in list `a` | 0 | 154 |
output | sum(isinstance(x, int) for x in a) | 1 | 154 |
instruction | replacing '\u200b' with '*' in a string using regular expressions | 0 | 155 |
output | 'used\u200b'.replace('\u200b', '*') | 1 | 155 |
instruction | run function 'SudsMove' simultaneously | 0 | 156 |
output | threading.Thread(target=SudsMove).start() | 1 | 156 |
instruction | sum of squares values in a list `l` | 0 | 157 |
output | sum(i * i for i in l) | 1 | 157 |
instruction | calculate the sum of the squares of each value in list `l` | 0 | 158 |
output | sum(map(lambda x: x * x, l)) | 1 | 158 |
instruction | Create a dictionary `d` from list `iterable` | 0 | 159 |
output | d = dict(((key, value) for (key, value) in iterable)) | 1 | 159 |
instruction | Create a dictionary `d` from list `iterable` | 0 | 160 |
output | d = {key: value for (key, value) in iterable} | 1 | 160 |
instruction | Create a dictionary `d` from list of key value pairs `iterable` | 0 | 161 |
output | d = {k: v for (k, v) in iterable} | 1 | 161 |
instruction | round off entries in dataframe `df` column `Alabama_exp` to two decimal places, and entries in column `Credit_exp` to three decimal places | 0 | 162 |
output | df.round({'Alabama_exp': 2, 'Credit_exp': 3}) | 1 | 162 |
instruction | Make function `WRITEFUNCTION` output nothing in curl `p` | 0 | 163 |
output | p.setopt(pycurl.WRITEFUNCTION, lambda x: None) | 1 | 163 |
instruction | return a random word from a word list 'words' | 0 | 164 |
output | print(random.choice(words)) | 1 | 164 |
instruction | Find a max value of the key `count` in a nested dictionary `d` | 0 | 165 |
output | max(d, key=lambda x: d[x]['count']) | 1 | 165 |
instruction | get list of string elements in string `data` delimited by commas, putting `0` in place of empty strings | 0 | 166 |
output | [(int(x) if x else 0) for x in data.split(',')] | 1 | 166 |
instruction | split string `s` into a list of strings based on ',' then replace empty strings with zero | 0 | 167 |
output | """,""".join(x or '0' for x in s.split(',')) | 1 | 167 |
instruction | regular expression match nothing | 0 | 168 |
output | re.compile('$^') | 1 | 168 |
instruction | regular expression syntax for not to match anything | 0 | 169 |
output | re.compile('.\\A|.\\A*|.\\A+') | 1 | 169 |
instruction | create a regular expression object with a pattern that will match nothing | 0 | 170 |
output | re.compile('a^') | 1 | 170 |
instruction | drop all columns in dataframe `df` that holds a maximum value bigger than 0 | 0 | 171 |
output | df.columns[df.max() > 0] | 1 | 171 |
instruction | check if date `yourdatetime` is equal to today's date | 0 | 172 |
output | yourdatetime.date() == datetime.today().date() | 1 | 172 |
instruction | print bold text 'Hello' | 0 | 173 |
output | print('\x1b[1m' + 'Hello') | 1 | 173 |
instruction | remove 20 symbols in front of '.' in string 'unique12345678901234567890.mkv' | 0 | 174 |
output | re.sub('.{20}(.mkv)', '\\1', 'unique12345678901234567890.mkv') | 1 | 174 |
instruction | Define a list with string values `['a', 'c', 'b', 'obj']` | 0 | 175 |
output | ['a', 'c', 'b', 'obj'] | 1 | 175 |
instruction | substitute multiple whitespace with single whitespace in string `mystring` | 0 | 176 |
output | """ """.join(mystring.split()) | 1 | 176 |
instruction | print a floating point number 2.345e-67 without any truncation | 0 | 177 |
output | print('{:.100f}'.format(2.345e-67)) | 1 | 177 |
instruction | Check if key 'key1' in `dict` | 0 | 178 |
output | ('key1' in dict) | 1 | 178 |
instruction | Check if key 'a' in `d` | 0 | 179 |
output | ('a' in d) | 1 | 179 |
instruction | Check if key 'c' in `d` | 0 | 180 |
output | ('c' in d) | 1 | 180 |
instruction | Check if a given key 'key1' exists in dictionary `dict` | 0 | 181 |
output | if ('key1' in dict):
pass | 1 | 181 |
instruction | Check if a given key `key` exists in dictionary `d` | 0 | 182 |
output | if (key in d):
pass | 1 | 182 |
instruction | create a django query for a list of values `1, 4, 7` | 0 | 183 |
output | Blog.objects.filter(pk__in=[1, 4, 7]) | 1 | 183 |
instruction | read a binary file 'test/test.pdf' | 0 | 184 |
output | f = open('test/test.pdf', 'rb') | 1 | 184 |
instruction | insert ' ' between every three digit before '.' and replace ',' with '.' in 12345678.46 | 0 | 185 |
output | format(12345678.46, ',').replace(',', ' ').replace('.', ',') | 1 | 185 |
instruction | Join pandas data frame `frame_1` and `frame_2` with left join by `county_ID` and right join by `countyid` | 0 | 186 |
output | pd.merge(frame_1, frame_2, left_on='county_ID', right_on='countyid') | 1 | 186 |
instruction | calculate ratio of sparsity in a numpy array `a` | 0 | 187 |
output | np.isnan(a).sum() / np.prod(a.shape) | 1 | 187 |
instruction | reverse sort items in default dictionary `cityPopulation` by the third item in each key's list of values | 0 | 188 |
output | sorted(iter(cityPopulation.items()), key=lambda k_v: k_v[1][2], reverse=True) | 1 | 188 |
instruction | Sort dictionary `u` in ascending order based on second elements of its values | 0 | 189 |
output | sorted(list(u.items()), key=lambda v: v[1]) | 1 | 189 |
instruction | reverse sort dictionary `d` based on its values | 0 | 190 |
output | sorted(list(d.items()), key=lambda k_v: k_v[1], reverse=True) | 1 | 190 |
instruction | sorting a defaultdict `d` by value | 0 | 191 |
output | sorted(list(d.items()), key=lambda k_v: k_v[1]) | 1 | 191 |
instruction | open a file 'bundled-resource.jpg' in the same directory as a python script | 0 | 192 |
output | f = open(os.path.join(__location__, 'bundled-resource.jpg')) | 1 | 192 |
instruction | open the file 'words.txt' in 'rU' mode | 0 | 193 |
output | f = open('words.txt', 'rU') | 1 | 193 |
instruction | divide the values with same keys of two dictionary `d1` and `d2` | 0 | 194 |
output | {k: (float(d2[k]) / d1[k]) for k in d2} | 1 | 194 |
instruction | divide the value for each key `k` in dict `d2` by the value for the same key `k` in dict `d1` | 0 | 195 |
output | {k: (d2[k] / d1[k]) for k in list(d1.keys()) & d2} | 1 | 195 |
instruction | divide values associated with each key in dictionary `d1` from values associated with the same key in dictionary `d2` | 0 | 196 |
output | dict((k, float(d2[k]) / d1[k]) for k in d2) | 1 | 196 |
instruction | write dataframe `df` to csv file `filename` with dates formatted as yearmonthday `%Y%m%d` | 0 | 197 |
output | df.to_csv(filename, date_format='%Y%m%d') | 1 | 197 |
instruction | remove a key 'key' from a dictionary `my_dict` | 0 | 198 |
output | my_dict.pop('key', None) | 1 | 198 |
instruction | replace NaN values in array `a` with zeros | 0 | 199 |
output | b = np.where(np.isnan(a), 0, a) | 1 | 199 |
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