Filling DataFrame Pandas Python
1
I have a similar dataset, and even though the code gives me the right output; I do not want to use three for loops. Is there a way to do this in a better way?
import pandas as pd
col = ["a","b","c","d"]
index = ["0","1","2","3"]
dict_ = {("0","a"):8,
("1","a"):3,
("3","b"):2}
df = pd.DataFrame(columns=col,index=index)
for i in range(len(dict_)):
for j in range(len(df)):
for k in range(len(df)):
if (str(df.index[j]),str(df.columns[k])) == dict_.keys()[i]:
df.at[df.index[j],df.columns[k]] = dict_.values()[i]
print df
python pandas performance dataframe for-loop
edited Nov 23 '18 at 16:57
Ken Dekalb
321111
asked Nov 23 '18 at 16:03
Avantika BanerjeeAvantika Banerjee
187
add a comment |
1
I have a similar dataset, and even though the code gives me the right output; I do not want to use three for loops. Is there a way to do this in a better way?
import pandas as pd
col = ["a","b","c","d"]
index = ["0","1","2","3"]
dict_ = {("0","a"):8,
("1","a"):3,
("3","b"):2}
df = pd.DataFrame(columns=col,index=index)
for i in range(len(dict_)):
for j in range(len(df)):
for k in range(len(df)):
if (str(df.index[j]),str(df.columns[k])) == dict_.keys()[i]:
df.at[df.index[j],df.columns[k]] = dict_.values()[i]
print df
python pandas performance dataframe for-loop
edited Nov 23 '18 at 16:57
Ken Dekalb
321111
asked Nov 23 '18 at 16:03
Avantika BanerjeeAvantika Banerjee
187
add a comment |
1
1
1
I have a similar dataset, and even though the code gives me the right output; I do not want to use three for loops. Is there a way to do this in a better way?
import pandas as pd
col = ["a","b","c","d"]
index = ["0","1","2","3"]
dict_ = {("0","a"):8,
("1","a"):3,
("3","b"):2}
df = pd.DataFrame(columns=col,index=index)
for i in range(len(dict_)):
for j in range(len(df)):
for k in range(len(df)):
if (str(df.index[j]),str(df.columns[k])) == dict_.keys()[i]:
df.at[df.index[j],df.columns[k]] = dict_.values()[i]
print df
python pandas performance dataframe for-loop
edited Nov 23 '18 at 16:57
Ken Dekalb
321111
asked Nov 23 '18 at 16:03
Avantika BanerjeeAvantika Banerjee
187
I have a similar dataset, and even though the code gives me the right output; I do not want to use three for loops. Is there a way to do this in a better way?
import pandas as pd
col = ["a","b","c","d"]
index = ["0","1","2","3"]
dict_ = {("0","a"):8,
("1","a"):3,
("3","b"):2}
df = pd.DataFrame(columns=col,index=index)
for i in range(len(dict_)):
for j in range(len(df)):
for k in range(len(df)):
if (str(df.index[j]),str(df.columns[k])) == dict_.keys()[i]:
df.at[df.index[j],df.columns[k]] = dict_.values()[i]
print df
python pandas performance dataframe for-loop
python pandas performance dataframe for-loop
edited Nov 23 '18 at 16:57
Ken Dekalb
321111
asked Nov 23 '18 at 16:03
Avantika BanerjeeAvantika Banerjee
187
edited Nov 23 '18 at 16:57
Ken Dekalb
321111
asked Nov 23 '18 at 16:03
Avantika BanerjeeAvantika Banerjee
187
edited Nov 23 '18 at 16:57
Ken Dekalb
321111
edited Nov 23 '18 at 16:57
Ken Dekalb
321111
edited Nov 23 '18 at 16:57
Ken Dekalb
321111
321111
asked Nov 23 '18 at 16:03
Avantika BanerjeeAvantika Banerjee
187
asked Nov 23 '18 at 16:03
Avantika BanerjeeAvantika Banerjee
187
asked Nov 23 '18 at 16:03
Avantika BanerjeeAvantika Banerjee
187
187
add a comment |
add a comment |
1 Answer
1
active
oldest
votes
2
IIUC, using reindex
pd.Series(dict_).unstack().reindex(index=index,columns=col)
Out[245]:
a b c d
0 8.0 NaN NaN NaN
1 3.0 NaN NaN NaN
2 NaN NaN NaN NaN
3 NaN 2.0 NaN NaN
answered Nov 23 '18 at 16:06
W-BW-B
105k73165
Beautiful! Thank you :')
– Avantika Banerjee
Nov 23 '18 at 16:12
1
@ W-B.. is always gives beautiful solution & tips :-) +1
– pygo
Nov 23 '18 at 16:13
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%2f53449792%2ffilling-dataframe-pandas-python%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
IIUC, using reindex
pd.Series(dict_).unstack().reindex(index=index,columns=col)
Out[245]:
a b c d
0 8.0 NaN NaN NaN
1 3.0 NaN NaN NaN
2 NaN NaN NaN NaN
3 NaN 2.0 NaN NaN
answered Nov 23 '18 at 16:06
W-BW-B
105k73165
Beautiful! Thank you :')
– Avantika Banerjee
Nov 23 '18 at 16:12
1
@ W-B.. is always gives beautiful solution & tips :-) +1
– pygo
Nov 23 '18 at 16:13
add a comment |
2
IIUC, using reindex
pd.Series(dict_).unstack().reindex(index=index,columns=col)
Out[245]:
a b c d
0 8.0 NaN NaN NaN
1 3.0 NaN NaN NaN
2 NaN NaN NaN NaN
3 NaN 2.0 NaN NaN
answered Nov 23 '18 at 16:06
W-BW-B
105k73165
Beautiful! Thank you :')
– Avantika Banerjee
Nov 23 '18 at 16:12
1
@ W-B.. is always gives beautiful solution & tips :-) +1
– pygo
Nov 23 '18 at 16:13
add a comment |
2
2
2
IIUC, using reindex
pd.Series(dict_).unstack().reindex(index=index,columns=col)
Out[245]:
a b c d
0 8.0 NaN NaN NaN
1 3.0 NaN NaN NaN
2 NaN NaN NaN NaN
3 NaN 2.0 NaN NaN
answered Nov 23 '18 at 16:06
W-BW-B
105k73165
IIUC, using reindex
pd.Series(dict_).unstack().reindex(index=index,columns=col)
Out[245]:
a b c d
0 8.0 NaN NaN NaN
1 3.0 NaN NaN NaN
2 NaN NaN NaN NaN
3 NaN 2.0 NaN NaN
answered Nov 23 '18 at 16:06
W-BW-B
105k73165
answered Nov 23 '18 at 16:06
W-BW-B
105k73165
answered Nov 23 '18 at 16:06
W-BW-B
105k73165
answered Nov 23 '18 at 16:06
W-BW-B
105k73165
105k73165
Beautiful! Thank you :')
– Avantika Banerjee
Nov 23 '18 at 16:12
1
@ W-B.. is always gives beautiful solution & tips :-) +1
– pygo
Nov 23 '18 at 16:13
add a comment |
Beautiful! Thank you :')
– Avantika Banerjee
Nov 23 '18 at 16:12
1
@ W-B.. is always gives beautiful solution & tips :-) +1
– pygo
Nov 23 '18 at 16:13
Beautiful! Thank you :')
– Avantika Banerjee
Nov 23 '18 at 16:12
Beautiful! Thank you :')
– Avantika Banerjee
Nov 23 '18 at 16:12
1
1
@ W-B.. is always gives beautiful solution & tips :-) +1
– pygo
Nov 23 '18 at 16:13
@ W-B.. is always gives beautiful solution & tips :-) +1
– pygo
Nov 23 '18 at 16:13
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%2f53449792%2ffilling-dataframe-pandas-python%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
