^quickmean.py
^datanums.txt
^ this is the csvsplit.py file
to or greater than 100 . 3. For the quickmean.py script modify the script to average 20 random
selected numbers instead of al the data from datanums.txt.4! /usr/bin/env python # -*_ coding: utf-
8 _*_ expects one number per line FileName="datanums.txt" Total =0 Number =0 NumberList =[]
for Item in Reader: NumberList. append(float(Item)) #print (NumberList) Total = Total + float(Item)
Number = Number +1 Reader.close() print (NumberList) print ("The mean of %d values was %.2f"
% (Number, Total/Number)) Line 1/23 Column: 1 Character 35(023) Encoding: 1252 (ANSI-La#1
/usr/bin/env python #-*-coding; utf-8 -*- ."split file and create a list FileName - "datasplit.txt" import
csv # open the FileName for reading and parse with # the CSV reader function # Default is comas,
give "excel-tab" for tabs. Eielditer = csv.reader (open(FileName, ' r '), dialect - "excel-tab') # Using
list comprehension to parse at once # could also do a for loop # This creates a list of lists Fields =
[Row for Row in Fielditer] print (Flelds).
quickmeanpy datanumstxt this is the csvsplitpy file .pdf
1. ^quickmean.py
^datanums.txt
^ this is the csvsplit.py file
to or greater than 100 . 3. For the quickmean.py script modify the script to average 20 random
selected numbers instead of al the data from datanums.txt.4! /usr/bin/env python # -*_ coding: utf-
8 _*_ expects one number per line FileName="datanums.txt" Total =0 Number =0 NumberList =[]
for Item in Reader: NumberList. append(float(Item)) #print (NumberList) Total = Total + float(Item)
Number = Number +1 Reader.close() print (NumberList) print ("The mean of %d values was %.2f"
% (Number, Total/Number)) Line 1/23 Column: 1 Character 35(023) Encoding: 1252 (ANSI-La#1
/usr/bin/env python #-*-coding; utf-8 -*- ."split file and create a list FileName - "datasplit.txt" import
csv # open the FileName for reading and parse with # the CSV reader function # Default is comas,
give "excel-tab" for tabs. Eielditer = csv.reader (open(FileName, ' r '), dialect - "excel-tab') # Using
list comprehension to parse at once # could also do a for loop # This creates a list of lists Fields =
[Row for Row in Fielditer] print (Flelds)
![^quickmean.py
^datanums.txt
^ this is the csvsplit.py file
to or greater than 100 . 3. For the quickmean.py script modify the script to average 20 random
selected numbers instead of al the data from datanums.txt.4! /usr/bin/env python # -*_ coding: utf-
8 _*_ expects one number per line FileName="datanums.txt" Total =0 Number =0 NumberList =[]
for Item in Reader: NumberList. append(float(Item)) #print (NumberList) Total = Total + float(Item)
Number = Number +1 Reader.close() print (NumberList) print ("The mean of %d values was %.2f"
% (Number, Total/Number)) Line 1/23 Column: 1 Character 35(023) Encoding: 1252 (ANSI-La#1
/usr/bin/env python #-*-coding; utf-8 -*- ."split file and create a list FileName - "datasplit.txt" import
csv # open the FileName for reading and parse with # the CSV reader function # Default is comas,
give "excel-tab" for tabs. Eielditer = csv.reader (open(FileName, ' r '), dialect - "excel-tab') # Using
list comprehension to parse at once # could also do a for loop # This creates a list of lists Fields =
[Row for Row in Fielditer] print (Flelds)](https://image.slidesharecdn.com/quickmeanpydatanumstxtthisisthecsvsplitpyfile-230320160638-f5e2af17/85/quickmeanpy-datanumstxt-this-is-the-csvsplitpy-file-pdf-1-320.jpg)
