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- 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
- 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]
- disk usage - Differences between df, df -h, and df -l - Ask Ubuntu
Question What are the differences between the following commands? df df -h df -l Feedback Information is greatly appreciated Thank you
- 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
- 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 - Insert a row to pandas dataframe - Stack Overflow
289 Just assign row to a particular index, using loc: df loc[-1] = [2, 3, 4] # adding a row df index = df index + 1 # shifting index df = df sort_index() # sorting by index And you get, as desired: A B C 0 2 3 4 1 5 6 7 2 7 8 9 See in Pandas documentation Indexing: Setting with enlargement
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