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changed outcols in dssp and kd outputs

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Tanushree Tunstall 2020-03-26 17:12:59 +00:00
parent 5bab99c15f
commit c0bac6fd7b
3 changed files with 14 additions and 9 deletions
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11
meta_data_analysis/kd_df.py
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@ -59,6 +59,7 @@ print('Input filename:', in_filename
, '\nInput path:', indir)
print('======================================================================')
#=======
# output
#=======
@ -111,7 +112,7 @@ print('======================================================================')
# df1: df of aa seq with index reset to start from 1 (reflective of the actual aa position in a sequence)
# Name column of wt as 'wild_type' to be the same name used in the file required for merging later.
dfSeq = pd.DataFrame({'wild_type':list(sequence)})
dfSeq = pd.DataFrame({'wild_type_kd':list(sequence)})
dfSeq.index = np.arange(1, len(dfSeq) + 1) # python is not inclusive
# df2: df of kd_values with index reset to start from offset + 1 and subsequent matched length of the kd_values
@ -122,9 +123,9 @@ dfVals.index = np.arange(offset + 1, len(dfVals) + 1 + offset)
max(dfVals['kd_values'])
min(dfVals['kd_values'])
#============
# merging dfs
#============
#===================
# concatenating dfs
#===================
# Merge the two on index (as these are now reflective of the aa position numbers): df1 and df2
# This will introduce NaN where there is missing values. In our case this will be 2 (first and last ones)
# Conveniently, the last position in this case is not part of the struc, so not much loss of info
@ -133,7 +134,7 @@ min(dfVals['kd_values'])
kd_df = pd.concat([dfSeq, dfVals], axis = 1)
#============================
# Renaming index to position
# renaming index to position
#============================
kd_df = kd_df.rename_axis('position')
kd_df.head