Pandas DataFrame to List of Lists

Question

It s easy to turn a list of lists into a pandas dataframe   import pandas as pd df   pd DataFrame   1 2 3   3 4 5      But how do I turn df back into a list of lists   lol   df what to do now  print lol     1 2 3   3 4 5

User · Answer

We can use the DataFrame iterrows   function to iterate over each of the rows of the given Dataframe and construct a list out of the data of each row     Empty list  row list         Iterate over each row  for index  rows in df iterrows           Create list for the current row      my list   rows Date  rows Event  rows Cost          append the list to the final list      row list append my list      Print  print row list     We can successfully extract each row of the given data frame into a list

User · Answer

You could access the underlying array and call its tolist method    gt  gt  gt  df   pd DataFrame   1 2 3   3 4 5     gt  gt  gt  lol   df values tolist    gt  gt  gt  lol   1L  2L  3L    3L  4L  5L

User · Answer

Maybe something changed but this gave back a list of ndarrays which did what I needed   list df values

User · Answer

I wanted to preserve the index  so I adapted the original answer to this solution  list df   df reset index   values tolist    Now you can paste it somewhere else  e g  to paste into a Stack Overflow question  and latter recreate it  pd Dataframe list df  columns   name1         pd set index   name1    inplace True

User · Answer

I don t know if it will fit your needs  but you can also do    gt  gt  gt  lol   df values  gt  gt  gt  lol array   1  2  3           3  4  5      This is just a numpy array from the ndarray module  which lets you do all the usual numpy array things

User · Answer

If you wish to convert a Pandas DataFrame to a table  list of lists  and include the header column this should work  import pandas as pd def dfToTable df pd DataFrame  - gt  list      return  list df columns     df values tolist    Usage  in REPL    gt  gt  gt  df   pd DataFrame                  quot r1c1 quot   quot r1c2 quot   quot r1c3 quot     quot r2c1 quot   quot r2c2 quot   quot r3c3 quot                   columns   quot c1 quot    quot c2 quot    quot c3 quot     gt  gt  gt  df      c1    c2    c3 0  r1c1  r1c2  r1c3 1  r2c1  r2c2  r3c3  gt  gt  gt  dfToTable df     c1    c2    c3      r1c1    r1c2    r1c3      r2c1    r2c2    r3c3

User · Answer

Note  I have seen many cases on Stack Overflow where converting a Pandas Series or DataFrame to a NumPy array or plain Python lists is entirely unecessary  If you re new to the library  consider double-checking whether the functionality you need is already offered by those Pandas objects   To quote a comment by  jpp       In practice  there s often no need to convert the NumPy array into a list of lists      If a Pandas DataFrame Series won t work  you can use the built-in DataFrame to numpy and Series to numpy methods

User · Answer

This is very simple   import numpy as np  list of lists   np array df

User · Answer

The solutions presented so far suffer from a  quot reinventing the wheel quot  approach  Quoting  AMC    If you re new to the library  consider double-checking whether the functionality you need is already offered by those Pandas objects    If you convert a dataframe to a list of lists you will lose information - namely the index and columns names   My solution  use to dict   dict of lists   df to dict orient  split    This will give you a dictionary with three lists  index  columns  data  If you decide you really don t need the columns and index names  you get the data with dict of lists  data

User · Answer

quot df values quot  returns a numpy array  This does not preserve the data types  An integer might be converted to a float  df iterrows   returns a series which also does not guarantee to preserve the data types  See  https   pandas pydata org pandas-docs stable reference api pandas DataFrame iterrows html The code below converts to a list of list and preserves the data types  rows    list row  for row in df itertuples

User · Answer

If the data has column and index labels that you want to preserve  there are a few options   Example data    gt  gt  gt  df   pd DataFrame   1 2 3   3 4 5             columns   first    second    third             index   alpha    beta      gt  gt  gt  df        first  second  third alpha      1       2      3 beta       3       4      5   The tolist   method described in other answers is useful but yields only the core data - which may not be enough  depending on your needs     gt  gt  gt  df values tolist     1  2  3    3  4  5     One approach is to convert the DataFrame to json using df to json   and then parse it again  This is cumbersome but does have some advantages  because the to json   method has some useful options    gt  gt  gt  df to json        first    alpha  1  beta  3      second    alpha  2  beta  4   third    alpha  3  beta  5      gt  gt  gt  df to json orient  split       columns    first   second   third      index    alpha   beta      data    1 2 3   3 4 5       Cumbersome but may be useful   The good news is that it s pretty straightforward to build lists for the columns and rows    gt  gt  gt  columns    df index name     i for i in df columns   gt  gt  gt  rows     i for i in row  for row in df itertuples      This yields    gt  gt  gt  print f columns   columns  nrows   rows     columns   None   first    second    third   rows     alpha   1  2  3     beta   3  4  5     If the None as the name of the index is bothersome  rename it   df   df rename axis  stage     Then    gt  gt  gt  columns    df index name     i for i in df columns   gt  gt  gt  print f columns   columns  nrows   rows      columns    stage    first    second    third   rows     alpha   1  2  3     beta   3  4  5

[python] Pandas DataFrame to List of Lists

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