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How can I iterate over rows in a Pandas DataFrame? I have a pandas dataframe, df: c1 c2 0 10 100 1 11 110 2 12 120 How do I iterate over the rows of this dataframe? For every row, I want to access its elements (values in cells) by the n
How do I get the row count of a Pandas DataFrame? could use df info () so you get row count (# entries), number of non-null entries in each column, dtypes and memory usage Good complete picture of the df If you're looking for a number you can use programatically then df shape [0]
python - Renaming column names in Pandas - Stack Overflow To focus on the need to rename of replace column names with a pre-existing list, I'll create a new sample dataframe df with initial column names and unrelated new column names
How to iterate over columns of a pandas dataframe 66 This answer is to iterate over selected columns as well as all columns in a DF df columns gives a list containing all the columns' names in the DF Now that isn't very helpful if you want to iterate over all the columns But it comes in handy when you want to iterate over columns of your choosing only
python - How to check if particular value (in cell) is NaN in pandas . . . >>> df iloc[1,0] nan So, why is the second option not working? Is it possible to check for NaN values using iloc? Editor's note: This question previously used pd np instead of np and ix in addition to iloc, but since these no longer exist, they have been edited out to keep it short and clear
How can I get a value from a cell of a dataframe? - Stack Overflow 54 Most answers are using iloc which is good for selection by position If you need selection-by-label, loc would be more convenient For getting a value explicitly (equiv to deprecated df get_value ('a','A'))