本文整理匯總了Python中datetime.datetime.month方法的典型用法代碼示例。如果您正苦於以下問題：Python datetime.month方法的具體用法？Python datetime.month怎麽用？Python datetime.month使用的例子？那麽, 這裏精選的方法代碼示例或許可以為您提供幫助。您也可以進一步了解該方法所在類datetime.datetime的用法示例。
在下文中一共展示了datetime.month方法的5個代碼示例，這些例子默認根據受歡迎程度排序。您可以為喜歡或者感覺有用的代碼點讚，您的評價將有助於係統推薦出更棒的Python代碼示例。
示例1: extract_month
# 需要導入模塊: from datetime import datetime [as 別名]
# 或者: from datetime.datetime import month [as 別名]
def extract_month(utc_timestamp):
"""
Extracts month from utc timestamp string.
"""
datetime = parser.parse(utc_timestamp)
return '{0}-{1}'.format(datetime.year, datetime.month) 示例2: extract_day
# 需要導入模塊: from datetime import datetime [as 別名]
# 或者: from datetime.datetime import month [as 別名]
def extract_day(utc_timestamp):
"""
Extracts day from utc timestamp string.
"""
datetime = parser.parse(utc_timestamp)
return '{0}-{1}-{2}'.format(datetime.year, datetime.month, datetime.day) 示例3: _for_commits_monthly
# 需要導入模塊: from datetime import datetime [as 別名]
# 或者: from datetime.datetime import month [as 別名]
def _for_commits_monthly(self, commits):
"""
Returns number of commits per month for the given commits.
"""
dates = [get_month(extract_month(commit.get_committer_date())) for commit in commits
if get_year(commit.get_committer_date()) == self.current_year]
return {mn: dates.count(mn) if mn in dates else 0 for mn in range(1, 13)} 示例4: test_sort_datetimelike
# 需要導入模塊: from datetime import datetime [as 別名]
# 或者: from datetime.datetime import month [as 別名]
def test_sort_datetimelike():
# GH10505
# use same data as test_groupby_sort_categorical, which category is
# corresponding to datetime.month
df = DataFrame({'dt': [datetime(2011, 7, 1), datetime(2011, 7, 1),
datetime(2011, 2, 1), datetime(2011, 5, 1),
datetime(2011, 2, 1), datetime(2011, 1, 1),
datetime(2011, 5, 1)],
'foo': [10, 8, 5, 6, 4, 1, 7],
'bar': [10, 20, 30, 40, 50, 60, 70]},
columns=['dt', 'foo', 'bar'])
# ordered=True
df['dt'] = Categorical(df['dt'], ordered=True)
index = [datetime(2011, 1, 1), datetime(2011, 2, 1),
datetime(2011, 5, 1), datetime(2011, 7, 1)]
result_sort = DataFrame(
[[1, 60], [5, 30], [6, 40], [10, 10]], columns=['foo', 'bar'])
result_sort.index = CategoricalIndex(index, name='dt', ordered=True)
index = [datetime(2011, 7, 1), datetime(2011, 2, 1),
datetime(2011, 5, 1), datetime(2011, 1, 1)]
result_nosort = DataFrame([[10, 10], [5, 30], [6, 40], [1, 60]],
columns=['foo', 'bar'])
result_nosort.index = CategoricalIndex(index, categories=index,
name='dt', ordered=True)
col = 'dt'
assert_frame_equal(
result_sort, df.groupby(col, sort=True, observed=False).first())
# when categories is ordered, group is ordered by category's order
assert_frame_equal(
result_sort, df.groupby(col, sort=False, observed=False).first())
# ordered = False
df['dt'] = Categorical(df['dt'], ordered=False)
index = [datetime(2011, 1, 1), datetime(2011, 2, 1),
datetime(2011, 5, 1), datetime(2011, 7, 1)]
result_sort = DataFrame(
[[1, 60], [5, 30], [6, 40], [10, 10]], columns=['foo', 'bar'])
result_sort.index = CategoricalIndex(index, name='dt')
index = [datetime(2011, 7, 1), datetime(2011, 2, 1),
datetime(2011, 5, 1), datetime(2011, 1, 1)]
result_nosort = DataFrame([[10, 10], [5, 30], [6, 40], [1, 60]],
columns=['foo', 'bar'])
result_nosort.index = CategoricalIndex(index, categories=index,
name='dt')
col = 'dt'
assert_frame_equal(
result_sort, df.groupby(col, sort=True, observed=False).first())
assert_frame_equal(
result_nosort, df.groupby(col, sort=False, observed=False).first()) 示例5: test_groupby_sort_categorical_datetimelike
# 需要導入模塊: from datetime import datetime [as 別名]
# 或者: from datetime.datetime import month [as 別名]
def test_groupby_sort_categorical_datetimelike(self):
# GH10505
# use same data as test_groupby_sort_categorical, which category is
# corresponding to datetime.month
df = DataFrame({'dt': [datetime(2011, 7, 1), datetime(2011, 7, 1),
datetime(2011, 2, 1), datetime(2011, 5, 1),
datetime(2011, 2, 1), datetime(2011, 1, 1),
datetime(2011, 5, 1)],
'foo': [10, 8, 5, 6, 4, 1, 7],
'bar': [10, 20, 30, 40, 50, 60, 70]},
columns=['dt', 'foo', 'bar'])
# ordered=True
df['dt'] = Categorical(df['dt'], ordered=True)
index = [datetime(2011, 1, 1), datetime(2011, 2, 1),
datetime(2011, 5, 1), datetime(2011, 7, 1)]
result_sort = DataFrame(
[[1, 60], [5, 30], [6, 40], [10, 10]], columns=['foo', 'bar'])
result_sort.index = CategoricalIndex(index, name='dt', ordered=True)
index = [datetime(2011, 7, 1), datetime(2011, 2, 1),
datetime(2011, 5, 1), datetime(2011, 1, 1)]
result_nosort = DataFrame([[10, 10], [5, 30], [6, 40], [1, 60]],
columns=['foo', 'bar'])
result_nosort.index = CategoricalIndex(index, categories=index,
name='dt', ordered=True)
col = 'dt'
assert_frame_equal(result_sort, df.groupby(col, sort=True).first())
# when categories is ordered, group is ordered by category's order
assert_frame_equal(result_sort, df.groupby(col, sort=False).first())
# ordered = False
df['dt'] = Categorical(df['dt'], ordered=False)
index = [datetime(2011, 1, 1), datetime(2011, 2, 1),
datetime(2011, 5, 1), datetime(2011, 7, 1)]
result_sort = DataFrame(
[[1, 60], [5, 30], [6, 40], [10, 10]], columns=['foo', 'bar'])
result_sort.index = CategoricalIndex(index, name='dt')
index = [datetime(2011, 7, 1), datetime(2011, 2, 1),
datetime(2011, 5, 1), datetime(2011, 1, 1)]
result_nosort = DataFrame([[10, 10], [5, 30], [6, 40], [1, 60]],
columns=['foo', 'bar'])
result_nosort.index = CategoricalIndex(index, categories=index,
name='dt')
col = 'dt'
assert_frame_equal(result_sort, df.groupby(col, sort=True).first())
assert_frame_equal(result_nosort, df.groupby(col, sort=False).first())