diff --git a/parse_stdout.py b/parse_stdout.py
deleted file mode 100644
index 659c0c0..0000000
--- a/parse_stdout.py
+++ /dev/null
@@ -1,107 +0,0 @@
-import os
-import io
-import subprocess
-import pandas as pd
-import matplotlib.pyplot as plt
-
-survey_date = '20180517'
-beach = 'Avoca'
-output_csv_dir = 'csv'
-
-las_in = 'C:/Users/z3161860/Downloads/LASTools/XXFiles/S2_Delivery/avoca_20180517.las'
-cp_in = 'C:/Users/z3161860/Downloads/LASTools/XXFiles/CC_Profiles/Avoca_profiles.csv'
-
-
-def extract_pts(las_in, cp_in, survey_date, keep_only_ground=True):
-    """Extract elevations from a las surface based on x and y coordinates.
-
-    Requires lastools in system path.
-
-    Args:
-        las_in:            input point cloud (las)
-        cp_in:             point coordinates with columns: id, x, y, z (csv)
-        survey_date:       survey date string, e.g. '19700101'
-        keep_only_ground:  only keep points classified as 'ground' (boolean)
-
-    Returns:
-        Dataframe containing input coordinates with extracted elevations
-    """
-
-    cmd = ['lascontrol', '-i', las_in, '-cp', cp_in, '-parse', 'sxyz']
-
-    if keep_only_ground == True:
-        cmd += ['-keep_class', '2']
-
-    # Call lastools
-    process = subprocess.Popen(
-        cmd, stdout=subprocess.PIPE, stderr=subprocess.PIPE)
-    stdout, stderr = process.communicate()
-    errcode = process.returncode
-
-    # Handle errors, if detected
-    if errcode != 0:
-        print("Error. lascontrol failed on {}".format(
-            os.path.basename(las_in)))
-        print(stderr.decode())
-
-    # Load result into pandas dataframe
-    df = pd.read_csv(io.BytesIO(stdout))
-
-    # Tidy up dataframe
-    df = df.drop(columns=['diff'])
-    df['lidar_z'] = pd.to_numeric(df['lidar_z'], errors='coerce')
-    df['Beach'] = beach
-    df = df[[
-        'Beach', 'ProfileNum', 'Easting', 'Northing', 'Chainage', 'lidar_z'
-    ]]
-
-    # Rename columns
-    new_names = {
-        'ProfileNum': 'Profile',
-        'lidar_z': 'Elevation_{}'.format(survey_date),
-    }
-    df = df.rename(columns=new_names)
-
-    return df
-
-
-def update_survey_output(df, output_dir):
-    """Update survey profile output csv files with current survey.
-
-    Args:
-        df:         dataframe containing current survey elevations
-        output_dir: directory where csv files are saved
-
-    Returns:
-        None
-    """
-    # Merge current survey with existing data
-    profiles = df['Profile'].unique()
-    for profile in profiles:
-        csv_name = os.path.join(output_csv_dir, profile + '.csv')
-
-        # Extract survey data for current profile
-        current_profile = df[df['Profile'] == profile]
-        try:
-            # Load existing results
-            master = pd.read_csv(csv_name)
-        except FileNotFoundError:
-            master = current_profile.copy()
-
-        # Add (or update) current survey
-        current_survey_col = df.columns[-1]
-        master[current_survey_col] = current_profile[current_survey_col]
-
-        # Export updated results
-        master.to_csv(csv_name)
-
-
-df = extract_pts(las_in, cp_in, survey_date, keep_only_ground=True)
-update_survey_output(df, output_csv_dir)
-
-
-master.shape
-
-current_profile.shape
-
-df.shape