python pandas dataframe to dictionary

Question

I ve a two columns dataframe  and intend to convert it to python dictionary - the first column will be the key and the second will be the value  Thank you in advance    Dataframe       id    value 0    0     10 2 1    1      5 7 2    2      7 4

User · Answer

See the docs for to dict  You can use it like this   df set index  id   to dict     And if you have only one column  to avoid the column name is also a level in the dict  actually  in this case you use the Series to dict      df set index  id    value   to dict

User · Answer

Simplest solution   df set index  id   T to dict  records     Example   df  pd DataFrame    a  1    a  2    b  3    columns   id   value    df set index  id   T to dict  records     If you have multiple values  like val1  val2  val3 etc and u want them as lists  then use the below code   df set index  id   T to dict  list

User · Answer

def get dict from pd df  key col  row col       result   dict       for i in set df key col  values           is i   df key col     i         result i    list df is i  row col  values      return result   this is my sloution  a basic loop

User · Answer

You need a list as a dictionary value  This code will do the trick   from collections import defaultdict mydict   defaultdict list  for k  v in zip df id values df value values       mydict k  append v

User · Answer

You can use  dict comprehension   my dict    row 0   row 1  for row in df values

User · Answer

Another  slightly shorter  solution for not losing duplicate entries    gt  gt  gt  ptest   pd DataFrame    a  1    a  2    b  3    columns   id   value     gt  gt  gt  ptest   id  value 0  a      1 1  a      2 2  b      3   gt  gt  gt  pdict   dict    gt  gt  gt  for i in ptest  id   unique   tolist            ptest slice   ptest ptest  id      i          pdict i    ptest slice  value   tolist         gt  gt  gt  pdict   b    3    a    1  2

User · Answer

The answers by joris in this thread and by punchagan in the duplicated thread are very elegant  however they will not give correct results if the column used for the keys contains any duplicated value    For example    gt  gt  gt  ptest   p DataFrame    a  1    a  2    b  3    columns   id    value      gt  gt  gt  ptest   id  value 0  a      1 1  a      2 2  b      3    note that in both cases the association a- gt 1 is lost   gt  gt  gt  ptest set index  id    value   to dict     a   2   b   3   gt  gt  gt  dict zip ptest id  ptest value     a   2   b   3    If you have duplicated entries and do not want to lose them  you can use this ugly but working code    gt  gt  gt  mydict       gt  gt  gt  for x in range len ptest            currentid   ptest iloc x 0          currentvalue   ptest iloc x 1          mydict setdefault currentid              mydict currentid  append currentvalue   gt  gt  gt  mydict   a    1  2    b    3

User · Answer

mydict   dict zip df id  df value

User · Answer

This is my solution   import pandas as pd df   pd read excel  dic xlsx   df T   df set index  id   T dic   df T to dict  records   print dic

User · Answer

If you want a simple way to preserve duplicates  you could use groupby    gt  gt  gt  ptest   pd DataFrame    a  1    a  2    b  3    columns   id    value      gt  gt  gt  ptest   id  value 0  a      1 1  a      2 2  b      3  gt  gt  gt   k  g  value   tolist   for k g in ptest groupby  id      a    1  2    b    3

User · Answer

in some versions  the code below might not work  mydict   dict zip df id  df value     so make it explicit  id  df id values value df value values mydict dict zip id  value     Note i used id  because the word id is reserved word

User · Answer

If you set the the index than the dictionary will result in unique key value pairs encoder LabelEncoder   df  airline enc   encoder fit transform df  airline    dictAirline  df   airline enc   airline    set index  airline enc   to dict

User · Answer

I found this question while trying to make a dictionary out of three columns of a pandas dataframe  In my case the dataframe has columns A  B and C  let s say A and B are the geographical coordinates of longitude and latitude and C the country region state etc  which is more or less the case    I wanted a dictionary with each pair of A B values  dictionary key  matching the value of C  dictionary value  in the corresponding row  each pair of A B values is guaranteed to be unique due to previous filtering  but it is possible to have the same value of C for different pairs of A B values in this context   so I did   mydict   dict zip zip df  A   df  B     df  C       Using pandas to dict   also works   mydict   df set index   A   B    to dict orient  dict    C      none of the columns A or B were used as index before executing the line creating the dictionary   Both approaches are fast  less than one second on a dataframe with 85k rows  5-year-old fast dual-core laptop    The reasons I m posting this    for those who need this kind of solution if someone knows a faster executing solution  e g   for millions of rows   I d appreciate a reply

[python] python pandas dataframe to dictionary

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