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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 do I select rows from a DataFrame based on column values? Only, when the size of the dataframe approaches million rows, many of the methods tend to take ages when using df[df['col']==val] I wanted to have all possible values of "another_column" that correspond to specific values in "some_column" (in this case in a dictionary)
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 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 - Shuffle DataFrame rows - Stack Overflow Doesn't df = df sample(frac=1) do the exact same thing as df = sklearn utils shuffle(df)? According to my measurements df = df sample(frac=1) is faster and seems to perform the exact same action They also both allocate new memory np random shuffle(df values) is the slowest, but does not allocate new memory
Import CSV file as a Pandas DataFrame - Stack Overflow To read a CSV file as a pandas DataFrame, you'll need to use pd read_csv, which has sep=',' as the default But this isn't where the story ends; data exists in many different formats and is stored in different ways so you will often need to pass additional parameters to read_csv to ensure your data is read in properly Here's a table listing common scenarios encountered with CSV files along