concatenating a new column and renaming it
1
I'm trying to generate a new column based on another (hour column from the time column). The problem is that after concatenating, it's getting the same name ("time").
Moreover, when I try to change one, the other changes as well.
Why is that?
Here's the code
df['time'] = pd.to_datetime(df['time'])
hour_col = pd.Series(df['time']).copy()
hour_col = hour_col.apply(lambda t: t.hour)
df = pd.concat([df, hour_col], axis=1)
Name change:
df = df.rename(columns={ df.columns[3]: "hour" })
python-3.x pandas
asked Nov 24 '18 at 13:19
yasecoyaseco
42413
add a comment |
1
I'm trying to generate a new column based on another (hour column from the time column). The problem is that after concatenating, it's getting the same name ("time").
Moreover, when I try to change one, the other changes as well.
Why is that?
Here's the code
df['time'] = pd.to_datetime(df['time'])
hour_col = pd.Series(df['time']).copy()
hour_col = hour_col.apply(lambda t: t.hour)
df = pd.concat([df, hour_col], axis=1)
Name change:
df = df.rename(columns={ df.columns[3]: "hour" })
python-3.x pandas
asked Nov 24 '18 at 13:19
yasecoyaseco
42413
add a comment |
1
1
1
I'm trying to generate a new column based on another (hour column from the time column). The problem is that after concatenating, it's getting the same name ("time").
Moreover, when I try to change one, the other changes as well.
Why is that?
Here's the code
df['time'] = pd.to_datetime(df['time'])
hour_col = pd.Series(df['time']).copy()
hour_col = hour_col.apply(lambda t: t.hour)
df = pd.concat([df, hour_col], axis=1)
Name change:
df = df.rename(columns={ df.columns[3]: "hour" })
python-3.x pandas
asked Nov 24 '18 at 13:19
yasecoyaseco
42413
I'm trying to generate a new column based on another (hour column from the time column). The problem is that after concatenating, it's getting the same name ("time").
Moreover, when I try to change one, the other changes as well.
Why is that?
Here's the code
df['time'] = pd.to_datetime(df['time'])
hour_col = pd.Series(df['time']).copy()
hour_col = hour_col.apply(lambda t: t.hour)
df = pd.concat([df, hour_col], axis=1)
Name change:
df = df.rename(columns={ df.columns[3]: "hour" })
python-3.x pandas
python-3.x pandas
asked Nov 24 '18 at 13:19
yasecoyaseco
42413
asked Nov 24 '18 at 13:19
yasecoyaseco
42413
asked Nov 24 '18 at 13:19
yasecoyaseco
42413
asked Nov 24 '18 at 13:19
yasecoyaseco
42413
asked Nov 24 '18 at 13:19
yasecoyaseco
42413
42413
add a comment |
add a comment |
1 Answer
1
active
oldest
votes
2
Use dt.hour:
df['time'] = pd.to_datetime(df['time'])
df['hours'] = df['time'].dt.hour
But if really need your solution only rename column, converting to Series is not necessary, because each column of DataFrame is Series after selecting (print (type(df['time']))):
df = pd.DataFrame({'time':['10:20:30','20:03:04']})
df['time'] = pd.to_datetime(df['time'])
hour_col = df['time'].rename('hour')
hour_col = hour_col.apply(lambda t: t.hour)
df = pd.concat([df, hour_col], axis=1)
print (df)
time hour
0 2018-11-24 10:20:30 10
1 2018-11-24 20:03:04 20
If want replace columns by position (e.g. because duplicated values and rename change both names like mentioned @Gla Avineri in comment) use:
df = pd.DataFrame({'time':['10:20:30','20:03:04'],
'a':[2,3],
'b':[-4,5]})
df['time'] = pd.to_datetime(df['time'])
hour_col = df['time']
hour_col = hour_col.apply(lambda t: t.hour)
df = pd.concat([df, hour_col], axis=1)
#converting to list because columns are immutable
cols = df.columns.tolist()
#set 4th value
cols[3] = 'hour'
#assign back
df.columns = cols
print (df)
time a b hour
0 2018-11-24 10:20:30 2 -4 10
1 2018-11-24 20:03:04 3 5 20
answered Nov 24 '18 at 13:21
jezraeljezrael
341k25296368
I'll try that, thanks. Out of curiosity, what is the problem with my code? Why is it behaving like that?
– yaseco
Nov 24 '18 at 13:23
I would guess that in your code, when you copy the time series of the dataframe, you are also copying it's name - "time". Than when you concatenate the new series to the dataframe, it appears with the name "time". When you userename, you ask to renamedf.columns[3]to "hour". Butdf.columns[3]holds the value "time", so what you basically wrote there isrename(columns={"time": "hour"}). As i explained earlier your df had 2 columns named "time" up to this point, so now they will both be changed to "hour".
– Gal Avineri
Nov 24 '18 at 14:13
@GalAvineri - Yes, I agree - Added solution for this.
– jezrael
Nov 24 '18 at 14:58
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
});
}
});
draft saved
draft discarded
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%2f53458550%2fconcatenating-a-new-column-and-renaming-it%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
2
Use dt.hour:
df['time'] = pd.to_datetime(df['time'])
df['hours'] = df['time'].dt.hour
But if really need your solution only rename column, converting to Series is not necessary, because each column of DataFrame is Series after selecting (print (type(df['time']))):
df = pd.DataFrame({'time':['10:20:30','20:03:04']})
df['time'] = pd.to_datetime(df['time'])
hour_col = df['time'].rename('hour')
hour_col = hour_col.apply(lambda t: t.hour)
df = pd.concat([df, hour_col], axis=1)
print (df)
time hour
0 2018-11-24 10:20:30 10
1 2018-11-24 20:03:04 20
If want replace columns by position (e.g. because duplicated values and rename change both names like mentioned @Gla Avineri in comment) use:
df = pd.DataFrame({'time':['10:20:30','20:03:04'],
'a':[2,3],
'b':[-4,5]})
df['time'] = pd.to_datetime(df['time'])
hour_col = df['time']
hour_col = hour_col.apply(lambda t: t.hour)
df = pd.concat([df, hour_col], axis=1)
#converting to list because columns are immutable
cols = df.columns.tolist()
#set 4th value
cols[3] = 'hour'
#assign back
df.columns = cols
print (df)
time a b hour
0 2018-11-24 10:20:30 2 -4 10
1 2018-11-24 20:03:04 3 5 20
answered Nov 24 '18 at 13:21
jezraeljezrael
341k25296368
I'll try that, thanks. Out of curiosity, what is the problem with my code? Why is it behaving like that?
– yaseco
Nov 24 '18 at 13:23
I would guess that in your code, when you copy the time series of the dataframe, you are also copying it's name - "time". Than when you concatenate the new series to the dataframe, it appears with the name "time". When you userename, you ask to renamedf.columns[3]to "hour". Butdf.columns[3]holds the value "time", so what you basically wrote there isrename(columns={"time": "hour"}). As i explained earlier your df had 2 columns named "time" up to this point, so now they will both be changed to "hour".
– Gal Avineri
Nov 24 '18 at 14:13
@GalAvineri - Yes, I agree - Added solution for this.
– jezrael
Nov 24 '18 at 14:58
add a comment |
2
Use dt.hour:
df['time'] = pd.to_datetime(df['time'])
df['hours'] = df['time'].dt.hour
But if really need your solution only rename column, converting to Series is not necessary, because each column of DataFrame is Series after selecting (print (type(df['time']))):
df = pd.DataFrame({'time':['10:20:30','20:03:04']})
df['time'] = pd.to_datetime(df['time'])
hour_col = df['time'].rename('hour')
hour_col = hour_col.apply(lambda t: t.hour)
df = pd.concat([df, hour_col], axis=1)
print (df)
time hour
0 2018-11-24 10:20:30 10
1 2018-11-24 20:03:04 20
If want replace columns by position (e.g. because duplicated values and rename change both names like mentioned @Gla Avineri in comment) use:
df = pd.DataFrame({'time':['10:20:30','20:03:04'],
'a':[2,3],
'b':[-4,5]})
df['time'] = pd.to_datetime(df['time'])
hour_col = df['time']
hour_col = hour_col.apply(lambda t: t.hour)
df = pd.concat([df, hour_col], axis=1)
#converting to list because columns are immutable
cols = df.columns.tolist()
#set 4th value
cols[3] = 'hour'
#assign back
df.columns = cols
print (df)
time a b hour
0 2018-11-24 10:20:30 2 -4 10
1 2018-11-24 20:03:04 3 5 20
answered Nov 24 '18 at 13:21
jezraeljezrael
341k25296368
I'll try that, thanks. Out of curiosity, what is the problem with my code? Why is it behaving like that?
– yaseco
Nov 24 '18 at 13:23
I would guess that in your code, when you copy the time series of the dataframe, you are also copying it's name - "time". Than when you concatenate the new series to the dataframe, it appears with the name "time". When you userename, you ask to renamedf.columns[3]to "hour". Butdf.columns[3]holds the value "time", so what you basically wrote there isrename(columns={"time": "hour"}). As i explained earlier your df had 2 columns named "time" up to this point, so now they will both be changed to "hour".
– Gal Avineri
Nov 24 '18 at 14:13
@GalAvineri - Yes, I agree - Added solution for this.
– jezrael
Nov 24 '18 at 14:58
add a comment |
2
2
2
Use dt.hour:
df['time'] = pd.to_datetime(df['time'])
df['hours'] = df['time'].dt.hour
But if really need your solution only rename column, converting to Series is not necessary, because each column of DataFrame is Series after selecting (print (type(df['time']))):
df = pd.DataFrame({'time':['10:20:30','20:03:04']})
df['time'] = pd.to_datetime(df['time'])
hour_col = df['time'].rename('hour')
hour_col = hour_col.apply(lambda t: t.hour)
df = pd.concat([df, hour_col], axis=1)
print (df)
time hour
0 2018-11-24 10:20:30 10
1 2018-11-24 20:03:04 20
If want replace columns by position (e.g. because duplicated values and rename change both names like mentioned @Gla Avineri in comment) use:
df = pd.DataFrame({'time':['10:20:30','20:03:04'],
'a':[2,3],
'b':[-4,5]})
df['time'] = pd.to_datetime(df['time'])
hour_col = df['time']
hour_col = hour_col.apply(lambda t: t.hour)
df = pd.concat([df, hour_col], axis=1)
#converting to list because columns are immutable
cols = df.columns.tolist()
#set 4th value
cols[3] = 'hour'
#assign back
df.columns = cols
print (df)
time a b hour
0 2018-11-24 10:20:30 2 -4 10
1 2018-11-24 20:03:04 3 5 20
answered Nov 24 '18 at 13:21
jezraeljezrael
341k25296368
Use dt.hour:
df['time'] = pd.to_datetime(df['time'])
df['hours'] = df['time'].dt.hour
But if really need your solution only rename column, converting to Series is not necessary, because each column of DataFrame is Series after selecting (print (type(df['time']))):
df = pd.DataFrame({'time':['10:20:30','20:03:04']})
df['time'] = pd.to_datetime(df['time'])
hour_col = df['time'].rename('hour')
hour_col = hour_col.apply(lambda t: t.hour)
df = pd.concat([df, hour_col], axis=1)
print (df)
time hour
0 2018-11-24 10:20:30 10
1 2018-11-24 20:03:04 20
If want replace columns by position (e.g. because duplicated values and rename change both names like mentioned @Gla Avineri in comment) use:
df = pd.DataFrame({'time':['10:20:30','20:03:04'],
'a':[2,3],
'b':[-4,5]})
df['time'] = pd.to_datetime(df['time'])
hour_col = df['time']
hour_col = hour_col.apply(lambda t: t.hour)
df = pd.concat([df, hour_col], axis=1)
#converting to list because columns are immutable
cols = df.columns.tolist()
#set 4th value
cols[3] = 'hour'
#assign back
df.columns = cols
print (df)
time a b hour
0 2018-11-24 10:20:30 2 -4 10
1 2018-11-24 20:03:04 3 5 20
answered Nov 24 '18 at 13:21
jezraeljezrael
341k25296368
edited Nov 24 '18 at 14:57
answered Nov 24 '18 at 13:21
jezraeljezrael
341k25296368
answered Nov 24 '18 at 13:21
jezraeljezrael
341k25296368
answered Nov 24 '18 at 13:21
jezraeljezrael
341k25296368
341k25296368
I'll try that, thanks. Out of curiosity, what is the problem with my code? Why is it behaving like that?
– yaseco
Nov 24 '18 at 13:23
I would guess that in your code, when you copy the time series of the dataframe, you are also copying it's name - "time". Than when you concatenate the new series to the dataframe, it appears with the name "time". When you userename, you ask to renamedf.columns[3]to "hour". Butdf.columns[3]holds the value "time", so what you basically wrote there isrename(columns={"time": "hour"}). As i explained earlier your df had 2 columns named "time" up to this point, so now they will both be changed to "hour".
– Gal Avineri
Nov 24 '18 at 14:13
@GalAvineri - Yes, I agree - Added solution for this.
– jezrael
Nov 24 '18 at 14:58
add a comment |
I'll try that, thanks. Out of curiosity, what is the problem with my code? Why is it behaving like that?
– yaseco
Nov 24 '18 at 13:23
I would guess that in your code, when you copy the time series of the dataframe, you are also copying it's name - "time". Than when you concatenate the new series to the dataframe, it appears with the name "time". When you userename, you ask to renamedf.columns[3]to "hour". Butdf.columns[3]holds the value "time", so what you basically wrote there isrename(columns={"time": "hour"}). As i explained earlier your df had 2 columns named "time" up to this point, so now they will both be changed to "hour".
– Gal Avineri
Nov 24 '18 at 14:13
@GalAvineri - Yes, I agree - Added solution for this.
– jezrael
Nov 24 '18 at 14:58
I'll try that, thanks. Out of curiosity, what is the problem with my code? Why is it behaving like that?
– yaseco
Nov 24 '18 at 13:23
I'll try that, thanks. Out of curiosity, what is the problem with my code? Why is it behaving like that?
– yaseco
Nov 24 '18 at 13:23
I would guess that in your code, when you copy the time series of the dataframe, you are also copying it's name - "time". Than when you concatenate the new series to the dataframe, it appears with the name "time". When you use
rename, you ask to rename df.columns[3] to "hour". But df.columns[3] holds the value "time", so what you basically wrote there is rename(columns={"time": "hour"}). As i explained earlier your df had 2 columns named "time" up to this point, so now they will both be changed to "hour".– Gal Avineri
Nov 24 '18 at 14:13
I would guess that in your code, when you copy the time series of the dataframe, you are also copying it's name - "time". Than when you concatenate the new series to the dataframe, it appears with the name "time". When you use
rename, you ask to rename df.columns[3] to "hour". But df.columns[3] holds the value "time", so what you basically wrote there is rename(columns={"time": "hour"}). As i explained earlier your df had 2 columns named "time" up to this point, so now they will both be changed to "hour".– Gal Avineri
Nov 24 '18 at 14:13
@GalAvineri - Yes, I agree - Added solution for this.
– jezrael
Nov 24 '18 at 14:58
@GalAvineri - Yes, I agree - Added solution for this.
– jezrael
Nov 24 '18 at 14:58
add a comment |
draft saved
draft discarded
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.
draft saved
draft discarded
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%2f53458550%2fconcatenating-a-new-column-and-renaming-it%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
