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When storing data in a json object with to_json, and reading it back with read_json, rows and columns are returned sorted alphabetically. Is there a way to keep the results ordered or reorder them upon retrieval?
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Pandas. DataFrame doesn't preserve the column order when converting from a DataFrames.
To convert the object to a JSON string, then use the Pandas DataFrame. to_json() function. Pandas to_json() is an inbuilt DataFrame function that converts the object to a JSON string. To export pandas DataFrame to a JSON file, then use the to_json() function.
Use the T attribute or the transpose() method to swap (= transpose) the rows and columns of pandas. DataFrame . Neither method changes the original object but returns a new object with the rows and columns swapped (= transposed object).
No, it does not work for missing values. Then you start doing dropna or fillna on various columns that are not matching.
Let’s get right into the different methods to change the column order of a dataframe in Pandas. This is one of the simplest methods to change the order of the columns of a pandas DataFrame object. In this method, we simply pass the Python list of columns of the DataFrame in the desired order to the DataFrame object.
Pandas provide a unique method to retrieve rows from a Data frame. DataFrame.loc [] method is used to retrieve rows from Pandas DataFrame.
There you have it, working with JSON data in Pandas is not that bad and with a little creativity, you can write code to implement whatever your heart desires. Feel free to adjust the code so it doesn't save certain values or keys. The code provided is meant to serve as boilerplate for whatever JSON related problem you are dealing with.
#drop columns 'col3' and 'col4' df [df.columns[~df.columns.isin( ['col3', 'col4'])]] The following code shows how to define a new DataFrame that only keeps the “team” and “points” columns: Notice that the resulting DataFrame only keeps the two columns that we specified.
You could use orient='split', which stores the index and column information in lists, which preserve order:
In [34]: df
Out[34]:
A C B
5 0 1 2
4 3 4 5
3 6 7 8
In [35]: df.to_json(orient='split')
Out[35]: '{"columns":["A","C","B"],"index":[5,4,3],"data":[[0,1,2],[3,4,5],[6,7,8]]}'
In [36]: pd.read_json(df.to_json(orient='split'), orient='split')
Out[36]:
A C B
5 0 1 2
4 3 4 5
3 6 7 8
Just remember to use orient='split' on reading as well, or you'll get
In [37]: pd.read_json(df.to_json(orient='split'))
Out[37]:
columns data index
0 A [0, 1, 2] 5
1 C [3, 4, 5] 4
2 B [6, 7, 8] 3
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