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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
Selecting multiple columns in a Pandas dataframe - Stack Overflow So your column is returned by df['index'] and the real DataFrame index is returned by df index An Index is a special kind of Series optimized for lookup of its elements' values For df index it's for looking up rows by their label That df columns attribute is also a pd Index array, for looking up columns by their labels
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]
How to get set a pandas index column title or name? To just get the index column names df index names will work for both a single Index or MultiIndex as of the most recent version of pandas As someone who found this while trying to find the best way to get a list of index names + column names, I would have found this answer useful:
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
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
python - Change column type in pandas - Stack Overflow table = [ ['a', '1 2', '4 2' ], ['b', '70', '0 03'], ['x', '5', '0' ], ] df = pd DataFrame(table) How do I convert the columns to specific types? In this case, I want to convert columns 2 and 3 into floats Is there a way to specify the types while converting the list to DataFrame? Or is it better to create the DataFrame first and then loop through the columns to change the dtype for each