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New to Pandas, so maybe I'm missing a big idea? I have a Pandas DataFrame of register transactions with shape like (500,4):
Time datetime64[ns] Net Total float64 Tax float64 Total Due float64 I'm working through my code in a Python3 Jupyter notebook. I can't get past sorting any column. Working through the different code examples for sort, I'm not seeing the output reorder when I inspect the df. So, I've reduced the problem to trying to order just one column:
df.sort_values(by='Time') # OR df.sort_values(['Total Due']) # OR df.sort_values(['Time'], ascending=True) No matter which column title, or which boolean argument I use, the displayed results never change order.
Thinking it could be a Jupyter thing, I've previewed the results using print(df), df.head(), and HTML(df.to_html()) (the last example is for Jupyter notebooks). I've also rerun the whole notebook from import CSV to this code. And, I'm also new to Python3 (from 2.7), so I get stuck with that sometimes, but I don't see how that's relevant in this case.
Another post has a similar problem, Python pandas dataframe sort_values does not work. In that instance, the ordering was on a column type string. But as you can see all of the columns here are unambiguously sortable.
Why does my Pandas DataFrame not display new order using sort_values?
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To sort the DataFrame based on the values in a single column, you'll use . sort_values() . By default, this will return a new DataFrame sorted in ascending order. It does not modify the original DataFrame.
Set value of display. max_rows to None and pass it to set_option and this will display all rows from the data frame.
Another way to reorder columns is to use the Pandas . reindex() method. This allows you to pass in the columns= parameter to pass in the order of columns that you want to use.
df.sort_values(['Total Due']) returns a sorted DF, but it doesn't update DF in place.
So do it explicitly:
df = df.sort_values(['Total Due']) or
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