Return first numeric value in a column
This is pretty much what my dataframe looks like (indexed by year and countries.)
ISO gini efw
year countries
1970 Argentina ARG NaN 5.67
1975 Argentina ARG NaN 3.13
1980 Argentina ARG 40.8 4.25
1985 Argentina ARG NaN 3.53
1990 Argentina ARG NaN 4.47
1970 Bolivia BOL NaN NaN
1975 Bolivia BOL NaN NaN
1980 Bolivia BOL NaN 4.08
1985 Bolivia BOL NaN 3.52
1990 Bolivia BOL 42.0 5.62
2010 Uruguay URY 44.5 7.33
2011 Uruguay URY 42.2 7.39
2012 Uruguay URY 39.9 7.34
2013 Uruguay URY 40.5 7.26
1970 Venezuela VEN NaN 7.18
1975 Venezuela VEN NaN 6.22
1980 Venezuela VEN NaN 6.72
1985 Venezuela VEN NaN 6.08
1990 Venezuela VEN NaN 5.55
1995 Venezuela VEN 47.8 4.35
2000 Venezuela VEN NaN 5.89
I want to come up with a function that identifies the first non NaN value in the gini column, and returns the year and efw value that correspond to the value in the gini column.
For example, if the first non Nan for Argentina is 40.8, I want the function to return 40.8, the year for that value (1980), and the value for efw also for 1980 (4.25).
Ideally the new dataframe would look like this. That for every country.
ISO gini efw
year countries
1980 Argentina ARG 40.8 4.25
2016 Argentina ARG 43.60 3.13
The last row corresponds to 2016, the last year for which there is data available.
python pandas function dataframe
asked Nov 16 '18 at 3:42
Guillermina Sutter SchneiderGuillermina Sutter Schneider
12011
add a comment |
This is pretty much what my dataframe looks like (indexed by year and countries.)
ISO gini efw
year countries
1970 Argentina ARG NaN 5.67
1975 Argentina ARG NaN 3.13
1980 Argentina ARG 40.8 4.25
1985 Argentina ARG NaN 3.53
1990 Argentina ARG NaN 4.47
1970 Bolivia BOL NaN NaN
1975 Bolivia BOL NaN NaN
1980 Bolivia BOL NaN 4.08
1985 Bolivia BOL NaN 3.52
1990 Bolivia BOL 42.0 5.62
2010 Uruguay URY 44.5 7.33
2011 Uruguay URY 42.2 7.39
2012 Uruguay URY 39.9 7.34
2013 Uruguay URY 40.5 7.26
1970 Venezuela VEN NaN 7.18
1975 Venezuela VEN NaN 6.22
1980 Venezuela VEN NaN 6.72
1985 Venezuela VEN NaN 6.08
1990 Venezuela VEN NaN 5.55
1995 Venezuela VEN 47.8 4.35
2000 Venezuela VEN NaN 5.89
I want to come up with a function that identifies the first non NaN value in the gini column, and returns the year and efw value that correspond to the value in the gini column.
For example, if the first non Nan for Argentina is 40.8, I want the function to return 40.8, the year for that value (1980), and the value for efw also for 1980 (4.25).
Ideally the new dataframe would look like this. That for every country.
ISO gini efw
year countries
1980 Argentina ARG 40.8 4.25
2016 Argentina ARG 43.60 3.13
The last row corresponds to 2016, the last year for which there is data available.
python pandas function dataframe
asked Nov 16 '18 at 3:42
Guillermina Sutter SchneiderGuillermina Sutter Schneider
12011
1
Can you check your desired output df there? I don't see where you got the second row from... First makes sense, second I don't see here. Wouldn't the next row be1990 Bolivia BOL 32.0 5.62?
– Capn Jack
Nov 16 '18 at 3:45
1
Is there any particular reason whyyearandcountriesare indexes? I recommend those to be columns as those are more flexible to work with.
– vlizana
Nov 16 '18 at 3:54
add a comment |
This is pretty much what my dataframe looks like (indexed by year and countries.)
ISO gini efw
year countries
1970 Argentina ARG NaN 5.67
1975 Argentina ARG NaN 3.13
1980 Argentina ARG 40.8 4.25
1985 Argentina ARG NaN 3.53
1990 Argentina ARG NaN 4.47
1970 Bolivia BOL NaN NaN
1975 Bolivia BOL NaN NaN
1980 Bolivia BOL NaN 4.08
1985 Bolivia BOL NaN 3.52
1990 Bolivia BOL 42.0 5.62
2010 Uruguay URY 44.5 7.33
2011 Uruguay URY 42.2 7.39
2012 Uruguay URY 39.9 7.34
2013 Uruguay URY 40.5 7.26
1970 Venezuela VEN NaN 7.18
1975 Venezuela VEN NaN 6.22
1980 Venezuela VEN NaN 6.72
1985 Venezuela VEN NaN 6.08
1990 Venezuela VEN NaN 5.55
1995 Venezuela VEN 47.8 4.35
2000 Venezuela VEN NaN 5.89
I want to come up with a function that identifies the first non NaN value in the gini column, and returns the year and efw value that correspond to the value in the gini column.
For example, if the first non Nan for Argentina is 40.8, I want the function to return 40.8, the year for that value (1980), and the value for efw also for 1980 (4.25).
Ideally the new dataframe would look like this. That for every country.
ISO gini efw
year countries
1980 Argentina ARG 40.8 4.25
2016 Argentina ARG 43.60 3.13
The last row corresponds to 2016, the last year for which there is data available.
python pandas function dataframe
asked Nov 16 '18 at 3:42
Guillermina Sutter SchneiderGuillermina Sutter Schneider
12011
This is pretty much what my dataframe looks like (indexed by year and countries.)
ISO gini efw
year countries
1970 Argentina ARG NaN 5.67
1975 Argentina ARG NaN 3.13
1980 Argentina ARG 40.8 4.25
1985 Argentina ARG NaN 3.53
1990 Argentina ARG NaN 4.47
1970 Bolivia BOL NaN NaN
1975 Bolivia BOL NaN NaN
1980 Bolivia BOL NaN 4.08
1985 Bolivia BOL NaN 3.52
1990 Bolivia BOL 42.0 5.62
2010 Uruguay URY 44.5 7.33
2011 Uruguay URY 42.2 7.39
2012 Uruguay URY 39.9 7.34
2013 Uruguay URY 40.5 7.26
1970 Venezuela VEN NaN 7.18
1975 Venezuela VEN NaN 6.22
1980 Venezuela VEN NaN 6.72
1985 Venezuela VEN NaN 6.08
1990 Venezuela VEN NaN 5.55
1995 Venezuela VEN 47.8 4.35
2000 Venezuela VEN NaN 5.89
I want to come up with a function that identifies the first non NaN value in the gini column, and returns the year and efw value that correspond to the value in the gini column.
For example, if the first non Nan for Argentina is 40.8, I want the function to return 40.8, the year for that value (1980), and the value for efw also for 1980 (4.25).
Ideally the new dataframe would look like this. That for every country.
ISO gini efw
year countries
1980 Argentina ARG 40.8 4.25
2016 Argentina ARG 43.60 3.13
The last row corresponds to 2016, the last year for which there is data available.
python pandas function dataframe
python pandas function dataframe
asked Nov 16 '18 at 3:42
Guillermina Sutter SchneiderGuillermina Sutter Schneider
12011
asked Nov 16 '18 at 3:42
Guillermina Sutter SchneiderGuillermina Sutter Schneider
12011
edited Nov 16 '18 at 3:47
Guillermina Sutter Schneider
asked Nov 16 '18 at 3:42
Guillermina Sutter SchneiderGuillermina Sutter Schneider
12011
asked Nov 16 '18 at 3:42
Guillermina Sutter SchneiderGuillermina Sutter Schneider
12011
asked Nov 16 '18 at 3:42
Guillermina Sutter SchneiderGuillermina Sutter Schneider
12011
12011
1
Can you check your desired output df there? I don't see where you got the second row from... First makes sense, second I don't see here. Wouldn't the next row be1990 Bolivia BOL 32.0 5.62?
– Capn Jack
Nov 16 '18 at 3:45
1
Is there any particular reason whyyearandcountriesare indexes? I recommend those to be columns as those are more flexible to work with.
– vlizana
Nov 16 '18 at 3:54
add a comment |
1
Can you check your desired output df there? I don't see where you got the second row from... First makes sense, second I don't see here. Wouldn't the next row be1990 Bolivia BOL 32.0 5.62?
– Capn Jack
Nov 16 '18 at 3:45
1
Is there any particular reason whyyearandcountriesare indexes? I recommend those to be columns as those are more flexible to work with.
– vlizana
Nov 16 '18 at 3:54
1
1
Can you check your desired output df there? I don't see where you got the second row from... First makes sense, second I don't see here. Wouldn't the next row be
1990 Bolivia BOL 32.0 5.62?– Capn Jack
Nov 16 '18 at 3:45
Can you check your desired output df there? I don't see where you got the second row from... First makes sense, second I don't see here. Wouldn't the next row be
1990 Bolivia BOL 32.0 5.62?– Capn Jack
Nov 16 '18 at 3:45
1
1
Is there any particular reason why
year and countries are indexes? I recommend those to be columns as those are more flexible to work with.– vlizana
Nov 16 '18 at 3:54
Is there any particular reason why
year and countries are indexes? I recommend those to be columns as those are more flexible to work with.– vlizana
Nov 16 '18 at 3:54
add a comment |
1 Answer
1
active
oldest
votes
Use this, get by condition, then reset the index, then sort the values, then multiindex the dataframe again:
print(df[df['gini'].notnull()].reset_index().sort_values('year').iloc[[0, -1]].set_index(['year','countries']))
answered Nov 16 '18 at 3:59
U9-ForwardU9-Forward
16.9k51643
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%2f53331096%2freturn-first-numeric-value-in-a-column%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
Use this, get by condition, then reset the index, then sort the values, then multiindex the dataframe again:
print(df[df['gini'].notnull()].reset_index().sort_values('year').iloc[[0, -1]].set_index(['year','countries']))
answered Nov 16 '18 at 3:59
U9-ForwardU9-Forward
16.9k51643
add a comment |
Use this, get by condition, then reset the index, then sort the values, then multiindex the dataframe again:
print(df[df['gini'].notnull()].reset_index().sort_values('year').iloc[[0, -1]].set_index(['year','countries']))
answered Nov 16 '18 at 3:59
U9-ForwardU9-Forward
16.9k51643
add a comment |
Use this, get by condition, then reset the index, then sort the values, then multiindex the dataframe again:
print(df[df['gini'].notnull()].reset_index().sort_values('year').iloc[[0, -1]].set_index(['year','countries']))
answered Nov 16 '18 at 3:59
U9-ForwardU9-Forward
16.9k51643
Use this, get by condition, then reset the index, then sort the values, then multiindex the dataframe again:
print(df[df['gini'].notnull()].reset_index().sort_values('year').iloc[[0, -1]].set_index(['year','countries']))
answered Nov 16 '18 at 3:59
U9-ForwardU9-Forward
16.9k51643
answered Nov 16 '18 at 3:59
U9-ForwardU9-Forward
16.9k51643
answered Nov 16 '18 at 3:59
U9-ForwardU9-Forward
16.9k51643
answered Nov 16 '18 at 3:59
U9-ForwardU9-Forward
16.9k51643
16.9k51643
add a comment |
add a comment |
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%2f53331096%2freturn-first-numeric-value-in-a-column%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
1
Can you check your desired output df there? I don't see where you got the second row from... First makes sense, second I don't see here. Wouldn't the next row be
1990 Bolivia BOL 32.0 5.62?– Capn Jack
Nov 16 '18 at 3:45
1
Is there any particular reason why
yearandcountriesare indexes? I recommend those to be columns as those are more flexible to work with.– vlizana
Nov 16 '18 at 3:54