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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]
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 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
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 - What is df. values [:,1:]? - Stack Overflow df values returns a numpy array with the underlying data of the DataFrame, without any index or columns names [:, 1:] is a slice of that array, that returns all rows and every column starting from the second column (the first column is index 0)
What is the meaning of `df [df [factor]]` syntax in Pandas? The second df in df[df['factor']] refers to the DataFrame on which the boolean indexing is being performed The boolean indexing operation [df['factor']] creates a boolean mask that is a Series of True and False values with the same length as the DataFrame
python - df. drop if it exists - Stack Overflow df = df drop([x for x in candidates if x in df columns], axis=1) It has the benefit of readability and (with a small tweak to the code) the ability to record exactly which columns existed were dropped when