How can I convert my datetime column in pandas all to the same timezoneConvert pandas timezone-aware DateTimeIndex to naive timestamp, but in certain timezoneConvert datetime columns to a different timezone pandasHow to return only the Date from a SQL Server DateTime datatypeHow can I safely create a nested directory?Converting string into datetimeHow can I make a time delay in Python?How do I list all files of a directory?How do I convert a String to an int in Java?Renaming columns in pandasDelete column from pandas DataFrameHow to iterate over rows in a DataFrame in Pandas?Select rows from a DataFrame based on values in a column in pandas
Open subspaces of CW complexes
Set orthographic view using python?
Contours of a national emergency in the United States
What stops you from using fixed income in developing countries?
What's difference between place Linked and Embedded in Photoshop?
Where does learning new skills fit into Agile?
Disk usage of integer column vs boolean column in Postgres
74S vs 74LS ICs
Does a Mace of Disruption's Frightened effect override undead immunity to the Frightened condition?
Why is the winner of Pow different everytime?
Beginner to guitar playing - where should I begin?
How does Mercy remove conditions?
Is the internet in Madagascar faster than in UK?
Retroactively modifying humans for Earth?
can you help me identify this aircraft?
Why is a statement like 1 + n *= 3 allowed in Ruby?
Why did my folder names end up like this, and how can I fix this using a script?
Why is the UK so keen to remove the "backstop" when their leadership seems to think that no border will be needed in Northern Ireland?
50-move rule: only the last 50 or any consecutive 50?
Billiard balls collision
Papers on arXiv solving the same problem at the same time
Did Dr. Hannibal Lecter like Clarice or was he attracted to her?
Can I get a PhD for developing an educational software?
How to prevent a hosting company from accessing a VM's encryption keys?
How can I convert my datetime column in pandas all to the same timezone
Convert pandas timezone-aware DateTimeIndex to naive timestamp, but in certain timezoneConvert datetime columns to a different timezone pandasHow to return only the Date from a SQL Server DateTime datatypeHow can I safely create a nested directory?Converting string into datetimeHow can I make a time delay in Python?How do I list all files of a directory?How do I convert a String to an int in Java?Renaming columns in pandasDelete column from pandas DataFrameHow to iterate over rows in a DataFrame in Pandas?Select rows from a DataFrame based on values in a column in pandas
.everyoneloves__top-leaderboard:empty,.everyoneloves__mid-leaderboard:empty,.everyoneloves__bot-mid-leaderboard:empty margin-bottom:0;
I have a dataframe with a DataTime column (with Timezone in different formats). It appears like timezone is UTC but I want to convert the column to pd.to_datetime and that is failing. That is problem #1. Since that fails I cannot do any datetime operations on the time period such as group the column by date / figure out the days / group by hour of the day and so on. Here's my dataframe df_res
DateTime
2017-11-02 19:49:28-07:00
2017-11-27 07:32:22-08:00
2017-12-27 17:01:15-08:00
OUTPUT for the command
df_res["DateTime"] = df_res["DateTime"].dt.tz_convert('America/New_York')
AttributeError: Can only use .dt accessor with datetimelike values
WHen I convert to datetime
df_res['DateTime'] = pd.to_datetime(df_res['DateTime'])
ValueError: Tz-aware datetime.datetime cannot be converted to datetime64 unless utc=True
I feel I am going around in circles. I need to convert the column to datetime in order to perform operations & in order to do that I need to have them all the same timezone but I cannot have the same timezone unless it is a datetime object so how can I best approach this.
I did refer to previous postings but they seem to convert to datetime as easily as possible:
Convert datetime columns to a different timezone pandas
Convert pandas timezone-aware DateTimeIndex to naive timestamp, but in certain timezone
python pandas datetime type-conversion timezone
edited Mar 28 at 0:57
CezarySzulc
7956 silver badges17 bronze badges
asked Mar 27 at 19:57
py_noobpy_noob
64 bronze badges
add a comment |
I have a dataframe with a DataTime column (with Timezone in different formats). It appears like timezone is UTC but I want to convert the column to pd.to_datetime and that is failing. That is problem #1. Since that fails I cannot do any datetime operations on the time period such as group the column by date / figure out the days / group by hour of the day and so on. Here's my dataframe df_res
DateTime
2017-11-02 19:49:28-07:00
2017-11-27 07:32:22-08:00
2017-12-27 17:01:15-08:00
OUTPUT for the command
df_res["DateTime"] = df_res["DateTime"].dt.tz_convert('America/New_York')
AttributeError: Can only use .dt accessor with datetimelike values
WHen I convert to datetime
df_res['DateTime'] = pd.to_datetime(df_res['DateTime'])
ValueError: Tz-aware datetime.datetime cannot be converted to datetime64 unless utc=True
I feel I am going around in circles. I need to convert the column to datetime in order to perform operations & in order to do that I need to have them all the same timezone but I cannot have the same timezone unless it is a datetime object so how can I best approach this.
I did refer to previous postings but they seem to convert to datetime as easily as possible:
Convert datetime columns to a different timezone pandas
Convert pandas timezone-aware DateTimeIndex to naive timestamp, but in certain timezone
python pandas datetime type-conversion timezone
edited Mar 28 at 0:57
CezarySzulc
7956 silver badges17 bronze badges
asked Mar 27 at 19:57
py_noobpy_noob
64 bronze badges
How are you creating the "DateTime" column values in the first place?
– benvc
Mar 27 at 22:12
I extract the datetime field from a json file
– py_noob
Mar 28 at 1:38
add a comment |
I have a dataframe with a DataTime column (with Timezone in different formats). It appears like timezone is UTC but I want to convert the column to pd.to_datetime and that is failing. That is problem #1. Since that fails I cannot do any datetime operations on the time period such as group the column by date / figure out the days / group by hour of the day and so on. Here's my dataframe df_res
DateTime
2017-11-02 19:49:28-07:00
2017-11-27 07:32:22-08:00
2017-12-27 17:01:15-08:00
OUTPUT for the command
df_res["DateTime"] = df_res["DateTime"].dt.tz_convert('America/New_York')
AttributeError: Can only use .dt accessor with datetimelike values
WHen I convert to datetime
df_res['DateTime'] = pd.to_datetime(df_res['DateTime'])
ValueError: Tz-aware datetime.datetime cannot be converted to datetime64 unless utc=True
I feel I am going around in circles. I need to convert the column to datetime in order to perform operations & in order to do that I need to have them all the same timezone but I cannot have the same timezone unless it is a datetime object so how can I best approach this.
I did refer to previous postings but they seem to convert to datetime as easily as possible:
Convert datetime columns to a different timezone pandas
Convert pandas timezone-aware DateTimeIndex to naive timestamp, but in certain timezone
python pandas datetime type-conversion timezone
edited Mar 28 at 0:57
CezarySzulc
7956 silver badges17 bronze badges
asked Mar 27 at 19:57
py_noobpy_noob
64 bronze badges
I have a dataframe with a DataTime column (with Timezone in different formats). It appears like timezone is UTC but I want to convert the column to pd.to_datetime and that is failing. That is problem #1. Since that fails I cannot do any datetime operations on the time period such as group the column by date / figure out the days / group by hour of the day and so on. Here's my dataframe df_res
DateTime
2017-11-02 19:49:28-07:00
2017-11-27 07:32:22-08:00
2017-12-27 17:01:15-08:00
OUTPUT for the command
df_res["DateTime"] = df_res["DateTime"].dt.tz_convert('America/New_York')
AttributeError: Can only use .dt accessor with datetimelike values
WHen I convert to datetime
df_res['DateTime'] = pd.to_datetime(df_res['DateTime'])
ValueError: Tz-aware datetime.datetime cannot be converted to datetime64 unless utc=True
I feel I am going around in circles. I need to convert the column to datetime in order to perform operations & in order to do that I need to have them all the same timezone but I cannot have the same timezone unless it is a datetime object so how can I best approach this.
I did refer to previous postings but they seem to convert to datetime as easily as possible:
Convert datetime columns to a different timezone pandas
Convert pandas timezone-aware DateTimeIndex to naive timestamp, but in certain timezone
python pandas datetime type-conversion timezone
python pandas datetime type-conversion timezone
edited Mar 28 at 0:57
CezarySzulc
7956 silver badges17 bronze badges
asked Mar 27 at 19:57
py_noobpy_noob
64 bronze badges
edited Mar 28 at 0:57
CezarySzulc
7956 silver badges17 bronze badges
asked Mar 27 at 19:57
py_noobpy_noob
64 bronze badges
edited Mar 28 at 0:57
CezarySzulc
7956 silver badges17 bronze badges
edited Mar 28 at 0:57
CezarySzulc
7956 silver badges17 bronze badges
edited Mar 28 at 0:57
CezarySzulc
7956 silver badges17 bronze badges
7956 silver badges17 bronze badges
asked Mar 27 at 19:57
py_noobpy_noob
64 bronze badges
asked Mar 27 at 19:57
py_noobpy_noob
64 bronze badges
asked Mar 27 at 19:57
py_noobpy_noob
64 bronze badges
64 bronze badges
How are you creating the "DateTime" column values in the first place?
– benvc
Mar 27 at 22:12
I extract the datetime field from a json file
– py_noob
Mar 28 at 1:38
add a comment |
How are you creating the "DateTime" column values in the first place?
– benvc
Mar 27 at 22:12
I extract the datetime field from a json file
– py_noob
Mar 28 at 1:38
How are you creating the "DateTime" column values in the first place?
– benvc
Mar 27 at 22:12
How are you creating the "DateTime" column values in the first place?
– benvc
Mar 27 at 22:12
I extract the datetime field from a json file
– py_noob
Mar 28 at 1:38
I extract the datetime field from a json file
– py_noob
Mar 28 at 1:38
add a comment |
1 Answer
1
active
oldest
votes
You can check this:
df = pd.DataFrame(
'time': [
'2017-11-02 19:49:28-08:00',
'2017-11-27 07:32:22-07:00',
'2017-12-27 17:01:15-07:00'
]
)
df['time'] = pd.to_datetime(df['time'])
df['time'].apply(lambda x: pd.to_datetime(x).tz_localize('US/Eastern'))
0 2017-11-03 03:49:28-04:00
1 2017-11-27 14:32:22-05:00
2 2017-12-28 00:01:15-05:00
Name: time, dtype: datetime64[ns, US/Eastern]
answered Mar 27 at 20:44
CezarySzulcCezarySzulc
7956 silver badges17 bronze badges
Thanks .. And what if my dataframe has over a 10k+ datetime entries. The DateTime is of typeobjecttoo and I need to convert them all?
– py_noob
Mar 28 at 1:36
add a comment |
Your Answer
StackExchange.ifUsing("editor", function ()
StackExchange.using("externalEditor", function ()
StackExchange.using("snippets", function ()
StackExchange.snippets.init();
);
);
, "code-snippets");
StackExchange.ready(function()
var channelOptions =
tags: "".split(" "),
id: "1"
;
initTagRenderer("".split(" "), "".split(" "), channelOptions);
StackExchange.using("externalEditor", function()
// Have to fire editor after snippets, if snippets enabled
if (StackExchange.settings.snippets.snippetsEnabled)
StackExchange.using("snippets", function()
createEditor();
);
else
createEditor();
);
function createEditor()
StackExchange.prepareEditor(
heartbeatType: 'answer',
autoActivateHeartbeat: false,
convertImagesToLinks: true,
noModals: true,
showLowRepImageUploadWarning: true,
reputationToPostImages: 10,
bindNavPrevention: true,
postfix: "",
imageUploader:
brandingHtml: "Powered by u003ca class="icon-imgur-white" href="https://imgur.com/"u003eu003c/au003e",
contentPolicyHtml: "User contributions licensed under u003ca href="https://creativecommons.org/licenses/by-sa/3.0/"u003ecc by-sa 3.0 with attribution requiredu003c/au003e u003ca href="https://stackoverflow.com/legal/content-policy"u003e(content policy)u003c/au003e",
allowUrls: true
,
onDemand: true,
discardSelector: ".discard-answer"
,immediatelyShowMarkdownHelp:true
);
);
Sign up or log in
StackExchange.ready(function ()
StackExchange.helpers.onClickDraftSave('#login-link');
);
Sign up using Google
Sign up using Facebook
Sign up using Email and Password
Post as a guest
Required, but never shown
StackExchange.ready(
function ()
StackExchange.openid.initPostLogin('.new-post-login', 'https%3a%2f%2fstackoverflow.com%2fquestions%2f55385497%2fhow-can-i-convert-my-datetime-column-in-pandas-all-to-the-same-timezone%23new-answer', 'question_page');
);
Post as a guest
Required, but never shown
1 Answer
1
active
oldest
votes
1 Answer
1
active
oldest
votes
active
oldest
votes
active
oldest
votes
You can check this:
df = pd.DataFrame(
'time': [
'2017-11-02 19:49:28-08:00',
'2017-11-27 07:32:22-07:00',
'2017-12-27 17:01:15-07:00'
]
)
df['time'] = pd.to_datetime(df['time'])
df['time'].apply(lambda x: pd.to_datetime(x).tz_localize('US/Eastern'))
0 2017-11-03 03:49:28-04:00
1 2017-11-27 14:32:22-05:00
2 2017-12-28 00:01:15-05:00
Name: time, dtype: datetime64[ns, US/Eastern]
answered Mar 27 at 20:44
CezarySzulcCezarySzulc
7956 silver badges17 bronze badges
Thanks .. And what if my dataframe has over a 10k+ datetime entries. The DateTime is of typeobjecttoo and I need to convert them all?
– py_noob
Mar 28 at 1:36
add a comment |
You can check this:
df = pd.DataFrame(
'time': [
'2017-11-02 19:49:28-08:00',
'2017-11-27 07:32:22-07:00',
'2017-12-27 17:01:15-07:00'
]
)
df['time'] = pd.to_datetime(df['time'])
df['time'].apply(lambda x: pd.to_datetime(x).tz_localize('US/Eastern'))
0 2017-11-03 03:49:28-04:00
1 2017-11-27 14:32:22-05:00
2 2017-12-28 00:01:15-05:00
Name: time, dtype: datetime64[ns, US/Eastern]
answered Mar 27 at 20:44
CezarySzulcCezarySzulc
7956 silver badges17 bronze badges
Thanks .. And what if my dataframe has over a 10k+ datetime entries. The DateTime is of typeobjecttoo and I need to convert them all?
– py_noob
Mar 28 at 1:36
add a comment |
You can check this:
df = pd.DataFrame(
'time': [
'2017-11-02 19:49:28-08:00',
'2017-11-27 07:32:22-07:00',
'2017-12-27 17:01:15-07:00'
]
)
df['time'] = pd.to_datetime(df['time'])
df['time'].apply(lambda x: pd.to_datetime(x).tz_localize('US/Eastern'))
0 2017-11-03 03:49:28-04:00
1 2017-11-27 14:32:22-05:00
2 2017-12-28 00:01:15-05:00
Name: time, dtype: datetime64[ns, US/Eastern]
answered Mar 27 at 20:44
CezarySzulcCezarySzulc
7956 silver badges17 bronze badges
You can check this:
df = pd.DataFrame(
'time': [
'2017-11-02 19:49:28-08:00',
'2017-11-27 07:32:22-07:00',
'2017-12-27 17:01:15-07:00'
]
)
df['time'] = pd.to_datetime(df['time'])
df['time'].apply(lambda x: pd.to_datetime(x).tz_localize('US/Eastern'))
0 2017-11-03 03:49:28-04:00
1 2017-11-27 14:32:22-05:00
2 2017-12-28 00:01:15-05:00
Name: time, dtype: datetime64[ns, US/Eastern]
answered Mar 27 at 20:44
CezarySzulcCezarySzulc
7956 silver badges17 bronze badges
answered Mar 27 at 20:44
CezarySzulcCezarySzulc
7956 silver badges17 bronze badges
answered Mar 27 at 20:44
CezarySzulcCezarySzulc
7956 silver badges17 bronze badges
answered Mar 27 at 20:44
CezarySzulcCezarySzulc
7956 silver badges17 bronze badges
7956 silver badges17 bronze badges
Thanks .. And what if my dataframe has over a 10k+ datetime entries. The DateTime is of typeobjecttoo and I need to convert them all?
– py_noob
Mar 28 at 1:36
add a comment |
Thanks .. And what if my dataframe has over a 10k+ datetime entries. The DateTime is of typeobjecttoo and I need to convert them all?
– py_noob
Mar 28 at 1:36
Thanks .. And what if my dataframe has over a 10k+ datetime entries. The DateTime is of type
object too and I need to convert them all?– py_noob
Mar 28 at 1:36
Thanks .. And what if my dataframe has over a 10k+ datetime entries. The DateTime is of type
object too and I need to convert them all?– py_noob
Mar 28 at 1:36
add a comment |
Got a question that you can’t ask on public Stack Overflow? Learn more about sharing private information with Stack Overflow for Teams.
Got a question that you can’t ask on public Stack Overflow? Learn more about sharing private information with Stack Overflow for Teams.
Thanks for contributing an answer to Stack Overflow!
- Please be sure to answer the question. Provide details and share your research!
But avoid …
- Asking for help, clarification, or responding to other answers.
- Making statements based on opinion; back them up with references or personal experience.
To learn more, see our tips on writing great answers.
Sign up or log in
StackExchange.ready(function ()
StackExchange.helpers.onClickDraftSave('#login-link');
);
Sign up using Google
Sign up using Facebook
Sign up using Email and Password
Post as a guest
Required, but never shown
StackExchange.ready(
function ()
StackExchange.openid.initPostLogin('.new-post-login', 'https%3a%2f%2fstackoverflow.com%2fquestions%2f55385497%2fhow-can-i-convert-my-datetime-column-in-pandas-all-to-the-same-timezone%23new-answer', 'question_page');
);
Post as a guest
Required, but never shown
Sign up or log in
StackExchange.ready(function ()
StackExchange.helpers.onClickDraftSave('#login-link');
);
Sign up using Google
Sign up using Facebook
Sign up using Email and Password
Post as a guest
Required, but never shown
Sign up or log in
StackExchange.ready(function ()
StackExchange.helpers.onClickDraftSave('#login-link');
);
Sign up using Google
Sign up using Facebook
Sign up using Email and Password
Post as a guest
Required, but never shown
Sign up or log in
StackExchange.ready(function ()
StackExchange.helpers.onClickDraftSave('#login-link');
);
Sign up using Google
Sign up using Facebook
Sign up using Email and Password
Sign up using Google
Sign up using Facebook
Sign up using Email and Password
Post as a guest
Required, but never shown
Required, but never shown
Required, but never shown
Required, but never shown
Required, but never shown
Required, but never shown
Required, but never shown
Required, but never shown
Required, but never shown
How are you creating the "DateTime" column values in the first place?
– benvc
Mar 27 at 22:12
I extract the datetime field from a json file
– py_noob
Mar 28 at 1:38