From 5578e60639c453399bbb119b6ae50a3e343437cd Mon Sep 17 00:00:00 2001
From: perezgonzalez-irene <iregon@noc.ac.uk>
Date: Mon, 24 Feb 2020 09:44:44 +0000
Subject: [PATCH] New comments
---
reader/get_sections.py | 5 ++++-
reader/import_data.py | 3 +--
reader/read_sections.py | 2 +-
3 files changed, 6 insertions(+), 4 deletions(-)
diff --git a/reader/get_sections.py b/reader/get_sections.py
index ef43f7f..acb0f2b 100644
--- a/reader/get_sections.py
+++ b/reader/get_sections.py
@@ -6,7 +6,7 @@ Created on Tue Apr 30 09:38:17 2019
Splits string reports in sections using a data model layout.
Input and output are simple pandas dataframes, with the output dataframe
-column names being section names
+column names being the section names
To work with a pandas TextParser, loop through this module.
@@ -29,6 +29,9 @@ use, also support to chunking would make converting to series a bit dirty...
provided the section is in a sequential parsing_order group
@author: iregon
+
+Have to documents the threads approach!!!!
+
"""
import pandas as pd
diff --git a/reader/import_data.py b/reader/import_data.py
index 7ecf0c8..889c5f5 100644
--- a/reader/import_data.py
+++ b/reader/import_data.py
@@ -6,7 +6,7 @@ Created on Fri Jan 10 13:17:43 2020
FUNCTION TO PREPARE SOURCE DATA TO WHAT GET_SECTIONS() EXPECTS:
AN ITERABLE WITH DATAFRAMES
-INPUT IS EITHER NOW ONLY A FILE PATH
+INPUT IS NOW ONLY A FILE PATH. COULD OPTIONALLY GET OTHER TYPE OBJECTS...
OUTPUT IS AN ITERABLE, DEPENDING ON CHUNKSIZE BEING SET:
- a single dataframe in a list
@@ -38,7 +38,6 @@ OPTIONS IN OLD DEVELOPMENT:
import pandas as pd
import os
-import io
from .. import properties
diff --git a/reader/read_sections.py b/reader/read_sections.py
index bfaf4ae..5beab89 100644
--- a/reader/read_sections.py
+++ b/reader/read_sections.py
@@ -13,7 +13,7 @@ where appropriate and ensure its data type consistency.
Output is a dataframe with columns as follows depending on the data model
structure:
- 1) Data model with sections (1 or more): [(section0,element0),.......(sectionN,elementN)]
+ 1) Data model with sections (1 or more): [(section0,element0),.......(sectionN,elementM)]
2) Data model with no sections[element0...element1]
--
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