CODEWITHSUNDEEP
pythonpandasdataframeindexingseries
Miguel
Miguel

Reputation: 3064

Pandas dataframe: simplest way to find arow and select an element from that row

How can I get a column value from a row given that this row was found using another value form another column? For example:

row = df.loc[df['Name'] == 'john']

and now I would like to get his email with something like this row['email']

Upvotes: 2

Views: 267

Answers (3)

jpp
jpp

Reputation: 164843

You have a few options. Note the below includes no error-handling. It's assumed the given name exists.

pd.DataFrame.loc + pd.Series.values

This accesses the underlying NumPy array and extracts the first item:

df.loc[df['Name'] == 'john', 'email'].values[0]

pd.DataFrame.at

Set your index to Name, then use at. Assumes your names are unique, otherwise scalar access in this way may not make sense.

df.set_index('Name').at['john', 'email']

If you do this often, I recommend you store df.set_index('Name') to avoid expensive repeat operations.

pd.Series.loc

Similar to the first solution but utilising pd.Series methods:

df['email'].loc[df['Name'].eq('john').index[0]]

Upvotes: 1

Mohit Motwani
Mohit Motwani

Reputation: 4792

You could use df.get_value too if you have

syntax:

DataFrame.get_value(index, col, takeable=False)

Example

df.get_value(1, 'email')

Here one is the index of the row

or df.at[]

df.at[1, 'email']

Upvotes: 0

zenofsahil
zenofsahil

Reputation: 1753

df.loc is a row and column indexer. So you can simply do

df.loc[df['Name'] == 'john', 'email']

Upvotes: 0

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