I created this dataframe: but I need to change order in column multiindex. I need to have something like this Could you help me :) ? Answer You can use swaplevel on the resulting dataframe: Output:
Tag: multi-index
Python (Pandas) pivot datframe, some sums keeping the order
I’m trying to get from a to b. I got a Pandas data frame similar to the a below. I realize I’ve backed myself into a corner by computing sums in a flat file. I’m new to Python. I guess I should create the sums when I’m done pivoting? What I am stuck in is this wrong b struggle, I
Pandas multiIndex slicing by aggregate
I have a pandas Series (S) that has an index like: I have a conditional function that returns a lower dimensional index. What I am doing is performing something like S.groupby(level=(0,1)).median() > 1 This returns a Series with Index like so: How do I slice the original Series with the lower dimensional index? I know I can reset index and
Select colums in pandas multi index dataframe
I probably have a rather simple pandas question, but despite having tried multiple solutions posted on stackoverflow, I can’t figure out how to do it properly. I have pandas multi-index Dataframe with the following structure: Image1 now I want to select a subset of this dataframe based on the first column headers (HDx_DATE) The columns which I want to show
Accessing and overwriting Multiindex df data
I’m trying to multiply all the values of the following multiindex df for which the first multiindex equals Property_2 with a scalar: I’ve tried various ways: but I am getting back nan’s in the relevant places. Answer That’s because the indices don’t match. One way to get around the issue is to assign the underlying numpy array: or you could
Groupby and get the values in one dataframe
I have a dataframe which I need to do groupby by multiple columns and get the items within every group as a row; I need to output a below table after group; I have been looking for the answer but I was not able to find any, I appreciate if you can help we with the code. Answer You could
Get values from dataframe with MultiIndex index containg NaNs
I cannot access the values of an index position that has a nan in it and wonder how I could solve this. (In my project this index has a very special meaning and I really need to keep it, otherwise I would need to make some dirty manual modifications: “there is always a solution” even if it is a very
setting columns in multiindex pandas
I have this pandas df which i imported from a csv: Is it possible for everything on the left to be grouped under fresh and everything on the right of the dates to be under column spoil in multiindex format. Such as, there is one column which contains [apple, banana, orange]. I want to do this because later when i
Use a multidimensional index on a MultiIndex pandas dataframe?
I have a multiindex pandas dataframe that looks like this (called p_z): I want to be able to select certain rows based on another dataframe (or numpy array) which is multidimensional. It would look like this as a pandas dataframe (called tofpid): I also have it as an awkward array, where it’s a (26692, ) array (each of the entries
How do I filter multi-level columns using notnull() in pandas?
I generate a multi-index dataframe that has some NAN values using this: Which will create something like this: I’d like to get rows of a specific subset of top-level columns (eg df[[‘baz’,’qux’]]) that have no nulls. For example in df[[‘baz’,’qux’]] I’d like to get rows 0 and 1 since they both have all nulls in 3. Hoping things would just