CODEWITHSUNDEEP
pythonpython-3.xpandas
edo101
edo101

Reputation: 639

Pandas DF Creating from Dictionary Error: ValueError: If using all scalar values, you must pass an index

Hi I am creating a Pandas DF from this peice of code:

for odfslogp_obj in odfslogs_plist:
        with zipfile.ZipFile(odfslogp_obj, mode='r') as z:
            for name in z.namelist():
                with z.open(name) as etest_zip:
                    tdict = {}
                    etestlines = [line.decode() for line in etest_zip] #change lines from log files from binary to text
                    regval_range_tup_list = list(zip([i for i,x in enumerate(etestlines) if 'Head' in x ],  [i for i,x in enumerate(etestlines) if 'BINS' in x ])) #get binval sections
                    head_siteparam_tup_list = list(zip([x.split("=")[1].replace("(",'').replace(")",'').rstrip() for x in etestlines if 'Head' in x], [x.split(":")[2].rstrip() for x in etestlines if 'SITE:PARAM_SITE:' in x])) #extract head and site:param values from bin val sections

                    print(head_siteparam_tup_list)
                    linesineed = [etestlines[range[0]:range[1]-1] for range in regval_range_tup_list]
                    reglinecount = []
                    regvals = []
                    for head_site, loclist in zip(head_siteparam_tup_list, linesineed):
                        regvals_ext = [x for x in loclist if pattern.search(x)]
                        regvaltups_list = [tuple(x.split(":")[0:2]) for x in regvals_ext]
                        regvaldict = dict(regvaltups_list)
                        df = pd.DataFrame(data=regvaldict)
                        print(df)

The Sample of output of the dictionary being used looks like this when printed:

{'1000': '1669.15', '10012': '-0.674219', '10013': '-0.260156', '1003': '9.5792', '1007': '11.9812', '1011': '27.888', '1012': '14.8333', '1014': '19.1812', '1015': '19.0396', '1024': '1352.66', '1025': '3247.63', '1026': '33.7434', '1027': '38.7566', '1030': '19.7548', '1031': '30.2201'}

As you can see they are all strings, so why is it giving me this error? And how do i fix it?

Upvotes: 0

Views: 263

Answers (2)

edo101
edo101

Reputation: 639

I found what I was looking for by using a list of dictionaries instead of passing a dictionary.

This not only helped me append different dictionaries but it streamlined the code and allowed me to create a dataframe from the aggregate list of dictionaries easily to exactly how I wanted it to look:

     for head_site, loclist in zip(head_siteparam_tup_list, linesineed):
                  
                    regvals_ext = [x for x in loclist if pattern.search(x)]
                    #print(regvals_ext)
                    regvaltups_list = [tuple(x.split(":")[0:2]) for x in regvals_ext]
                    
                    regvaldict = dict(regvaltups_list)
                    regvaltupaggr_list.append(regvaldict)
                    
                regvalfile_df = pd.DataFrame(regvaltupaggr_list)
                # print(regvalfile_df)
                regvalfile_df.to_csv(r"C:\Users\sys_nsgprobeingestio\Documents\dozie\odfs\etest\filebinval.csv", index=False)

Ouput:

1000      10012      10013     1003     1007    1011     1012     1014     1015     1024     1025     1026     1027  ...   9717   9718     9722     9723     9724     9725     9726     9727     9728     9729    9730       9912       9913
0   1665.67  -0.678906  -0.267969  9.66017  12.0638  27.728  15.2347  19.9796   19.634  1352.33  3618.55   32.843  38.1179  ...  81.58  89.88  106.239  117.136  132.556  132.944   141.92   132.76  161.551  68.6192  67.325   -0.68125  -0.27031

Upvotes: 0

Let's try
Let's try

Reputation: 1058

Check the parameter orient from .from_dict():

pd.DataFrame.from_dict(dic, orient='index')

Another option:

pd.DataFrame(dic.keys(), index = dic.values())

Output:

        0
1000    1669.15
10012   -0.674219
10013   -0.260156
...

Alternatively, if you do not want to have the keys as index:

pd.DataFrame(dic.items())

Output:

    0       1
0   1000    1669.15
1   10012   -0.674219
2   10013   -0.260156

Upvotes: 3

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