So in python class we are going over files and exceptions but the professor didn't explain it thoroughly hence why I'm lost to what exactly it is that he wants me to do, I would appreciate any help please. I understand that he wants us to copy the table 2 example but not quite sure. Here is the question.
The file ALW.txt contains the information shown in Table 1. Write a program to use the file to produce a text file containing the information in Table 2, in which the baseball teams list W-L percentage, as well as the total percentage.
Table 1:
ALW,W,L,W-L%
----------------
Oakland Athletics,96,66
----------------------
Texas Rangers,91,72
-------------------
Los Angeles,78,84
-------------------
Seattle Mariners,71,91
-----------------------
Houston Astros,51,111
---------------------------
Table 2:
-----
**Team.........................................W L W-L%**
-----
Oakland Athletics....................96 66 0.593
--------
Texas Rangers.........................91 72 0.558
------
Los Angeles.............................78 84 0.481
--------
Seattle Mariners.......................71 91 0.438
--------
Houston Astros.......................51 111 0.315
--------
Total:........................................387 423 0.484
so I came up with this code but I don't think I'm doing it right.
fob= open("C:/Users/Manny/Documents/Chapter 5 Assignments/ALW.txt","r")
fob.readline()
print ("Total number of teams: 5 ")
print ("Teams")
Oakland_Athletics_win = 96
Texas_Rangers_win = 91
Los_Angeles_win = 78
Seattle_Mariners_win = 71
Houston_Astros_win = 51
Oakland_Athletics_lose = 66
Texas_Rangers_lose = 72
Los_Angeles_lose = 84
Seattle_Mariners_lose = 91
Houston_Astros_lose = 111
total_win = Oakland_Athletics_win + Texas_Rangers_win + Los_Angeles_win + Seattle_Mariners_win + Houston_Astros_win
total_lose = Oakland_Athletics_lose + Texas_Rangers_lose + Los_Angeles_lose + Seattle_Mariners_lose + Houston_Astros_lose
win_lose_ratio = (Oakland_Athletics_lose + Oakland_Athletics_win)
win_lose_ratio2 = Oakland_Athletics_win / win_lose_ratio
total_ratio = total_win + total_lose
total_ratio2 = total_win / total_ratio
for line in fob:
x = line.split(",")
x2 = win_lose_ratio2
print ('\t','\t','\t','\t',"Wins",'\t',"Losses",'\t','\t',"Win-Lose%")
print (x[0],'\t',x[1],'\t',x[2],'\t','\t',(x2))
print ("Total: ",'\t','\t',total_win,'\t',total_lose,'\t',total_ratio2)
He basically wants you to convert how the statistics are displayed from one file and copy it to a different file in a different format.
I'd suggest that you first read the first file line by line and then split the line with commas. Then the elements at each index of the returned array can be formatted and written to an out file in the format he wants you to.
You teacher wants you to parse the file and produce a similar result than table 2 has.
You will need to:
open the file
Go through each line until you find the first Team
Add the strings separated by commas in that line to a list
Calculate the percentages
Carry on till the end
Write everything in anew file
It's a good exercise and Python is really good doing it
Related
I have converted a PDF bank statement to a txt file. Here is a snippet of the .txt file:
15 Apr 20DDOPEN 100.00DDBENNON WATER SRVCS29.00DDBG BUSINESS106.00BPC BOB PETROL MINISTRY78.03BPC BARBARA STREAMING DATA30.50CRPAYPAL Z4J22FR450.00CRPAYNAL AAWDL4Z4J22222KHMG30.0019,028.4917 Apr 20CRCASH IN AT HSBC BANK
What is the easiest way of re-writing the text file in python to create a new line at certain points. i.e. after a number ‘xx.xx’ there in a new date such as ‘xx APR’
For example the text to become:
15 Apr 20DDOPEN 100.00
BENNON WATER SRVCS29.00
DDBG BUSINESS106.00...(etc)
I am just trying to make a PDF more readable and useful when working amongst my other files.
If you know of another PDF to txt python converter which works better, I would also be interested.
Thanks for your help
First step would be getting the text file into Python
with open(“file.txt”) as file:
data = file.read()
This next part, initially, I thought you wouldn't be able to do, but in your example, each part contains a number XX.XX The important thing to notice here is that there is a '.' in each number.
Using Python's string find command, you can iteratively look for that '.' and add a newline character two characters later. You can change my indices below to remove the DD as well if you want.
index = 0
while(index != -1):
index = data.find('.', index)
if index != -1:
data = data[:index+3] + '\n' + data[index+3:]
Then you need to write the new data back to the file.
file = open('ValidEmails.txt','w')
file.write(data)
For the given input the following should work:
import re
counter = 0
l = "15 Apr 20DDOPEN 100.00DDBENNON WATER SRVCS29.00DDBG BUSINESS106.00BPC BOB PETROL MINISTRY78.03BPC BARBARA STREAMING DATA30.50CRPAYPAL Z4J22FR450.00CRPAYNAL AAWDL4Z4J22222KHMG30.0019,028.4917 Apr 20CRCASH IN AT HSBC BANK"
nums = re.finditer("[\d]+[\.][\d]+", l)
for elem in nums:
idx = elem.span()[1] + counter
l = l[:idx] + '\n' + l[idx:]
counter += 1
print(l)
The output is:
15 Apr 20DDOPEN 100.00
DDBENNON WATER SRVCS29.00
DDBG BUSINESS106.00
BPC BOB PETROL MINISTRY78.03
BPC BARBARA STREAMING DATA30.50
CRPAYPAL Z4J22FR450.00
CRPAYNAL AAWDL4Z4J22222KHMG30.0019
,028.4917
Apr 20CRCASH IN AT HSBC BANK
Then you should easily able to write line by line to a file.
I was trying to filter some .txt files that are named after a date in YYYYMMDD format and contain some data about active regions in the Sun. I made a code that, given a date in YYYYMMDD format, can list the files that are within a time range which I expect the active region I am looking for to be and parse the information based on that entry. An example of these txts can be seen below and more information about it (if you feel curious) can be seen on SWPC website.
:Product: 0509SRS.txt
:Issued: 2012 May 09 0030 UTC
# Prepared jointly by the U.S. Dept. of Commerce, NOAA,
# Space Weather Prediction Center and the U.S. Air Force.
#
Joint USAF/NOAA Solar Region Summary
SRS Number 130 Issued at 0030Z on 09 May 2012
Report compiled from data received at SWO on 08 May
I. Regions with Sunspots. Locations Valid at 08/2400Z
Nmbr Location Lo Area Z LL NN Mag Type
1470 S19W68 284 0030 Cro 02 02 Beta
1471 S22W60 277 0120 Cso 05 03 Beta
1474 N14W13 229 0010 Axx 00 01 Alpha
1476 N11E35 181 0940 Fkc 17 33 Beta-Gamma-Delta
1477 S22E73 144 0060 Hsx 03 01 Alpha
IA. H-alpha Plages without Spots. Locations Valid at 08/2400Z May
Nmbr Location Lo
1472 S28W80 297
1475 N05W05 222
II. Regions Due to Return 09 May to 11 May
Nmbr Lat Lo
1460 N16 126
1459 S16 110
The code I am using to parse over these txt files is:
import glob
def seeker(noaa_number, t_start, path = None):
'''
This function will open an SRS file
and look for each line if the given AR
(specified by its NOAA number) is there.
If so, this function should grab the
entries and return them.
'''
#defaulting path if none is given
if path is None:
#assigning
path = 'defaultpath'
#listing the items within the directory
files = sorted(glob.glob(path+'*.txt'))
#finding the index in the list of
#the starting time
index = files.index(path+str(t_start)+'SRS.txt')
#looping over each file
for file in files[index: index+20]:
#opening file
f = open(file, 'r')
#reading the lines
text = f.readlines()
#looping over each line in the text
for line in text:
#checking if the noaa number is mentioned
#in the given line
if noaa_number in line:
#test print
print('Original line: ', line)
#slicing the text to get the column values
nbr = line[:4]
Location = line[5:11]
Lo = line[14:18]
Area = line[19:23]
Z = line[24:28]
LL = line[29:31]
NN = line[34:36]
MagType = line[37:]
#test prints
print('nbr: ', nbr)
print('location: ', Location)
print('Lo: ', Lo)
print('Area: ', Area)
print('Z: ', Z)
print('LL: ', LL)
print('NN: ', NN)
print('MagType: ', MagType)
return
I tested this and it is working but I fell a bit dumb for two reasons:
Despite these files being made following a standard, one extra space is all it takes to crash the code considering the way I am slicing the arrays by index. Is there a better option to that?
The information on tables IA and II are not relevant for me so, ideally, I would like to prevent my code to scan them. Since the number of lines on the first column varies, is it possible to tell the code when to stop reading a giving document?
Thanks for your time!
Robustness:
Instead of slicing by absolute position you could split the lines up into a list using the .split() method. This will be robust against extra spaces.
So instead of
Location = line[5:11]
Lo = line[14:18]
Area = line[19:23]
Z = line[24:28]
LL = line[29:31]
NN = line[34:36]
You could use
Location = line.split()[1]
Lo = line.split()[2]
Area = line.split()[3]
Z = line.split()[4]
LL = line.split()[5]
NN = line.split()[6]
If you wanted it to be faster you could split the list once and then just pull the relevant data from the same list rather than splitting it every time:
data = line.split()
Location = data[1]
Lo = data[2]
Area = data[3]
Z = data[4]
LL = data[5]
NN = data[6]
Stopping:
To stop it from continuing reading the file after it's passed the relevant data you could just have something that exits the loop once it no longer finds the noaa_number in the line
# In the file function but before looping through the lines.
started_reading = False ## Set this to false so
## that it doesn't exit
## before it gets to the
## relevant data
for line in text:
if noaa_number in line:
started_reading = True
## Parsing stuff
elif started_reading is True:
break # exits the loop
I have a fixed width text file that I must convert to a .csv where all numbers have to be converted to integers (no commas, dollar signs, quotes, etc). I have currently parsed the text file using plain python, but when utilizing the right package I seem to be at an impasse.
With csv, I can use writer.writerows in place of my print statement to write the output into my csv file, but the problem is that I have more columns (such as the date and time) that I must add after these rows that I cannot seem to do with csv. I also cannot seem to find a way to translate the blank columns in my text document to blank columns in output. csv seems to write in order.
I was reading the documentation on xlsxwriter and I see how you can write to individual columns with a set formatting, but I am unsure if it would work with my .csv requirement
My input text has a series of random groupings throughout the 50k line document but follows the below format
* START ******************************************************************************************************************** START *
* START ******************************************************************************************************************** START *
* START ******************************************************************************************************************** START *
1--------------------
1ANTECR09 CHEK DPCK_R_009
TRANSIT EXTRACT SUB-SYSTEM
CURRENT DATE = 08/03/2017 JOURNAL REPORT PAGE 1
PROCESS DATE =
ID = 022000046-MNT
FILE HEADER = H080320171115
+____________________________________________________________________________________________________________________________________
R T SEQUENCE CR BT A RSN ITEM ITEM CHN USER REASO
NBR NBR OR PIC NBR DB NBR NBR COD AMOUNT SERIAL IND .......FIELD.. DESCR
5,556 01 7450282689 C 538196640 9835177743 15 $9,064.81 00 CREDIT
5,557 01 7450282690 D 031301422 362313705 38 $592.35 43431 DR CR
5,558 01 7450282691 D 021309379 601298839 38 $1,491.04 44896 DR CR
5,559 01 7450282692 D 071108834 176885 38 $6,688.00 1454 DR CR
5,560 01 7450282693 D 031309123 1390001566241 38 $293.42 6878 DR CR
My code currently parses this document, pulls the date, time, and prints only the lines where the sequence number starts with 42 and the CR is "C"
lines = []
a = 'PRINT DATE:'
b = 'ARCHIVE'
c = 'PRINT TIME:'
with open(r'textfile.txt') as in_file:
for line in in_file:
values = line.split()
if 'PRINT DATE:' in line:
dtevalue = line.split(a,1)[-1].split(b)[0]
lines.append(dtevalue)
elif 'PRINT TIME:' in line:
timevalue = line.split(c,1)[-1].split(b)[0]
lines.append(timevalue)
elif (len(values) >= 4 and values[3] == 'C'
and len(values[2]) >= 2 and values[2][:2] == '41'):
print(line)
print (lines[0])
print (lines[1])
What would be the cleanest way to achieve this result, and am I headed in the right direction by writing out the parsing first or should I have just done everything within a package first?
Any help is appreciated
Edit:
the header block (between 1----------, and +___________) is repeated throughout the document, as well as different sized groupings separated by -------
--------------------
34,615 207 4100223726 C 538196620 9866597322 10 $645.49 00 CREDIT
34,616 207 4100223727 D 022000046 8891636675 31 $645.49 111583 DR ON-
--------------------
34,617 208 4100223728 C 538196620 11701364 10 $756.19 00 CREDIT
34,618 208 4100223729 D 071923828 00 54 $305.31 11384597 BAD AC
34,619 208 4100223730 D 071923828 35110011 30 $450.88 10913052 6 DR SEL
--------------------
I would recommend slicing fixed width blocks to parse through the fixed width fields. Something like the following (incomplete) code:
data = """ 5,556 01 4250282689 C 538196640 9835177743 15 $9,064.81 00
CREDIT
5,557 01 7450282690 D 031301422 362313705 38 $592.35 43431
DR CR
5,558 01 7450282691 D 021309379 601298839 38 $1,491.04 44896
DR CR
"""
# list of data layout tuples (start_index, stop_index, field name)
# TODO add missing data layout tuples
data_layout = [(0, 12, 'r_nbr'), (12, 22, 't_nbr'), (22, 39, 'seq'), (39, 42, 'cr_db')]
for line in data.splitlines():
# skip "separator" lines
# NOTE this may be an iterative process to identify these
if line.startswith('-----'):
continue
record = {}
for start_index, stop_index, name in data_layout:
record[name] = line[start_index:stop_index].strip()
# your conditional (seems inconsistent with text)
if record['seq'].startswith('42') and record['cr_db'] == 'C':
# perform any special handling for each column
record['r_nbr'] = record['r_nbr'].replace(',', '')
# TODO other special handling (like $)
print('{r_nbr},{t_nbr},{seq},{cr_db},...'.format(**record))
Output is:
5556,01,4250282689,C,...
Update based on seemingly spurious values in undefined columns
Based on the new information provided about the "spurious" columns/fields (appear only rarely), this will likely be an iterative process.
My recommendation would be to narrow (appropriately!) the width of the desired fields. For example, if spurious data is in line[12:14] above, you could change the tuple for (12, 22, 't_nbr') to (14, 22, 't_nbr') to "skip" the spurious field.
An alternative is to add a "garbage" field in the list of tuples to handle those types of lines. Wherever the "spurious" fields appear, the "garbage" field would simply consume it.
If you need these fields, the same general approach to the "garbage" field approach still applies, but you save the data.
Update based on random separators
If they are relatively consistent, I'd simply add some logic (as I did above) to "detect" the separators and skip over them.
I have 3 small sample input files (the actual files are much larger),
# File Name: books.txt
# File Format: BookID|Title
1|The Hunger Games
2|To Kill a Mockingbird
3|Pride and Prejudice
4|Animal Farm
# File Name: ratings.txt
# File Format: ReaderID|BookID|Rating
101|1|1
102|2|2
103|3|3
104|4|4
105|1|5
106|2|1
107|3|2
108|4|3
# File Name: readers.txt
# File Format: ReaderID|Gender|PostCode|PreferComms
101|M|1000|email
102|F|1001|mobile
103|M|1002|email
104|F|1003|mobile
105|M|1004|email
106|F|1005|mobile
107|M|1006|email
108|F|1007|mobile
I want to create a Python MapReduce Hadoop Streaming Job to get the following output which is the Average Rating by Title by Gender
Animal Farm F 3.5
Pride and Prejudice M 2.5
The Hunger Games M 3
To Kill a Mockingbird F 1.5
I searched this forum and someone pointed out a solution but it is for 2 input files instead of 3. I gave it a go but am stuck at the mapper part because I am not able to sort it correctly so that the reducer can appropriately recognise the 1st record for Title & Gender, then start aggregating. My mapper code below,
#!/usr/bin/env python
import sys
for line in sys.stdin:
try:
ReaderID = "-1"
BookID = "-1"
Title = "-1"
Gender = "-1"
Rating = "-1"
line = line.strip()
splits = line.split("|")
if len(splits) == 2:
BookID = splits[0]
Title = splits[1]
elif len(splits) == 3:
ReaderID = splits[0]
BookID = splits[1]
Rating = splits[2]
else:
ReaderID = splits[0]
Gender = splits[1]
print('%s\t%s\t%s\t%s\t%s' % (BookID, Title, ReaderID, Rating, Gender))
except:
pass
PS: I need to use Python and Hadoop Streaming only. Not allowed to install Python packages like Dumbo, mrjob and etc.
Appreciate your help in advance.
Thanks,
Lobbie
Went through some core Java MR and all have suggested, the three files cannot be merged together in a single map job. We have to first join the first two, and the resultant should be joined with the third one. Applying your logic for the three, does not give me good result. Hence, I tried with Pandas, and its seems to give promising result. If using pandas is not a constraint for you, please try my code. Else, we will try to join these three files with Python Dictionary and Lists.
Here is my suggested code. I have just concatenated all the input to test it. In you code, just comment my for loop (line #36) and un-comment your for loop (line #35).
import pandas as pd
import sys
input_string_book = [
"1|The Hunger Games",
"2|To Kill a Mockingbird",
"3|Pride and Prejudice",
"4|Animal Farm"]
input_string_book_df = pd.DataFrame(columns=('BookID','Title'))
input_string_rating = [
"101|1|1",
"102|2|2",
"103|3|3",
"104|4|4",
"105|1|5",
"106|2|1",
"107|3|2",
"108|4|3"]
input_string_rating_df = pd.DataFrame(columns=('ReaderID','BookID','Rating'))
input_string_reader = [
"101|M|1000|email",
"102|F|1001|mobile",
"103|M|1002|email",
"104|F|1003|mobile",
"105|M|1004|email",
"106|F|1005|mobile",
"107|M|1006|email",
"108|F|1007|mobile"]
input_string_reader_df = pd.DataFrame(columns=('ReaderID','Gender','PostCode','PreferComms'))
#for line in sys.stdin:
for line in input_string_book + input_string_rating + input_string_reader:
try:
line = line.strip()
splits = line.split("|")
if len(splits) == 2:
input_string_book_df = input_string_book_df.append(pd.DataFrame([[splits[0],splits[1]]],columns=('BookID','Title')))
elif len(splits) == 3:
input_string_rating_df = input_string_rating_df.append(pd.DataFrame([[splits[0],splits[1],splits[2]]],columns=('ReaderID','BookID','Rating')))
else:
input_string_reader_df = input_string_reader_df.append(pd.DataFrame([[splits[0],splits[1],splits[2],splits[3]]]
,columns=('ReaderID','Gender','PostCode','PreferComms')))
except:
raise
l_concat_1 = input_string_book_df.merge(input_string_rating_df,on='BookID',how='inner')
l_concat_2 = l_concat_1.merge(input_string_reader_df,on='ReaderID',how='inner')
for each_iter in l_concat_2[['BookID', 'Title', 'ReaderID', 'Rating', 'Gender']].iterrows():
print('%s\t%s\t%s\t%s\t%s' % (each_iter[1][0], each_iter[1][1], each_iter[1][2], each_iter[1][3], each_iter[1][4]))
Output
1 The Hunger Games 101 1 M
1 The Hunger Games 105 5 M
2 To Kill a Mockingbird 102 2 F
2 To Kill a Mockingbird 106 1 F
3 Pride and Prejudice 103 3 M
3 Pride and Prejudice 107 2 M
4 Animal Farm 104 4 F
4 Animal Farm 108 3 F
I'm trying to extract two ranges per line of an opened text file in python 3 by looping through.
The application has a Entry widget and the value is stored in self.search. I then loop through a text file which contains the values I want, and write out the results to self.searchresults and then display in a Textbox.
I've tried variations of the third line below but am not getting anywhere.
I want to write out characters in each line from 3:24 and 81:83 ...
for line in self.searchfile:
if self.search in line:
line = line[3:24]+[81:83]
self.searchresults.write(line+"\n")
Here's an abridged version of the text file I'm working with (original here):
! Author: Greg Thompson NCAR/RAP
! please mail corrections to gthompsn (at) ucar (dot) edu
! Date: 24 Feb 2015
! This file is continuously maintained at:
! http://www.rap.ucar.edu/weather/surface/stations.txt
!
! [... more comments ...]
ALASKA 19-SEP-14
CD STATION ICAO IATA SYNOP LAT LONG ELEV M N V U A C
AK ADAK NAS PADK ADK 70454 51 53N 176 39W 4 X T 7 US
AK AKHIOK PAKH AKK 56 56N 154 11W 14 X 8 US
AK AKUTAN PAUT 54 09N 165 36W 25 X 7 US
AK AMBLER PAFM AFM 67 06N 157 51W 88 X 7 US
AK ANAKTUVUK PASS PAKP AKP 68 08N 151 44W 642 X 7 US
AK ANCHORAGE INTL PANC ANC 70273 61 10N 150 01W 38 X T X A 5 US
You're not far off - your problem is that you need to specify what you're slicing each time you slice it:
for line in self.searchfile:
if self.search in line:
line = line[3:24] + line[81:83]
self.searchresults.write(line+"\n")
... but you'll probably want to separate the two fields with a space:
line = line[3:24] + " " + line[81:83]
However, if you find yourself using + more than once to construct a string, you should think about using Python's built-in string-formatting abilities instead (and while you're at it, you can add that newline in the same operation):
for line in self.searchfile:
if self.search in line:
formatted = "%s %s\n" % (line[3:24], line[81:83])
self.searchresults.write(formatted)