We Keep Coding

How do i find the mean

def get_mean_temperature(filename):
with open(filename) as f:
lst = f.read().splitlines()
lst.pop(0)
result = 0
count = 0
for element in lst:
count += 1
el = int(element[6:])
result += el
print(result)
mn_tem = result / count
return mmn_tem
if __name__ == "__main__":
filename = "temp_log.txt"
with open(filename, "w") as f:
f.write("DATES T.\n07-01 28.0\n08-01 33.5\n09-01 27.0\n")
mean_temperature = get_mean_temperature(filename)
print(f"{mean_temperature:.1f}")
This is the code that I am trying to solve. So what I have to do here is to find the mean of temperature that are given in the text file, which are in this case "DATES T.\n07-01 28.0\n08-01 33.5\n09-01 27.0\n"
The text is sorted by MM-DD TT.T
Please help me have this code to work

from statistics import mean
data = "DATES T.\n07-01 28.0\n08-01 33.5\n09-01 27.0\n"
temperatures = [float(item.split()[1]) for item in data.split("\n")[1:] if item]
temperatures_mean = mean(temperatures)
print(temperatures)
print(temperatures_mean)
Output:
[28.0, 33.5, 27.0]
29.5
Or, as your original function:
from statistics import mean
def get_mean_temperature(filepath):
with open(filepath, "r") as f:
data = f.read()
temperatures = [float(item.split()[1]) for item in data.split("\n")[1:] if item]
return mean(temperatures)

Python: Average Prie per Year

Would anyone be able to help me with the below? I'm trying to create a program that can open the "notepad.txt" file and calculate the average price for the month of October.
notepad.txt
10-15-2012:3.886
10-22-2012:3.756
10-29-2012:3.638
infile = open('notepad.txt', 'r')
def clean_data():
line1 = infile.readline()
split1 = line1.rstrip('\n')
items = split1[0].split('-')
del items[0]
del items[0]
master = []
master = master + split1 + items
master = list(map(float, master))
print(master)
print(total)
line1 = infile.readline()
clean_data()

this prints and returns the average
def clean_data(infile):
lines = infile.readlines()
total = 0.0
num = 0
for line in lines:
spl = line.strip().split(":")
total += float(spl[len(spl)-1])
num += 1
average = total/num
print(average)
return average

def sum_data():
n,c = 0,0
with open('notepad.txt', 'r') as infile:
x = infile.readline()
# for october 10
if x[:3]=='10-' and x[6:10]=='2010';
n += float(x[12:])
c += 1
print(n/c)

If you want to use Pandas:
from io import StringIO
import pandas as pd
notepadtxt = StringIO("""10-15-2012:3.886
10-22-2012:3.756
10-29-2012:3.638""")
df = pd.read_csv(notepadtxt, sep='\:',header=None, engine='python')
df[0] = pd.to_datetime(df[0])
df=df.set_index(0)
df.resample('M').mean().values[0][0]
Output:
3.7600000000000002

The following vanilla Python code should suffice:
infile = open('notepad.txt', 'r')
def clean_data():
data = []
for line in infile:
data.append(line.strip().split(':'))
values = []
for value in data:
values.append(float(value[1]))
avg_price = sum(values)/len(values)
print(avg_price)
clean_data()
infile.close()

Sum of a particular column in a csv file

There is a csv file, say A.csv, having content:
Place,Hotel,Food,Fare
Norway,Regal,NonVeg,5000
Poland,Jenny,Italiano,6000
Norway,Suzane,Vegeterian,4000
Norway,Regal,NonVeg,5000
I have to parse this csv and obtain an output by passing arguments in command prompt.
Example 1:
mycode.py Place
Desired output is:
Place,Fare
Norway,14000
Poland,6000
Example 2:
mycode.py Place Hotel
Desired output is:
Place,Hotel,Fare
Norway,Regal,10000
Poland,Jenny,6000
Norway,Suzane,4000
So it is clear from the above example that no matter what you pass as argument it gives you the sum of the Fare header for the common ones.
Below is my code and I am able to pass arguments and get an output, but I am stuck in sum of Fare. Can any one help me with this.
import sys
import csv
import collections
d = collections.defaultdict(list)
Data = []
Result = []
Final = []
Argvs = []
argv_len = len(sys.argv)
index = 0
input = ''
file = open('A.csv', 'rb')
try:
reader = csv.reader(file)
for row in reader:
Data.append(row)
for x in range(1, argv_len):
Argvs.append(sys.argv[x])
Argvs.append('Fare')
for input in Argvs:
for y in range(0, len(Data[0])):
if(input == Data[0][y]):
for z in range(1, len(Data)):
Result.append(Data[z][y])
break
Final.append(Result)
Result = []
New = []
NewFinal = []
for x in range(0, len(Final[0])):
for y in range(0, len(Final)):
New.append(Final[y][x])
NewFinal.append(New)
New = []
out = {}
for a in NewFinal:
out.setdefault(a[0],[]).append(int(a[-1]))
with open("output.csv", "wb") as csv_file:
writer = csv.writer(csv_file, dialect='excel', delimiter=',')
writer.writerow(Argvs)
for k,v in out.iteritems():
writer.writerow((k,sum(v)))
except Exception,e:
print str(e)
finally:
file.close()
I edit the code and tried to group it. Now I am able to get the aggregate of the Fare but not the desired output.
So when I am passing:
mycode.py Place Hotel
Instead of:
Place,Hotel,Fare
Norway,Regal,10000
Poland,Jenny,6000
Norway,Suzane,4000
I am getting:
Place,Hotel,Fare
Norway,14000
Poland,6000

Finally i managed to get my desired output.
Below i am sharing the final code. \
import sys
import csv
Data = []
Result = []
Final = []
Argvs = []
argv_len = len(sys.argv)
index = 0
input = ''
file = open('A.csv', 'rb')
try:
reader = csv.reader(file)
for row in reader:
Data.append(row)
for x in range(1, argv_len):
Argvs.append(sys.argv[x])
Argvs.append('Fare')
for input in Argvs:
for y in range(0, len(Data[0])):
if(input == Data[0][y]):
for z in range(1, len(Data)):
Result.append(Data[z][y])
break
Final.append(Result)
Result = []
New = []
NewFinal = []
for x in range(0, len(Final[0])):
for y in range(0, len(Final)):
New.append(Final[y][x])
NewFinal.append(New)
New = []
out = {}
for a in NewFinal:
count_val = a[-1]
del a[-1]
key_val = ','.join(a)
out.setdefault(key_val.strip('"'),[]).append(int(count_val))
with open("output.csv", "wb") as csv_file:
writer = csv.writer(csv_file, delimiter=',',quotechar=' ')
writer.writerow(Argvs)
for k,v in out.iteritems():
writer.writerow((k,sum(v)))
except Exception,e:
print str(e)
finally:
file.close()

Group and Check-mark using Python

I have several files, each of which has data like this (filename:data inside separated by newline):
Mike: Plane\nCar
Paula: Plane\nTrain\nBoat\nCar
Bill: Boat\nTrain
Scott: Car
How can I create a csv file using python that groups all the different vehicles and then puts a X on the applicable person, like:

Assuming those line numbers aren't in there (easy enough to fix if they are), and with an input file like following:
Mike: Plane
Car
Paula: Plane
Train
Boat
Car
Bill: Boat
Train
Scott: Car
Solution can be found here : https://gist.github.com/999481
import sys
from collections import defaultdict
import csv
# see http://stackoverflow.com/questions/6180609/group-and-check-mark-using-python
def main():
# files = ["group.txt"]
files = sys.argv[1:]
if len(files) < 1:
print "usage: ./python_checkmark.py file1 [file2 ... filen]"
name_map = defaultdict(set)
for f in files:
file_handle = open(f, "r")
process_file(file_handle, name_map)
file_handle.close()
print_csv(sys.stdout, name_map)
def process_file(input_file, name_map):
cur_name = ""
for line in input_file:
if ":" in line:
cur_name, item = [x.strip() for x in line.split(":")]
else:
item = line.strip()
name_map[cur_name].add(item)
def print_csv(output_file, name_map):
names = name_map.keys()
items = set([])
for item_set in name_map.values():
items = items.union(item_set)
writer = csv.writer(output_file, quoting=csv.QUOTE_MINIMAL)
writer.writerow( [""] + names )
for item in sorted(items):
row_contents = map(lambda name:"X" if item in name_map[name] else "", names)
row = [item] + row_contents
writer.writerow( row )
if __name__ == '__main__':
main()
Output:
,Mike,Bill,Scott,Paula
Boat,,X,,X
Car,X,,X,X
Plane,X,,,X
Train,,X,,X
Only thing this script doesn't do is keep the columns in order that the names are in. Could keep a separate list maintaining the order, since maps/dicts are inherently unordered.

Here is an example of how-to parse these kind of files.
Note that the dictionary is unordered here. You can use ordered dict (in case of Python 3.2 / 2.7) from standard library, find any available implmentation / backport in case if you have older Python versions or just save an order in additional list :)
data = {}
name = None
with open(file_path) as f:
for line in f:
if ':' in line: # we have a name here
name, first_vehicle = line.split(':')
data[name] = set([first_vehicle, ]) # a set of vehicles per name
else:
if name:
data[name].add(line)
# now a dictionary with names/vehicles is available
# let's convert it to simple csv-formatted string..
# a set of all available vehicles
vehicles = set(v for vlist in data.values()
for v in vlist)
for name in data:
name_vehicles = data[name]
csv_vehicles = ''
for v in vehicles:
if v in name_vehicles:
csv_vehicles += v
csv_vehicles += ','
csv_line = name + ',' + csv_vehicles

Assuming that the input looks like this:
Mike: Plane
Car
Paula: Plane
Train
Boat
Car
Bill: Boat
Train
Scott: Car
This python script, places the vehicles in a dictionary, indexed by the person:
#!/usr/bin/python
persons={}
vehicles=set()
with open('input') as fd:
for line in fd:
line = line.strip()
if ':' in line:
tmp = line.split(':')
p = tmp[0].strip()
v = tmp[1].strip()
persons[p]=[v]
vehicles.add(v)
else:
persons[p].append(line)
vehicles.add(line)
for k,v in persons.iteritems():
print k,v
print 'vehicles', vehicles
Result:
Mike ['Plane', 'Car']
Bill ['Boat', 'Train']
Scott ['Car']
Paula ['Plane', 'Train', 'Boat', 'Car']
vehicles set(['Train', 'Car', 'Plane', 'Boat'])
Now, all the data needed are placed in data-structures. The csv-part is left as an exercise for the reader :-)

The most elegant and simple way would be like so:
vehiclesToPeople = {}
people = []
for root,dirs,files in os.walk('/path/to/folder/with/files'):
for file in files:
person = file
people += [person]
path = os.path.join(root, file)
with open(path) as f:
for vehicle in f:
vehiclesToPeople.setdefault(vehicle,set()).add(person)
people.sort()
table = [ ['']+people ]
for vehicle,owners in peopleToVehicles.items():
table.append([('X' if p in vehiclesToPeople[vehicle] else '') for p in people])
csv = '\n'.join(','.join(row) for row in table)
You can do pprint.pprint(table) as well to look at it.

How to extract column and row in csv using python

I have this input in a file.csv
"","min","max","rainfall","days_clear"
"Missouri",-2,10,300,23
"Amsterdam",-3,5,1212,34
"LA",10,20,1000,54
I wanted to write a simple program to find the city with the lowest rainfall which is Missouri in this case. How can I do that using Python csv reader?
I can try extract the items but unfortunately the first row of the file has to be there.
I wanted to have something like count[Missouri]=300
count[Amsterdam]=1212 etc.. so that I can do a minimum and reference back to print the city.
Please advise. Thanks.

import csv
def main():
with open('file.csv', 'rb') as inf:
data = [(int(row['rainfall']), row['']) for row in csv.DictReader(inf)]
data.sort()
print data[0]
if __name__=="__main__":
main()
returns
(300, 'Missouri')

One way to do this would be to use the csv module's DictReader class to write a function to extract the column of data. DictReader will take care of handling the first row of field names automatically. The built-in min() function can then be used to determine the item with the smallest value in the column.
import csv
def csv_extract_col(csvinput, colname, key):
""" extract a named column from a csv stream into a dictionary
colname: name of columm to extract
key: name of another columm to use as keys in returned dict
"""
col = {}
for row in csv.DictReader(csvinput):
col[row[key]] = row[colname]
return col
if __name__=='__main__':
import StringIO
csvdata = """\
"","min","max","rainfall","days_clear" # field name row
"Missouri",-2,10,300,23
"Amsterdam",-3,5,1212,34
"LA",10,20,1000,54
"""
csvfile = StringIO.StringIO(csvdata)
rainfall = csv_extract_col(csvfile, 'rainfall', '')
print rainfall
# {'Amsterdam': '1212', 'LA': '1000', 'Missouri': '300'}
print min(rainfall.iteritems(), key=lambda r: float(r[1]))
# ('Missouri', '300')

import StringIO
import csv
example = """"","min","max","rainfall","days_clear"
"Missouri",-2,10,300,23
"Amsterdam",-3,5,1212,34
"LA",10,20,1000,54
"""
data_in = StringIO.StringIO(example)
#data_in = open('mycsvdata.csv')
def read_data(data_in):
reader = csv.reader(data_in)
cols = []
results = {}
for row in reader:
if not cols:
cols = row
continue
row = [ int(x) if x.lstrip('-').isdigit() else x for x in row ]
results[row[0]] = dict(zip(cols[1:],row[1:]))
return results
data = read_data(data_in)
min(data.items(),key=lambda x: x[1].get('rainfall'))
Returns
('Missouri', {'max': 10, 'days_clear': 23, 'rainfall': 300, 'min': -2})

To read from a file, you need to remove all code that deals with a string:
reader = csv.reader(open('file.csv', 'rb'))
rainfall = csv_extract_col(reader, 'rainfall', '')
Update: Sorry, it neads a bit more work than that. The first arg of csv_extract_col will be used as the first arg of csv.DictReader so (in this case) it should be an open file object, and should never be a csv.reader instance. See below:
import csv
### def csv_extract_col(csvinput, colname, key):
### exactly as provided by #martineau
if __name__ == '__main__':
import sys
filename, data_col_name, key_col_name = sys.argv[1:4]
input_file_object = open(filename, 'rb')
result_dict = csv_extract_col(input_file_object, data_col_name, key_col_name)
print result_dict
print min(result_dict.iteritems(), key=lambda r: float(r[1]))
Results:
command-prompt>\python27\python joj_csv.py joj.csv rainfall ""
{'Amsterdam': '1212', 'LA': '1000', 'Missouri': '300'}
('Missouri', '300')
command-prompt>\python27\python joj_csv.py joj.csv days_clear ""
{'Amsterdam': '34', 'LA': '54', 'Missouri': '23'}
('Missouri', '23')
Update 2 in response to comment """there must be something i missed out.. i tried.. [what looks like #martineau's function] with the above main function you define. Then in my shell, i define python rainfall "". But it gives me KeyError: 'rainfall'"""
Two possibilities:
(1) You made a mistake patching the pieces of source code together. Check your work.
(2) Your file doesn't have the expected heading row contents. Try some debugging e.g. change #martineau's code so that you can insert a print statement etc. to show what the csv.DictReader thinks about your heading row:
reader = csv.DictReader(csvinput)
print "fieldnames", reader.fieldnames
assert colname in reader.fieldnames
assert key in reader.fieldnames
for row in reader:
If you are still stuck, show us ALL of your code plus the full traceback and error message -- either edit your question or put it up on pastbin or dropbox; DON'T put it into a comment!!

My code for cases in which there are several cities having the same minimum or several cities having the same maximum:
import csv
def minmax_col(filename,key,colname):
with open(filename,'rb') as csvfile:
rid = csv.DictReader(csvfile,
fieldnames=None,
quoting=csv.QUOTE_NONNUMERIC)
mini = float('inf')
maxi = float('-inf')
limin = limax =[]
for row in rid:
if row[colname] == maxi:
limax.append(row[key])
elif row[colname] > maxi:
maxi = row[colname]
limax = [row[key]]
if row[colname] == mini:
limin.append(row[key])
elif row[colname] < mini:
mini = row[colname]
limin = [row[key]]
return (key,(maxi,limax),(mini,limin))
key = 'rainfall'
city,(Ma,liMa),(mi,limi) = minmax_col('filename.csv','',key)
print 'Cities analysed on ' + repr(key) + ' parameter :'
print 'maximum==',Ma,' cities :',', '.join(liMa)
print 'minimum==',mi,' cities :',', '.join(limi)
print
key = 'min'
city,(Ma,liMa),(mi,limi) = minmax_col('filename.csv','',key)
print 'Cities analysed on ' + repr(key) + ' parameter :'
print 'maximum==',Ma,' cities :',', '.join(liMa)
print 'minimum==',mi,' cities :',', '.join(limi)
On a file like that:
"","min","max","rainfall","days_clear"
"Missouri",-2,10,300,23
"Amsterdam",-3,5,1212,34
"Oslo",-2,8,800,12
"LA",10,20,1000,54
"Kologoro",28,45,1212,1
the result is
Cities analysed according the 'rainfall' parameter :
maximum== 1212.0 cities : Amsterdam, Kologoro
minimum== 300.0 cities : Missouri
Cities analysed according the 'min' parameter :
maximum== 28.0 cities : Kologoro
minimum== -3.0 cities : Amsterdam