Develop Reference

Python: how to fix matplotlib plotting error?

I want to make a loop to create a plot for each corresponding column in 2 different csv files such that column 1 in csv A and column 1 in csv B are plotted together with the same timestamp (pulled from another csv). I do not think I will have trouble when I modify my code to create the loop, but I have to get matplotlib to work for the first column before trying to construct a loop.
I have already tried checking to make sure that the correct data is being passed into the function and that is in the correct order. For example, I printed the zipped array as a list (t_array, b_array) and checked my csv files to verify that the data was in the correct order. I have also tried modifying the axes, ticks, and zoom to no avail. I have tried checking the helper functions which I lifted from my other projects and they all work as expected.
def double_plot():
before = read_file(r_before)
after = read_file(r_after)
time = read_file(timestamp)
if len(before) == len(after):
b_array = np.asarray(before[1])
a_array = np.asarray(after[1])
t_array = np.asarray(time[1])
plt.plot(t_array, b_array)
plt.plot(t_array, a_array)
plt.show()
else:
print(len(before))
print(len(after))
print("dimension failure")
read_file() is a helper function that reads csv files and saves the columns to dictionaries with the first column key indexed by key
"1" and so on down the columns. I know I should probably change it to index with 0 first, but this is a problem for later...
Images showing what I want the code to do and what it is doing
What I would like
What my code is actually doing
Thank you for your time. This is my first time posting so I apologize if something I did was incorrect. I did attempt to find the answer before posting.
Edits: data sample; read_file()
screenshot of excel
def read_file(read_file):
data = {}
with open(read_file, 'r') as f:
reader = csv.reader(f)
for row in reader:
col_num = 0
for col in row:
col_num += 1
if col_num in data:
data[col_num].append(col)
else:
ls = col
ls = [ls]
data[col_num] = ls
return data
edit again: ^ its much better to use pandas but I am leaving this here because its funny after seeing it done with dataframes

The arrays I was using with the plot function contained strings rather than floats.
These links explain the problem along with multiple ways to fix it:
Matplotlib y axis values are not ordered
In Python, how do I convert all of the items in a list to floats?

How to return the string of a header based on the max value of a cell in Openpyxl

Good morning guys! quick question for Openpyxl:
I am working with Python editing a xlsx document and generating various stats. Part of my script is to generate max values of a cell range :
temp_list=[]
temp_max=[]
for row in sheet.iter_rows(min_row=3, min_col=10, max_row=508, max_col=13):
print(row)
for cell in row:
temp_list.append(cell.value)
print(temp_list)
temp_max.append(max(temp_list))
temp_list=[]
I would also like to be able to print the string of the header of the column that contains the max value for the cell range desired. My data structure looks like this :
Any idea on how to do so?
Thanks!

This seems like a typical INDEX/MATCH Excel problem.
Have you tried retrieving the index for the max value in each temp_list?
You can use a function like numpy.argmax() to get the index of your max value within your "temp_list" array, then use this index to locate the header and append the string to a new list called, say, "max_headers" which contains all the header strings in order of appearance.
It would look something like this
for cell in row:
temp_list.append(cell.value)
i_max = np.argmax(temp_list)
max_headers.append(cell(row = 1, column = i_max).value)
And so on and so forth. Of course, for that to work, your temp_list should be a numpy array instead of a simple python list, and the max_headers list would have to be defined.

First, Thanks Bernardo for the hint. I found a decently working solution but still have a little issue. Perhaps someone can be of assistance.
Let me amend my initial statement : here is the code I am working with now :
temp_list=[]
headers_list=[]
for row in sheet.iter_rows(min_row=3, min_col=27, max_row=508, max_col=32): #Index starts at 1 // Here we set the rows/columns containing the data to be analyzed
for cell in row:
temp_list.append(cell.value)
for cell in row:
if cell.value == max(temp_list):
print(str(cell.column))
print(cell.value)
print(sheet.cell(row=1, column=cell.column).value)
headers_list.append(sheet.cell(row=1,column=cell.column).value)
else:
print('keep going.')
temp_list = []
This formula works, but has a little issue : If, for instance, a row has the same value twice (ie : 25,9,25,8,9), this loop will print 2 headers instead of one. My question is :
how can I get this loop to take in account only the first match of a max value in a row?

You probably want something like this:
headers = [c for c in next(ws.iter_rows(min_col=27, max_col=32, min_row=1, max_row=1, values_only=True))]
for row in ws.iter_rows(min_row=3, min_col=27, max_row=508, max_col=32, values_only=True):
mx = max(row)
idx = row.index(mx)
col = headers[idx]

Searching for specific text in csv(excel format) file

CVS Sample
So I have a csv file(sample in link above) , with variable names in row 7 and values in row 8 . The Variable all have units after them, and the values are just numbers like this :
Velocity (ft/s) Volumetric (Mgal/d Mass Flow (klb/d) Sound Speed (ft/s)
.-0l.121 1.232 1.4533434 1.233423
There are alot more variables, but basically I need some way to search in the csv file for the specefic unit groups, and then append the value associated with that in a list. For example search for text "(ft/s)", and then make a dictionary with Velocity and Sound speed as Keys, and their associated values . I am unable to do this because the csv is formatted like an excel spreadsheet, and the cells contains the whole variable name with it's unit
In the end I will have a dictionary for each unit group, and I need to do it this way because each csv file generated, the unit groups change ( ft/s becomes m/s). I also can't use excel read, because it doesn't work in IronPython.

You can use csv module to read the appropriate lines into lists.
defaultdict is a good choice for data aggregation, while variable
names and units can be easily separated by splitting on '('.
import csv
import collections
with open(csv_file_name) as fp:
reader = csv.feader(fp)
for k in range(6): # skip 6 lines
next(reader)
varnames = next(reader) # 7th line
values = next(reader) # 8th line
groups = collections.defaultdict(dict)
for i, (col, value) in enumerate(zip(varnames, values)):
if i < 2:
continue
name, units = map(str.strip, col.strip(')').split('(', 1))
groups[units][name] = float(value)
Edit: added the code to skip first two columns

I'll help with the part I think you're stuck on, which is trying to extract the units from the category. Given your data, your best bet may be to use regex, the following should work:
import re
f = open('data.csv')
# I assume the first row has the header you listed in your question
header = f.readline().split(',') #since you said its a csv
for item in header:
print re.search(r'\(.+\)', item).group()
print re.sub(r'\(.+\)', '', item)
That should print the following for you:
(ft/s)
Velocity
(Mgal/d)
Volumetric
(klb/d)
Mass Flow
(ft/s)
Sound Speed
You can modify the above to store these in a list, then iterate through them to find duplicates and merge the appropriate strings to dictionaries or whatnot.

Mapping CSV data into Python

I am new to Python, and I am trying to sort of 'migrate' a excel solver model that I have created to Python, in hopes of more efficient processing time.
I receive a .csv sheet that I use as my input for the model, it is always in the same format.
This model essentially uses 4 different metrics associated with product A, B and C, and I essentially determine how to price A, B, and C accordingly.
I am at the very nascent stage of effectively inputting this data to Python. This is what I have, and I would not be surprised if there is a better approach, so open to trying anything you veterans have to recommend!
import csv
f = open("141881.csv")
for row in csv.reader(f):
price = row[0]
a_metric1 = row[1]
a_metric2 = row[2]
a_metric3 = row[3]
a_metric4 = row[4]
b_metric1 = row[7]
b_metric2 = row[8]
b_metric3 = row[9]
b_metric4 = row[10]
c_metric1 = row[13]
c_metric2 = row[14]
c_metric3 = row[15]
c_metric4 = row[16]
The .csv file comes in the format of price,a_metric1,a_metric2,a_metric3,a_metric4,,price,b_metric1,b_metric2,b_metric3,b_metric4,price,,c_metric1,c_metric2,c_metric3,c_metric4
I skip the second and third price column as they are identical to the first one.
However when I run the python script, I get the following error:
c_metric1 = row[13]
IndexError: list index out of range
And I have no idea why this occurs, when I can see the data is there myself (in excel, this .csv file would go all the way to column Q, or what I understand as row[16].
Your help is appreciated, and any advice on my approach is more than welcomed.
Thanks in advance!

Using print() can be your friend here:
import csv
with open('141881.csv') as file_handle:
file_reader = csv.reader(file_handle)
for row in file_reader:
print(row)
The code above will print out EACH row.
To print out ONLY the first row replace the for loop with: print(file_reader.__next__()) (assuming Python3)
Printing out row(s) will allow you to see what exactly a "row" is.
P.S.
Using with is advisable because it handles the opening and closing of the file for you

Look into pandas.
Read file as:
data = pd.read_csv('141881.csv'))
to read a columns:
col = data.columns['column_name']
to read a row:
row = data.ix[row_number]

CSV Module in Python transforms a spreadsheet into a matrice : a list of list
The python module to read csv transform each line of your input into a list.
For each row, it will split the row into a list of cell.In other words, one array is composed of as many columns you have into your excel spreadsheet.
Try in terminal:
>>> f = open("141881.csv")
>>> print csv.reader(f)
>>>[["id", "name", "company", "email"],[1563, "defoe", "SuperFastCompany",],["def#superfastcie.net"],[1564, "doe", "Awsomestartup", "doe#awesomestartup"], ...]`
So that's why you iterate throught the rows of your spreadsheet assigning the value into a new variable.
I recommend you to read on basics of list manipulation.
But...
What is an IndexError? catching exception:
If one cell is empty or one row has less columns than other: it will thraw an Error. Such as you described. IndexError means Python wasn't able to find a value for this specific cell. In other words if some line of your excel spreadsheet are smaller than the other it will say there is no such value to asign and throw an Index Error. That why knowing how to catch exception could be very useful to see the problem. Try to verify that the list of each has the same lenght if not assign an empty value for example
try:
#if row has always 17 cells with values
#I can just assign it directly using a little trick
price,a_metric1,a_metric2,a_metric3,a_metric4,,price,b_metric1,b_metric2,b_metric3,b_metric4,price,c_metric1,c_metric2,c_metric3,c_metric4 = row'
except IndexError:
# if there is no 17 cells
# tell me how many cells is actually in the list
# you will see there that there less than 17 elements
print len(row)
Now you can just skip the error by assigning None value to those who don't appears in the csv file
You can read more about Catching Exception

Thanks everyone for your input - printing the results made me realize that I was getting the IndexError because of the very first row, which only had headers. Skipping that row got rid of the error.
I will look into pandas, it seems like that will be useful for the type of work I am doing.
Thanks again for all of your help, much appreciated.

CSV find max in column and append new data

I asked a question about two hours ago regarding the reading and writing of data from a website. I've spent the last two hours since then trying to find a way to read the maximum date value from column 'A' of the output, comparing that value to the refreshed website data, and appending any new data to the csv file without overriding the old ones or creating duplicates.
The code that is currently 100% working is this:
import requests
symbol = "mtgoxUSD"
url = 'http://api.bitcoincharts.com/v1/trades.csv?symbol={}'.format(symbol)
data = requests.get(url)
with open("trades_{}.csv".format(symbol), "r+") as f:
f.write(data.text)
I've tried various ways of finding the maximum value of column 'A'. I've tried a bunch of different ways of using "Dict" and other methods of sorting/finding max, and even using pandas and numpy libs. None of which seem to work. Could someone point me in the direction of a decent way to find the maximum of a column from the .csv file? Thanks!

if you have it in a pandas DataFrame, you can get the max of any column like this:
>>> max(data['time'])
'2012-01-18 15:52:26'
where data is the variable name for the DataFrame and time is the name of the column

I'll give you two answers, one that just returns the max value, and one that returns the row from the CSV that includes the max value.
import csv
import operator as op
import requests
symbol = "mtgoxUSD"
url = 'http://api.bitcoincharts.com/v1/trades.csv?symbol={}'.format(symbol)
csv_file = "trades_{}.csv".format(symbol)
data = requests.get(url)
with open(csv_file, "w") as f:
f.write(data.text)
with open(csv_file) as f:
next(f) # discard first row from file -- see notes
max_value = max(row[0] for row in csv.reader(f))
with open(csv_file) as f:
next(f) # discard first row from file -- see notes
max_row = max(csv.reader(f), key=op.itemgetter(0))
Notes:
max() can directly consume an iterator, and csv.reader() gives us an iterator, so we can just pass that in. I'm assuming you might need to throw away a header line so I showed how to do that. If you had multiple header lines to discard, you might want to use islice() from the itertools module.
In the first one, we use a "generator expression" to select a single value from each row, and find the max. This is very similar to a "list comprehension" but it doesn't build a whole list, it just lets us iterate over the resulting values. Then max() consumes the iterable and we get the max value.
max() can use a key= argument where you specify a "key function". It will use the key function to get a value and use that value to figure the max... but the value returned by max() will be the unmodified original value (in this case, a row value from the CSV). In this case, the key function is manufactured for you by operator.itemgetter()... you pass in which column you want, and operator.itemgetter() builds a function for you that gets that column.
The resulting function is the equivalent of:
def get_col_0(row):
return row[0]
max_row = max(csv.reader(f), key=get_col_0)
Or, people will use lambda for this:
max_row = max(csv.reader(f), key=lambda row: row[0])
But I think operator.itemgetter() is convenient and nice to read. And it's fast.
I showed saving the data in a file, then pulling from the file again. If you want to go through the data without saving it anywhere, you just need to iterate over it by lines.
Perhaps something like:
text = data.text
rows = [line.split(',') for line in text.split("\n") if line]
rows.pop(0) # get rid of first row from data
max_value = max(row[0] for row in rows)
max_row = max(rows, key=op.itemgetter(0))
I don't know which column you want... column "A" might be column 0 so I used 0 in the above. Replace the column number as you like.

It seems like something like this should work:
import requests
import csv
symbol = "mtgoxUSD"
url = 'http://api.bitcoincharts.com/v1/trades.csv?symbol={}'.format(symbol)
data = requests.get(url)
with open("trades_{}.csv".format(symbol), "r+") as f:
all_values = list(csv.reader(f))
max_value = max([int(row[2]) for row in all_values[1:]])
(write-out-the-value?)
EDITS: I used "row[2]" because that was the sample column I was taking max of in my csv. Also, I had to strip off the column headers, which were all text, which was why I looked at "all_values[1:]" from the second row to the end of the file.