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We can use the following to iterate rows of a data frame.
for index, row in df.iterrows(): What if I want to begin from a different row index? (not from first row)?
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iterrows() is used to iterate over a pandas Data frame rows in the form of (index, series) pair. This function iterates over the data frame column, it will return a tuple with the column name and content in form of series. Syntax: DataFrame.iterrows() Yields: index- The index of the row.
The iterrows() method generates an iterator object of the DataFrame, allowing us to iterate each row in the DataFrame. Each iteration produces an index object and a row object (a Pandas Series object).
This function returns each index value along with a series that contain the data in each row. iterrows() - used for iterating over the rows as (index, series) pairs. iteritems() - used for iterating over the (key, value) pairs. itertuples() - used for iterating over the rows as namedtuples.
Itertuples(): Itertuples() iterates through the data frame by converting each row of data as a list of tuples. itertuples() takes 16 seconds to iterate through a data frame with 10 million records that are around 50x times faster than iterrows().
i know this has an answer, but why not just do:
for i, r in df.iloc[1:].iterrows(): Try using itertools.islice
from itertools import islice for index, row in islice(df.iterrows(), 1, None): If you love us? You can donate to us via Paypal or buy me a coffee so we can maintain and grow! Thank you!
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