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I have a pandas DataFrame containing one column with multiple JSON data items as list of dicts. I want to normalize the JSON column and duplicate the non-JSON columns: # creating dataframe df_actions...
Consider a dataframe with 2 columns for easiness. The first column is id and it is the key. The second column, named code is not a key but the case of two entries having the same value is very rare....
I want to write a text file which is separated by four spaces instead of one tab: df.to_csv(file,sep= '\s\s\s\s') instead of df.to_csv(file,sep= '\t') I tried regex : df.to_csv(file,sep= r'\s...
To create a pandas dataframe from numpy I can use : columns = ['1','2'] data = np.array([[1,2] , [1,5] , [2,3]]) df_1 = pd.DataFrame(data,columns=columns) df_1 If I instead use : columns = ['1',...
Assuming I have a dataframe similar to the below, how would I get the correlation between 2 specific columns and then group by the 'ID' column? I believe the Pandas 'corr' method finds the correlatio...
This is more of a conceptual question, I do not have a specific problem. I am learning python for data analysis, but I am very familiar with R - one of the great things about R is plyr (and of course...
I have two data frames, df1 and df2. Now, df1 contains 6 records and df2 contains 4 records. I want to get the unmatched records out of it. I tried it but getting an error ValueError: Can only compare...
Formerly I had anaconda with pandas 0.18. Using the code below, I made a calculation by the function "calc_func" and assign the result to the the columns of DataFrame, say "A" and "B". df[["A", "B"]]...
My question is simple, I have a dataframe and I groupby the results based on a column and get the size like this: df.groupby('column').size() Now the problem is that I only want the ones where size...
I have a DataFrame that looks like the following: X Y Date are_equal 0 50.0 10.0 2018-08-19 False 1 NaN 10.0 2018-08-19 False 2 NaN 50.0 2018-08-1...
I have two pandas dataframes that Im trying to merge together on their ID number. However in df1 the ID is being used multiple times and in df2 it is only being used once. Therefore I want the final d...
I have the following data frame: import pandas as pd df = pd.DataFrame({ 'gene':["foo", "bar // lal", "qux", "woz"]...
In the dataframe below, I would like to eliminate the duplicate cid values so the output from df.groupby('date').cid.size() matches the output from df.groupby('date').cid.nunique(). I have looked at...
I have a dataframe where each second column name is skipped: eg Step_1. The idea is to fill unnamed columns with previous name to get: Step_2. To sum up "in" and "out" in each class, to get fi...
I have a dictionary which is dict['TimeStamp'] = [value1,value2,value3] the dict has many times stamps and each time stamp has 3 values for example I want to make panda dataframe of all values of dict...