【发布时间】:2020-04-10 22:21:44
【问题描述】:
我正在编写一个函数,它返回一个字典,其中数据集中所有引用的创建日期用作键,作为值,它指定由函数 do_get_citations_per_year 返回的两个项目的元组。
def do_get_citations_per_year(data, year):
result = tuple()
my_ocan['creation'] = pd.DatetimeIndex(my_ocan['creation']).year
len_citations = len(my_ocan.loc[my_ocan["creation"] == year, "creation"])
timespan = my_ocan.loc[my_ocan["creation"] == year, "timespan"].fillna(0).mean()
result = (len_citations, round(timespan))
return result
def do_get_citations_all_years(data):
mydict = {}
s = set(my_ocan.creation)
print(s)
for year in s:
mydict[year] = do_get_citations_per_year(data, year)
#print(mydict)
return mydict
我不断收到错误消息:
(32, 240)
{2016, 2017, 2018, 2013, 2015}
File "/Users/lisa/Desktop/yopy/execution_example.py", line 28, in <module>
print(my_ocan.get_citations_all_years())
File "/Users/lisa/Desktop/yopy/ocan.py", line 35, in get_citations_all_years
return do_get_citations_all_years(self.data)
File "/Users/lisa/Desktop/yopy/lisa.py", line 113, in do_get_citations_all_years
mydict[year] = do_get_citations_per_year(data, year)
File "/Users/lisa/Desktop/yopy/lisa.py", line 103, in do_get_citations_per_year
result = (len_citations, round(timespan))
ValueError: cannot convert float NaN to integer
Process finished with exit code 1
更新:为了提供一个工作示例,我在这里发布了其他函数,特别是处理我的数据帧 (my_ocan)do_process_citation_data(f_path) 和我的解析函数 parse_timespan 的函数:
def do_process_citation_data(f_path):
global my_ocan
my_ocan = pd.read_csv(f_path, names=['oci', 'citing', 'cited', 'creation', 'timespan', 'journal_sc', 'author_sc'],
parse_dates=['creation', 'timespan'])
my_ocan = my_ocan.iloc[1:] # to remove the first row
my_ocan['creation'] = pd.to_datetime(my_ocan['creation'], format="%Y-%m-%d", yearfirst=True)
my_ocan['timespan'] = my_ocan['timespan'].map(parse_timespan)
print(my_ocan['timespan'])
return my_ocan
#print(my_ocan['timespan'])
timespan_regex = re.compile(r'P(?:(\d+)Y)?(?:(\d+)M)?(?:(\d+)D)?')
def parse_timespan(timespan):
# check if the input is a valid timespan
if not timespan or 'P' not in timespan:
return None
# check if timespan is negative and skip initial 'P' literal
curr_idx = 0
is_negative = timespan.startswith('-')
if is_negative:
curr_idx = 1
# extract years, months and days with the regex
match = timespan_regex.match(timespan[curr_idx:])
years = int(match.group(1) or 0)
months = int(match.group(2) or 0)
days = int(match.group(3) or 0)
timespan_days = years * 365 + months * 30 + days
return timespan_days if not is_negative else -timespan_days
当我打印 my_ocan['timespan']
我明白了:
1 486.0
2 1080.0
3 730.0
4 824.0
5 365.0
6 0.0
...
我认为问题是 0.0
如何解决这个浮点 NaN 到整数的问题?
提前谢谢你!
【问题讨论】:
-
能否为您的数据提供一个最小的工作示例?
-
@Fourier 我刚刚用一个工作示例更新了我的问题:)