Convert Python dict into a dataframe

Question

I have a Python dictionary like the following    u 2012-06-08   388   u 2012-06-09   388   u 2012-06-10   388   u 2012-06-11   389   u 2012-06-12   389   u 2012-06-13   389   u 2012-06-14   389   u 2012-06-15   389   u 2012-06-16   389   u 2012-06-17   389   u 2012-06-18   390   u 2012-06-19   390   u 2012-06-20   390   u 2012-06-21   390   u 2012-06-22   390   u 2012-06-23   390   u 2012-06-24   390   u 2012-06-25   391   u 2012-06-26   391   u 2012-06-27   391   u 2012-06-28   391   u 2012-06-29   391   u 2012-06-30   391   u 2012-07-01   391   u 2012-07-02   392   u 2012-07-03   392   u 2012-07-04   392   u 2012-07-05   392   u 2012-07-06   392    The keys are Unicode dates and the values are integers  I would like to convert this into a pandas dataframe by having the dates and their corresponding values as two separate columns  Example  col1  Dates col2  DateValue  the dates are still Unicode and datevalues are still integers        Date         DateValue 0    2012-07-01    391 1    2012-07-02    392 2    2012-07-03    392      2012-07-04    392                                                 Any help in this direction would be much appreciated  I am unable to find resources on the pandas docs to help me with this   I know one solution might be to convert each key-value pair in this dict  into a dict so the entire structure becomes a dict of dicts  and then we can add each row individually to the dataframe  But I want to know if there is an easier way and a more direct way to do this   So far I have tried converting the dict into a series object but this doesn t seem to maintain the relationship between the columns   s    Series my dict index my dict keys

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In my case I wanted keys and values of a dict to be columns and values of DataFrame  So the only thing that worked for me was   data     adjust power    y    af policy r submix prio adjust     null     af rf info     null     bat ac    3500    bat capacity    75     columns   list data keys    values   list data values    arr len   len values   pd DataFrame np array values  dtype object  reshape 1  arr len   columns columns

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p s  in particular  I ve found Row-Oriented examples helpful  since often that how records are stored externally   https   pbpython com pandas-list-dict html

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Pass the items of the dictionary to the DataFrame constructor  and give the column names  After that parse the Date column to get Timestamp values   Note the difference between python 2 x and 3 x   In python 2 x   df   pd DataFrame data items    columns   Date    DateValue    df  Date     pd to datetime df  Date      In Python 3 x   requiring an additional  list    df   pd DataFrame list data items     columns   Date    DateValue    df  Date     pd to datetime df  Date

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As explained on another answer using pandas DataFrame   directly here will not act as you think   What you can do is use pandas DataFrame from dict with orient  index     In 7   pandas DataFrame from dict  u 2012-06-08   388   u 2012-06-09   388   u 2012-06-10   388   u 2012-06-11   389   u 2012-06-12   389          u 2012-07-05   392   u 2012-07-06   392   orient  index   columns   foo    Out 7                foo 2012-06-08  388 2012-06-09  388 2012-06-10  388 2012-06-11  389 2012-06-12  389          2012-07-05  392 2012-07-06  392

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pd DataFrame   date    dict dates keys      date value    dict dates values

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Accepts a dict as argument and returns a dataframe with the keys of the dict as index and values as a column   def dict to df d       df pd DataFrame d items        df set index 0  inplace True      return df

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The error here  is since calling the DataFrame constructor with scalar values  where it expects values to be a list dict     i e  have multiple columns    pd DataFrame d  ValueError  If using all scalar values  you must must pass an index   You could take the items from the dictionary  i e  the key-value pairs    In  11   pd DataFrame d items       or list d items    in python 3 Out 11                0    1 0   2012-07-02  392 1   2012-07-06  392 2   2012-06-29  391 3   2012-06-28  391      In  12   pd DataFrame d items    columns   Date    DateValue    Out 12             Date  DateValue 0   2012-07-02        392 1   2012-07-06        392 2   2012-06-29        391   But I think it makes more sense to pass the Series constructor   In  21   s   pd Series d  name  DateValue   Out 21   2012-06-08    388 2012-06-09    388 2012-06-10    388  In  22   s index name    Date   In  23   s reset index   Out 23             Date  DateValue 0   2012-06-08        388 1   2012-06-09        388 2   2012-06-10        388

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d     Date   list yourDict keys     Date Values   list yourDict values     df   pandas DataFrame data d    If you don t encapsulate yourDict keys   inside of list     then you will end up with all of your keys and values being placed in every row of every column  Like this   Date    0    2012-06-08  2012-06-09  2012-06-10  2012-06-1    1    2012-06-08  2012-06-09  2012-06-10  2012-06-1    2    2012-06-08  2012-06-09  2012-06-10  2012-06-1    3    2012-06-08  2012-06-09  2012-06-10  2012-06-1    4    2012-06-08  2012-06-09  2012-06-10  2012-06-1     But by adding list   then the result looks like this   Date  Date Values 0   2012-06-08          388 1   2012-06-09          388 2   2012-06-10          388 3   2012-06-11          389 4   2012-06-12          389

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Pandas have built-in function for conversion of dict to data frame      pd DataFrame from dict dictionaryObject orient  index     For your data you can convert it like below   import pandas as pd your dict  u 2012-06-08   388   u 2012-06-09   388   u 2012-06-10   388   u 2012-06-11   389   u 2012-06-12   389   u 2012-06-13   389   u 2012-06-14   389   u 2012-06-15   389   u 2012-06-16   389   u 2012-06-17   389   u 2012-06-18   390   u 2012-06-19   390   u 2012-06-20   390   u 2012-06-21   390   u 2012-06-22   390   u 2012-06-23   390   u 2012-06-24   390   u 2012-06-25   391   u 2012-06-26   391   u 2012-06-27   391   u 2012-06-28   391   u 2012-06-29   391   u 2012-06-30   391   u 2012-07-01   391   u 2012-07-02   392   u 2012-07-03   392   u 2012-07-04   392   u 2012-07-05   392   u 2012-07-06   392   your df from dict pd DataFrame from dict your dict orient  index   print your df from dict

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I have run into this several times and have an example dictionary that I created from a function get max Path     and it returns the sample dictionary    2  0 3097502930247044   3  0 4413177909384636   4  0 5197224051562838   5  0 5717654946470984   6  0 6063959031223476   7  0 6365209824708223   8  0 655918861281035   9  0 680844386645206   To convert this to a dataframe  I ran the following   df   pd DataFrame from dict get max path 2   orient    index   reset index    Returns a simple two column dataframe with a separate index   index  0 0   2   0 309750 1   3   0 441318  Just rename the columns using f rename columns   index    Column1   0   Column2    inplace True

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I think that you can make some changes in your data format when you create dictionary  then you can easily convert it to DataFrame   input   a   Dates    2012-06-08   2012-06-10    Date value   388 389     output     Date value    388  389    Dates     2012-06-08    2012-06-10      input   aframe DataFrame a    output  will be your DataFrame  You just need to use some text editing in somewhere like Sublime or maybe Excel

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This is how it worked for me     df  pd DataFrame  d keys    d values     T df columns    keys    values      call them whatever you like   I hope this helps

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This is what worked for me  since I wanted to have a separate index column  df   pd DataFrame from dict some dict  orient  index   reset index   df columns     A    B

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You can also just pass the keys and values of the dictionary to the new dataframe  like so   import pandas as pd  myDict     lt the dict from your example gt   df   pd DataFrame   df  Date     myDict keys   df  DateValue     myDict values

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When converting a dictionary into a pandas dataframe where you want the keys to be the columns of said dataframe and the values to be the row values  you can do simply put brackets around the dictionary like this    gt  gt  gt  dict      key 1    value 1    key 2    value 2    key 3    value 3    gt  gt  gt  pd DataFrame  dict         key 1     key 2     key 3 0   value 1   value 2   value 3   It s saved me some headaches so I hope it helps someone out there   EDIT  In the pandas docs one option for the data parameter in the DataFrame constructor is a list of dictionaries  Here we re passing a list with one dictionary in it

[python] Convert Python dict into a dataframe

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