Merge pull request #338 from MattHJensen/pep8-ex-e402

pep8-ex-e402 compliance

.travis.yml

@@ -12,12 +12,11 @@ install:
   - export PATH="$HOME/miniconda/bin:$PATH"
   - conda config --set always_yes yes --set changeps1 no
   - conda update conda
-  - conda create -n test-environment python=$TRAVIS_PYTHON_VERSION pytest numpy pandas
-  - conda install -n test-environment numba networkx six toolz
-  - source activate test-environment
+  - conda env create
+  - source activate taxcalc-dev
   - python setup.py install
 
 
 # command to run tests, e.g. python setup.py test
 script:
-  - python -c "import taxcalc"; py.test
+  - python -c "import taxcalc"; py.test --pep8

csv_to_ascii.py

@@ -2,44 +2,50 @@
 Turns csv output of tax calculator to ascii output with uniform columns
 and transposes data so columns are rows, rows are columns
 
-In ipython notebook, you can import this script as a module, and then use the function from the module.
+In ipython notebook, you can import this script as a module, and then use the
+function from the module.
 
 """
 
 import pandas as pd
 
+
 def ascii_output(csv_results="", ascii_results=""):
-    
+
     if csv_results == "":
         print("no csv file given!")
         exit(0)
     if ascii_results == "":
         print("no output file name given!")
         exit(0)
 
-    #list of integers corresponding to the number(s) of the row(s) in the
-    #csv file, only rows in list will be recorded in final output
-    #if left as [], results in entire file being converted to ascii
-    #put in order from smallest to largest, for example:
-    #recids = [33180, 64023, 68020, 74700, 84723, 98001, 107039, 107298, 108820]
-    recids = [1,4,5]
-
-    #Number of characters in each column, must be whole nonnegative integer
+    # list of integers corresponding to the number(s) of the row(s) in the
+    # csv file, only rows in list will be recorded in final output
+    # if left as [], results in entire file being converted to ascii
+    # put in order from smallest to largest, for example:
+    # recids = [33180, 64023, 68020, 74700, 84723, 98001, 107039, 107298,
+    #            108820]
+    recids = [1, 4, 5]
+
+    # Number of characters in each column, must be whole nonnegative integer
     col_size = 15
-    
+
     df = pd.read_csv(csv_results, dtype=object)
-    
-    #keeps only listed recid's
+
+    # keeps only listed recid's
     if recids != []:
-        f = lambda x : x - 1
-        recids = map(f, recids) #maps recids to correct index in df
+
+        def f(x):
+            return x - 1
+        recids = map(f, recids)  # maps recids to correct index in df
         df = df.ix[recids]
 
-    #does transposition
+    # does transposition
     out = df.T.reset_index()
 
-    #formats data into uniform columns
+    # formats data into uniform columns
     fstring = '{:' + str(col_size) + '}'
     out = out.applymap(fstring.format)
 
-    out.to_csv(ascii_results, header=False, index=False, delim_whitespace=True, sep='\t')
+    out.to_csv(ascii_results, header=False, index=False,
+               delim_whitespace=True, sep='\t')