Comparison between datetime and datetime64[ns] in pandas
Question:
I’m writing a program that checks an excel file and if today’s date is in the excel file’s date column, I parse it
I’m using:
cur_date = datetime.today()
for today’s date. I’m checking if today is in the column with:
bool_val = cur_date in df['date'] #evaluates to false
I do know for a fact that today’s date is in the file in question. The dtype of the series is datetime64[ns]
Also, I am only checking the date itself and not the timestamp afterwards, if that matters. I’m doing this to make the timestamp 00:00:00:
cur_date = datetime.strptime(cur_date.strftime('%Y_%m_%d'), '%Y_%m_%d')
And the type of that object after printing is datetime as well
Answers:
You can use
pd.Timestamp('today')
or
pd.to_datetime('today')
But both of those give the date and time for 'now'.
Try this instead:
pd.Timestamp('today').floor('D')
or
pd.to_datetime('today').floor('D')
You could have also passed the datetime object to pandas.to_datetime but I like the other option mroe.
pd.to_datetime(datetime.datetime.today()).floor('D')
Pandas also has a Timedelta object
pd.Timestamp('now').floor('D') + pd.Timedelta(-3, unit='D')
Or you can use the offsets module
pd.Timestamp('now').floor('D') + pd.offsets.Day(-3)
To check for membership, try one of these
cur_date in df['date'].tolist()
Or
df['date'].eq(cur_date).any()
For anyone who also stumbled across this when comparing a dataframe date to a variable date, and this did not exactly answer your question; you can use the code below.
Instead of:
self.df["date"] = pd.to_datetime(self.df["date"])
You can import datetime and then add .dt.date to the end like:
self.df["date"] = pd.to_datetime(self.df["date"]).dt.date
When converting datetime64 type using pd.Timestamp() it is important to note that you should compare it to another timestamp type. (not a datetime.date type)
Convert a date to numpy.datetime64
date = '2022-11-20 00:00:00'
date64 = np.datetime64(date)
Seven days ago – timestamp type
sevenDaysAgoTs = (pd.to_datetime('today')-timedelta(days=7))
convert date64 to Timestamp and see if it was in the last 7 days
print(pd.Timestamp(pd.to_datetime(date64)) >= sevenDaysAgoTs)
I’m writing a program that checks an excel file and if today’s date is in the excel file’s date column, I parse it
I’m using:
cur_date = datetime.today()
for today’s date. I’m checking if today is in the column with:
bool_val = cur_date in df['date'] #evaluates to false
I do know for a fact that today’s date is in the file in question. The dtype of the series is datetime64[ns]
Also, I am only checking the date itself and not the timestamp afterwards, if that matters. I’m doing this to make the timestamp 00:00:00:
cur_date = datetime.strptime(cur_date.strftime('%Y_%m_%d'), '%Y_%m_%d')
And the type of that object after printing is datetime as well
You can use
pd.Timestamp('today')
or
pd.to_datetime('today')
But both of those give the date and time for 'now'.
Try this instead:
pd.Timestamp('today').floor('D')
or
pd.to_datetime('today').floor('D')
You could have also passed the datetime object to pandas.to_datetime but I like the other option mroe.
pd.to_datetime(datetime.datetime.today()).floor('D')
Pandas also has a Timedelta object
pd.Timestamp('now').floor('D') + pd.Timedelta(-3, unit='D')
Or you can use the offsets module
pd.Timestamp('now').floor('D') + pd.offsets.Day(-3)
To check for membership, try one of these
cur_date in df['date'].tolist()
Or
df['date'].eq(cur_date).any()
For anyone who also stumbled across this when comparing a dataframe date to a variable date, and this did not exactly answer your question; you can use the code below.
Instead of:
self.df["date"] = pd.to_datetime(self.df["date"])
You can import datetime and then add .dt.date to the end like:
self.df["date"] = pd.to_datetime(self.df["date"]).dt.date
When converting datetime64 type using pd.Timestamp() it is important to note that you should compare it to another timestamp type. (not a datetime.date type)
Convert a date to numpy.datetime64
date = '2022-11-20 00:00:00'
date64 = np.datetime64(date)
Seven days ago – timestamp type
sevenDaysAgoTs = (pd.to_datetime('today')-timedelta(days=7))
convert date64 to Timestamp and see if it was in the last 7 days
print(pd.Timestamp(pd.to_datetime(date64)) >= sevenDaysAgoTs)