@bogatron has it right, you can use where, it’s worth noting that you can do this natively in pandas: Note: this changes the dtype of all columns to object. Example: Note: what you cannot do recast the DataFrames dtype to allow all datatypes types, using astype, and then the DataFrame fillna method: Unfortunately neither this, nor using replace, works with None see this (closed) issue. As an aside, … Read more
either: or, .reset_index: so, if you have a multi-index frame with 3 levels of index, like: and you want to convert the 1st (tick) and 3rd (obs) levels in the index into columns, you would do:
We can use ix to reorder by passing a list: Another method is to take a reference to the column and reinsert it at the front: You can also use loc to achieve the same result as ix will be deprecated in a future version of pandas from 0.20.0 onwards:
You can use parameter usecols with order of columns: Edit: You can use separator regex – 2 and more spaces and then add engine=’python’ because warning: ParserWarning: Falling back to the ‘python’ engine because the ‘c’ engine does not support regex separators (separators > 1 char and different from ‘\s+’ are interpreted as regex); you … Read more
I am trying to read a .xlsx with pandas, but get the follwing error: I’ve also tried And I Still get the same error. Background: I’m trying to extract an excel file with multiple worksheets as a dict of data frames.I installed xlrd version 0.9.0 and the latest version(1.1.0) but I still get the same … Read more
Your error is line 2. df[‘intage’] = int(df[‘age’]) is not valid, you can’t pass a pandas series to the int function. You need to use astype if df[‘age’] is object dtype. Or since you are subtracting two dates, you need to use dt accessor with the days attribute to get the number of days as … Read more
pd.concat requires that the indices be unique. To remove rows with duplicate indices, use Note there is also pd.join, which can join DataFrames based on their indices, and handle non-unique indices based on the how parameter. Rows with duplicate index are not removed.
You can plot several columns at once by supplying a list of column names to the plot‘s y argument. This will produce a graph where bars are sitting next to each other. In order to have them overlapping, you would need to call plot several times, and supplying the axes to plot to as an … Read more
You can use numpy.where: Error is better explain here. Slowier solution with apply, where need axis=1 for data processing by rows: Also is possible use loc, but sometimes data can be overwritten:
Use the to_datetime function, specifying a format to match your data.