Convert a Pandas DataFrame to a dictionary

Question

I have a DataFrame with four columns  I want to convert this DataFrame to a python dictionary  I want the elements of first column be keys and the elements of other columns in same row be values    DataFrame          ID   A   B   C 0   p    1   3   2 1   q    4   3   2 2   r    4   0   9     Output should be like this   Dictionary     p    1 3 2    q    4 3 2    r    4 0 9

User · Answer

DataFrame to dict   converts DataFrame to dictionary   Example   gt  gt  gt  df   pd DataFrame        col1    1  2    col2    0 5  0 75    index   a    b     gt  gt  gt  df    col1  col2 a     1   0 1 b     2   0 2  gt  gt  gt  df to dict     col1     a   1   b   2    col2     a   0 5   b   0 75     See this Documentation for details

User · Answer

For my use  node names with xy positions  I found  user4179775 s answer to the most helpful   intuitive   import pandas as pd  df   pd read csv  glycolysis nodes xy tsv   sep   t    df head       nodes    x    y 0  c00033  146  958 1  c00031  601  195      xy dict list dict   i  a b   for i  a b in zip df nodes  df x df y     xy dict list   c00022    483  868     c00024    146  868           xy dict tuples dict   i  a b   for i  a b in zip df nodes  df x df y     xy dict tuples   c00022    483  868     c00024    146  868              Addendum  I later returned to this issue  for other  but related  work  Here is an approach that more closely mirrors the  excellent  accepted answer   node df   pd read csv  node prop-glycolysis tca-from pg tsv   sep   t    node df head      node  kegg id kegg cid            name  wt  vis 0  22    22       c00022   pyruvate        1   1 1  24    24       c00024   acetyl-CoA      1   1       Convert Pandas dataframe to a  list    dict    dict of  dict         Per accepted answer   node df set index  kegg cid   T to dict  list      c00022    22  22   pyruvate   1  1     c00024    24  24   acetyl-CoA   1  1           node df set index  kegg cid   T to dict  dict      c00022     kegg id   22   name    pyruvate    node   22   vis   1   wt   1     c00024     kegg id   24   name    acetyl-CoA    node   24   vis   1   wt   1            In my case  I wanted to do the same thing but with selected columns from the Pandas dataframe  so I needed to slice the columns   There are two approaches    Directly     see  Convert pandas to dictionary defining the columns used fo the key values   node df set index  kegg cid     name    wt    vis    T to dict  dict      c00022     name    pyruvate    vis   1   wt   1     c00024     name    acetyl-CoA    vis   1   wt   1              Indirectly   first  slice the desired columns data from the Pandas dataframe  again  two approaches     node df sliced   node df   kegg cid    name    wt    vis      or  node df sliced2   node df loc      kegg cid    name    wt    vis      that can then can be used to create a dictionary of dictionaries  node df sliced set index  kegg cid   T to dict  dict      c00022     name    pyruvate    vis   1   wt   1     c00024     name    acetyl-CoA    vis   1   wt   1

User · Answer

df   pd DataFrame    p  1 3 2     q  4 3 2     r  4 0 9    columns   ID   A   B   C    my dict    k list v  for k v in zip df  ID    df drop columns  ID   values   print my dict   with output   p    1  3  2    q    4  3  2    r    4  0  9

User · Answer

The to dict   method sets the column names as dictionary keys so you ll need to reshape your DataFrame slightly  Setting the  ID  column as the index and then transposing the DataFrame is one way to achieve this   to dict   also accepts an  orient  argument which you ll need in order to output a list of values for each column  Otherwise  a dictionary of the form  index  value  will be returned for each column   These steps can be done with the following line    gt  gt  gt  df set index  ID   T to dict  list     p    1  3  2    q    4  3  2    r    4  0  9       In case a different dictionary format is needed  here are examples of the possible orient arguments  Consider the following simple DataFrame    gt  gt  gt  df   pd DataFrame   a     red    yellow    blue     b    0 5  0 25  0 125     gt  gt  gt  df         a      b 0     red  0 500 1  yellow  0 250 2    blue  0 125   Then the options are as follows   dict - the default  column names are keys  values are dictionaries of index data pairs   gt  gt  gt  df to dict  dict     a    0   red   1   yellow   2   blue       b    0  0 5  1  0 25  2  0 125     list - keys are column names  values are lists of column data   gt  gt  gt  df to dict  list     a     red    yellow    blue       b    0 5  0 25  0 125     series - like  list   but values are Series   gt  gt  gt  df to dict  series     a   0       red       1    yellow       2      blue       Name  a  dtype  object      b   0    0 500       1    0 250       2    0 125       Name  b  dtype  float64    split - splits columns data index as keys with values being column names  data values by row and index labels respectively   gt  gt  gt  df to dict  split     columns     a    b      data      red   0 5     yellow   0 25     blue   0 125      index    0  1  2     records - each row becomes a dictionary where key is column name and value is the data in the cell   gt  gt  gt  df to dict  records      a    red    b   0 5       a    yellow    b   0 25       a    blue    b   0 125     index - like  records   but a dictionary of dictionaries with keys as index labels  rather than a list    gt  gt  gt  df to dict  index    0    a    red    b   0 5    1    a    yellow    b   0 25    2    a    blue    b   0 125

User · Answer

If you don t mind the dictionary values being tuples  you can use itertuples    gt  gt  gt   x 0   x 1   for x in df itertuples index False     p    1  3  2    q    4  3  2    r    4  0  9

User · Answer

Try to use Zip  df   pd read csv  file   d  dict   i  a b c    for i  a b c in zip df ID  df A df B df C    print d   Output      p    1  3  2    q    4  3  2    r    4  0  9

User · Answer

Follow these steps   Suppose your dataframe is as follows    gt  gt  gt  df    A  B  C ID 0  1  3  2  p 1  4  3  2  q 2  4  0  9  r   1  Use set index to set ID columns as the dataframe index       df set index  ID   drop True  inplace True    2  Use the orient index parameter to have the index as dictionary keys       dictionary   df to dict orient  index     The results will be as follows        gt  gt  gt  dictionary       q     A   4   B   3   D   2    p     A   1   B   3   D   2    r     A   4   B   0   D   9     3  If you need to have each sample as a list run the following code  Determine the column order  column order    A    B    C      Determine your preferred order of columns d         Initialize the new dictionary as an empty dictionary for k in dictionary      d k     dictionary k  column name  for column name in column order

User · Answer

Should a dictionary like    red    0 500    yellow    0 250   blue    0 125    be required out of a dataframe like          a      b 0     red  0 500 1  yellow  0 250 2    blue  0 125  simplest way would be to do  dict df values   working snippet below  import pandas as pd df   pd DataFrame   a     red    yellow    blue     b    0 5  0 25  0 125    dict df values

[python] Convert a Pandas DataFrame to a dictionary

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