Python – Update a dataframe in pandas while iterating row by row

dataframepandaspythonupdates

I have a pandas data frame that looks like this (its a pretty big one)

           date      exer exp     ifor         mat  
1092  2014-03-17  American   M  528.205  2014-04-19 
1093  2014-03-17  American   M  528.205  2014-04-19 
1094  2014-03-17  American   M  528.205  2014-04-19 
1095  2014-03-17  American   M  528.205  2014-04-19    
1096  2014-03-17  American   M  528.205  2014-05-17

now I would like to iterate row by row and as I go through each row, the value of ifor
in each row can change depending on some conditions and I need to lookup another dataframe.

Now, how do I update this as I iterate.
Tried a few things none of them worked.

for i, row in df.iterrows():
    if <something>:
        row['ifor'] = x
    else:
        row['ifor'] = y

    df.ix[i]['ifor'] = x

None of these approaches seem to work. I don't see the values updated in the dataframe.

Best Answer

You can assign values in the loop using df.set_value:

for i, row in df.iterrows():
    ifor_val = something
    if <condition>:
        ifor_val = something_else
    df.set_value(i,'ifor',ifor_val)

If you don't need the row values you could simply iterate over the indices of df, but I kept the original for-loop in case you need the row value for something not shown here.

update

df.set_value() has been deprecated since version 0.21.0 you can use df.at() instead:

for i, row in df.iterrows():
    ifor_val = something
    if <condition>:
        ifor_val = something_else
    df.at[i,'ifor'] = ifor_val

Related Solutions

Python – Iterating over dictionaries using ‘for’ loops

key is just a variable name.

for key in d:

will simply loop over the keys in the dictionary, rather than the keys and values. To loop over both key and value you can use the following:

For Python 3.x:

for key, value in d.items():

For Python 2.x:

for key, value in d.iteritems():

To test for yourself, change the word key to poop.

In Python 3.x, iteritems() was replaced with simply items(), which returns a set-like view backed by the dict, like iteritems() but even better. This is also available in 2.7 as viewitems().

The operation items() will work for both 2 and 3, but in 2 it will return a list of the dictionary's (key, value) pairs, which will not reflect changes to the dict that happen after the items() call. If you want the 2.x behavior in 3.x, you can call list(d.items()).

Git – How to update or sync a forked repository on GitHub

In your local clone of your forked repository, you can add the original GitHub repository as a "remote". ("Remotes" are like nicknames for the URLs of repositories - origin is one, for example.) Then you can fetch all the branches from that upstream repository, and rebase your work to continue working on the upstream version. In terms of commands that might look like:

# Add the remote, call it "upstream":

git remote add upstream https://github.com/whoever/whatever.git

# Fetch all the branches of that remote into remote-tracking branches

git fetch upstream

# Make sure that you're on your master branch:

git checkout master

# Rewrite your master branch so that any commits of yours that
# aren't already in upstream/master are replayed on top of that
# other branch:

git rebase upstream/master

If you don't want to rewrite the history of your master branch, (for example because other people may have cloned it) then you should replace the last command with git merge upstream/master. However, for making further pull requests that are as clean as possible, it's probably better to rebase.

If you've rebased your branch onto upstream/master you may need to force the push in order to push it to your own forked repository on GitHub. You'd do that with:

git push -f origin master

You only need to use the -f the first time after you've rebased.

Best Answer

Related Solutions

Python – Iterating over dictionaries using ‘for’ loops

Git – How to update or sync a forked repository on GitHub

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