Custom Reorder of Values in Python Dataframe

Question

import pandas as pd
import numpy as np 

table = pd.DataFrame()

table["SORT_WW"]= ["03", "50", "01", "52", "03", "48", "02", "47"]
table ["Name"] = ["a", "b", "c", "d", "e", "f", "g", "h"]

And my current table is like:

Order I need:

SORT_WW_reorder = pd.Categorical(['45', '44', '46', '47', '48', '49', '50','51', '52', '53', '01', '02', '03', '04', '05', '06', '07'], ordered = True)

What I tried after reading on Stackoverflow answers:

SORT_WW_reorder = pd.Categorical(['45', '44', '46', '47', '48', '49', '50','51', '52', '53', '01', '02', '03', '04', '05', '06', '07'], ordered = True)

table.reindex(SORT_WW_reorder)

It does not do anything once I click on the dataframe "table" on Spyder (the image I shared is same = order is same, did not update). What am I missing?

How did you check the result ? Did you assign the result ? what did you prnt EXACTLY ? — azro
– azro, Commented Nov 14, 2019 at 21:44
It does not do anything once I click on the dataframe "table" on Spyder (the image I shared is same = order is same, did not update). What am I missing? — greencar
– greencar, Commented Nov 14, 2019 at 21:48
Try table.reindex(SORT_WW_reorder, inplace=True) or table = table.reindex(SORT_WW_reorder) please and tell us — azro
– azro, Commented Nov 14, 2019 at 21:49
TypeError: reindex() got an unexpected keyword argument "inplace" and the other suggestion returned all NaN — greencar
– greencar, Commented Nov 14, 2019 at 21:51
whaat, you just change sort_values by reindex ... the argument I gave is for sort_values — azro
– azro, Commented Nov 14, 2019 at 21:51

cs95 · Accepted Answer · 2019-11-14 22:04:47Z

0

From my understanding, you want to reorder your rows based on how the values in SORT_WW map to positions in your ordered categorical array.

Here's an option to get the sorted indices by converting your categorical array into an Index:

df.iloc[pd.Index(SORT_WW_reorder).get_indexer(df.SORT_WW).argsort()]                                                                                 

  SORT_WW Name
7      47    h
5      48    f
1      50    b
3      52    d
2      01    c
6      02    g
0      03    a
4      03    e

edited Nov 14, 2019 at 22:04

answered Nov 14, 2019 at 21:54

cs95

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8 Comments

greencar Over a year ago

this is not the order I want tho.. this is the order I need: SORT_WW_reorder = pd.Categorical(['45', '44', '46', '47', '48', '49', '50','51', '52', '53', '01', '02', '03', '04', '05', '06', '07'], ordered = True)

cs95 Over a year ago

@shaucha Hmm, how about now?

cs95 Over a year ago

@shaucha If that still isn't what you want, I'm going to stop and ask that you update your question with what the expected output should look like.

greencar Over a year ago

thanks-- works ! , I just did the assignment part as so: table = table.iloc[pd.Index(SORT_WW_reorder).get_indexer(table.SORT_WW).argsort()]

greencar Over a year ago

you did amazing! I will assign this the "answer"

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