--- /dev/null	Thu Jan 01 00:00:00 1970 +0000
+++ b/replace_NA.py	Wed Feb 12 15:44:18 2014 -0500
@@ -0,0 +1,89 @@
+#!/usr/bin/env python
+
+# Reads a tabular file and replaces a target sequence (currently 'NA') with a number in columns that have numerical values.
+# Limitations: (a) can only take input from stdin and (b) cannot specify target or replacement.
+
+import sys
+import os
+import tempfile
+
+# Constants.
+SEPARATOR = '\t'
+TARGET = 'NA'
+REPLACEMENT = -1
+# List of known numerical columns.
+NUMERICAL_COLUMNS = ['1000g2012apr_all', 'esp6500si_all']
+
+# Use tempfile to store data.
+temp_out = tempfile.NamedTemporaryFile(delete=False)
+
+# Use first line to set up data structure and identify numerical columns.
+first_line = sys.stdin.readline()
+fields = first_line.strip().split(SEPARATOR)
+numerical_cols = []
+for i, f in enumerate(fields):
+    if f in NUMERICAL_COLUMNS:
+        numerical_cols.append(i)
+
+# Data structure is a 2-element list for each fields; first element is # of string elements and second element is # of number elements.
+col_type_counts = [ [0, 0] for i in range( len(fields) ) ]
+
+# Set up function to process lines.
+def process_line_fields(fields):
+    '''
+    Process fields in a line.
+    '''
+    for i, f in enumerate(fields):
+        # Ignore targets in calculation.
+        if f == TARGET:
+            continue
+
+        # Assume it's a number.
+        type_index = 1
+        try:
+            float(f)
+        except:
+            # Not a number.
+            type_index = 0
+        col_type_counts[i][type_index] += 1
+
+
+# Process first line.
+process_line_fields(fields)
+temp_out.write(first_line)
+
+# Process N-1 lines.
+for line in sys.stdin:
+    fields = line.strip().split(SEPARATOR)
+    process_line_fields(fields)
+    temp_out.write(line)
+
+# Close temp file so that it can be read.
+temp_name = temp_out.name
+temp_out.close()
+
+# Get column type based on label or consensus.
+col_types = range(len(col_type_counts))
+for i, counts in enumerate(col_type_counts):
+    if i in numerical_cols:
+        col_type = 'number'
+    elif counts[0] > counts[1]:
+        col_type = 'string'
+    else:
+        col_type = 'number'
+    col_types[i] = col_type
+
+# Replace target in number columns.
+for line in open(temp_name, 'r'):
+    fields = line.strip().split(SEPARATOR)
+    for i, f in enumerate(fields):
+        if fields[i] == TARGET and col_types[i] == 'number':
+            fields[i] = str(REPLACEMENT)
+    print SEPARATOR.join(fields)
+
+# Clean up temp file.
+temp_out.close()
+os.unlink(temp_out.name)
+
+
+