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Tag: dataframe

I keep getting the error message AttributeError: ‘pandas._libs.properties.AxisProperty’ object has no attribute ‘unique’. How should I fix this error?

I’m using a Jupyter notebook and I’m trying to open a data file and keep getting an error code AttributeError:’pandas._libs.properties.AxisProperty’ object has no attribute ‘unique’. This is my first time using Jupyter So I am not familiar with any error like this. Answer You are not using pd.DataFrame right. See below corrected code:

How to convert first column of dataframe in to its headers

I have dataframe df: O/P should be: I want column containing(a, b,c,d,e) as header of my dataframe. Could anyone help? Answer If your dataframe is pandas and its name is df. Try solving it with pandas: Firstly convert initial df content to a list, afterwards create a new dataframe defining its columns with the list.

Group by the column in df python

I have a simple df. It has two columns. I want to groupby the values based on column a. Here is a simple example: Any input would be greatly appreciated! Desired output is: df Answer Here’s a way to do what you want. First you want to group by column ‘a’. Normally groupby is used to calculate group aggregation functions:

ValueError: Invalid fill method. Expecting pad (ffill) or backfill (bfill). Got nearest

I have this df: And when I try to run this interpolation: pmms_df.interpolate(method = ‘nearest’, inplace = True) I get ValueError: Invalid fill method. Expecting pad (ffill) or backfill (bfill). Got nearest I read in this post that pandas interpolate doesn’t do well with the time columns, so I tried this: pmms_df[[‘U.S. 30 yr FRM’, ‘U.S. 15 yr FRM’]].interpolate(method =

DataFrame from list of string dicts

So I have a list where each entry looks something like this: I am trying to get a dataframe that looks like this But I’m having trouble converting the format into something that can be read into a DataFrame. I know that pandas should automatically convert dicts into dataframes, but since my list elements are surrounded by quotes, it’s getting

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