df.index
DatetimeIndex(['2019-01-25 17:00:00', '2019-01-25 17:01:00',,
'2019-01-25 17:08:00', '2019-01-25 17:09:00',
...
'2019-02-15 07:44:00', '2019-02-15 07:45:00',
'2019-02-15 07:52:00', '2019-02-15 07:53:00'],
I want to save figures in the loop using plt.savefig and I'm trying to name the figure as the index for that hour of which the plot is.
I'm looping for everyhour
for hour, i in df.groupby('index_hour'):
plt.savefig(hour+'.png',dpi=300,bbox_inches='tight')
TypeError: unsupported operand type(s) for +: 'Timestamp' and 'str'
hour
Timestamp('2019-01-25 17:00:00')
Hour is the final name of the .png file that I'm trying to get. Thanks.
Use the strftime method of datetime objects:
timestamps = df.index.strftime("%Y-%m-%d %H:%M:%S")
If you just want the hour, then you can simply get that (as an int) via an attribute of the datetime index:
hours = df.index.hour
Refer to this for information on how to use the datetime string formatting.
Related
In my django project i have to convert a str variable passed as a date ("2021-11-10") to a datetime with timezone object for execute an ORM filter on a DateTime field.
In my db values are stored as for example:
2021-11-11 01:18:04.200149+00
i try:
# test date
df = "2021-11-11"
df = df + " 00:00:00+00"
start_d = datetime.strptime(df, '%Y-%m-%d %H:%M:%S%Z')
but i get an error due to an error about str format and datetime representation (are different)
How can i convert a single date string into a datetimeobject with timezone stated from midnight of the date value?
So many thanks in advance
It's not the way to datetime.strptime.
Read a little bit more here
I believe it will help you.
you should implement month as str and without "-".
good luck
I am looking for a way to plot temperature over datetime. The problem is that I have datetime as date in the format [(datetime.date(2020, 4, 3),), (datetime.date(2020, 4, 3),)] and a corresponding timedelta in the format [(datetime.timedelta(0, 27751),), (datetime.timedelta(0, 27761),)]. A datetime.date / datetime.timedelta object in a tuple in a list.
Can someone help me to find a propper solution with getting a datetime from the date and the timedelta?
Thanks in advance!
Convert timedelta object to time object:
convert timedelta object to time object
And then use combine method to receive datetime object:
Convert date to datetime in Python
I have a pandas dataset with this structure:
Date datetime64[ns]
Events int64
Location object
Day float64
I've used the following code to get the date of the first occurrence for location "A":
start_date = df[df['Location'] == 'A'][df.Events != 0].iat[0,0]
I now want to update all of the records after the start_date with the number of days since the start_date, where Day = df.Date - start_date.
I tried this code:
df.loc[df.Location == country, 'Day'] = (df.Date - start_date).days
However, that code returns an error:
AttributeError: 'Series' object has no attribute 'days'
The problem seems to be that the code recognizes df.Date as an object instead of a datetime. Anyone have any ideas on what is causing this problem?
Try, you need to add the .dt accessor.
df.loc[df.Location == country, 'Day'] = (df.Date - start_date).dt.days
I have a datframe that stores some information from text files, this information gives me details about my execution jobs.
I store all this information in a dataframe called "df_tmp". On that dataframe I have a column "end_Date" where I want to store the end date from the file that is the last line of my file but if in the dataframe I don't have any value I want to store the current_time.
Imagine that the information from my file is on the following variable:
string_from_my_file = 'Execution time at 2019/10/14 08:06:44'
What I need is:
In case of my manual file don't have any date on the last line I want to store the current_time.
For that I am trying with this code:
now = dt.datetime.now()
current_time = now.strftime('%H:%M:%S')
df_tmp['end_date'] = df_tmp['end_date'].fillna(current_time).apply(lambda x: x.strftime('%Y-%m-%d %H:%M:%S') if not pd.isnull(x) else pd.to_datetime(re.search("([0-9]{4}\/[0-9]{2}\/[0-9]{2}\ [0-9]{2}\:[0-9]{2}\:[0-9]{2})", str(df_tmp['string_from_my_file']))[0]))
However, it gives me the following error:
builtins.AttributeError: 'str' object has no attribute 'strftime'
What I am doing wrong?
Thanks
Try this:
df_tmp['end_date'] = df_tmp['end_date'].fillna(current_time).apply(lambda x: pd.to_datetime(x).strftime('%Y-%m-%d %H:%M:%S') if not pd.isnull(x) else pd.to_datetime(re.search("([0-9]{4}\/[0-9]{2}\/[0-9]{2}\ [0-9]{2}\:[0-9]{2}\:[0-9]{2})", str(df_tmp['string_from_my_file']))[0]))
In this part, lambda x: pd.to_datetime(x).strftime('%Y-%m-%d %H:%M:%S', need to change x to datetime to apply strftime().
Probable reason for your error:
Even if end_date column is of type datetime, but you are filling that column with values having str type. This is changing data type of end_date column.
I have a pandas dataframe with columns containing start and stop times in this format: 2016-01-01 00:00:00
I would like to convert these times to datetime objects so that I can subtract one from the other to compute total duration. I'm using the following:
import datetime
df = df['start_time'] =
df['start_time'].apply(lambda x:datetime.datetime.strptime(x,'%Y/%m/%d/%T %I:%M:%S %p'))
However, I have the following ValueError:
ValueError: 'T' is a bad directive in format '%Y/%m/%d/%T %I:%M:%S %p'
This would convert the column into datetime64 dtype. Then you could process whatever you need using that column.
df['start_time'] = pd.to_datetime(df['start_time'], format="%Y-%m-%d %H:%M:%S")
Also if you want to avoid explicitly specifying datetime format you can use the following:
df['start_time'] = pd.to_datetime(df['start_time'], infer_datetime_format=True)
Simpliest is use to_datetime:
df['start_time'] = pd.to_datetime(df['start_time'])