I trying to calculate mean of one colum in a csv file.First, I read one column from .csv file and save it into a list. Next when I try to get mean it have a error
TypeError: 'builtin_function_or_method' object has no attribute '__getitem__'
my code is :
with open('XXXXXX.csv') as f:
reader = csv.DictReader(f)
for row in reader:
for (k,v) in row.items():
columns_95[k].append(v)
sVaR5 = columns_95['95%']
mean_95 = sum（sVaR5）/len(sVaR5)
and my csv looks like:
95% 99%
1.225 2.332
1.252 10.252
2.336 4.213
... ...
when I check my list, output is['1.225','1.252','2.336'] I think maybe the quote mark is the reason why my code has error. but how to fix it!Thanks!!!
sum is a function. If you want to call the function sum with the argument sVaR5, you need to write:
sum(sVaR5)
If your sVaR5 is a list of strings, you could convert them to floats for the sum:
sum(map(float, sVaR5))
If you put sum[sVaR5], Python tries to call __getitem__ on the object sum, hence the error
'builtin_function_or_method' object has no attribute '__getitem__'
Related
Seems pretty straight forward. The column contains numbers in general but for some reason, some of them have non-digit characters. I want to find all of them. I am using this code:
df_other_values.total_count.str.contains('[^0-9]')
but I get the following error:
AttributeError: Can only use .str accessor with string values, which use
np.object_ dtype in pandas
So I tried this:
df_other_values = df_other.total_countvalues
df_other_values.total_count.str.contains('[^0-9]')
but get the following error:
AttributeError: 'DataFrame' object has no attribute 'total_countvalues'
So instead of going down the rabbit hole further, I was thinking there must be a way to do this without having to change my dataframe into a np.object. Please advise.
Thanks.
I believe you need cast to strings first by astype and then filter by boolean indexing:
df1 = df[df_other_values.total_count.astype(str).str.contains('[^0-9]')]
Alternative solution with isnumeric:
df1 = df[~df_other_values.total_count.astype(str).str.isnumeric()]
I have function that returns just one list of key-value pair. How can I convert this to an actual key value or an object type so I can get each attribute from the list. For example I would like to be able to just get the time or price or any other property and not the whole list as one item.
{'time': 1512858529643, 'price': '0.00524096', 'origQty': '530.00000000'
I know it doesn't look like a list but it actually is! The function that I am calling returns this as a list. I am simply storing it to a variable and nothign else.
open_order=client.get_open_orders(symbol="BNBETH",recvWindow=1234567)
If you still have doubts. When I try to print a dictionary item like this print(open_order['time'])
I get the following error.
Traceback (most recent call last):
File "C:\Python27\python-binance-master\main.py", line 63, in <module>
print(open_order['time'])
TypeError: list indices must be integers, not str
Also If I show type it shows as list.
print(type(open_order))
So, I was able to come up with a solution, sort of... by converting the list to string and splitting at the "," character. Now I have list of items that I can actually print by selecting one print(split_order_items[5]) There has to be a better solution.
open_order=client.get_open_orders(symbol="BNBETH",recvWindow=1234567)
y=''.join(str(e)for e in open_order)
split_order_items =([x.strip() for x in y.split(',')])
print(split_order_items[5])
I was able to create a multiple list items using the above code. I just can't seem to convert it to dictionary object!
Thanks!
What you have posted is a dict, not a list. You can do something like this:
data = {'time': 1512858529643, 'price': '0.00524096', 'orderId': 7848174, 'origQty': '530.00000000'}
print(data['time']) # this gets just the time and prints it
print(data['price']) # this gets just the price and prints it
I strongly suggest reading up on the Python dict: https://docs.python.org/3/tutorial/datastructures.html#dictionaries
i have a csv file containing years of data, and i need to calculate the difference between the max date and the min date, i am facing a real problem in how can i determine the max value of dates.
So, i am doing this to convert my dates into datetime object
Temps = datetime.strptime(W['datum'][i]+' '+W['timestamp'][i],'%Y-%m-%d %H:%M:%S')
Printing this line, gives me the exact result i want, but when i try to extract the max values of these dates using this line of code :
start = max(Temps)
I got this error : datetime.strptime' object is not iterable
where am i mistaken ?
The expression
datetime.strptime(W['datum'][i]+' '+W['timestamp'][i],'%Y-%m-%d %H:%M:%S')
produces a single value (a scalar). When you assign it to Temps this variable become a scalar not a list. It contains only one value.
Then when you try to evaluate max(Temps) max is expecting to find something with multiple values as its argument but, unfortunately, it finds what Temps was assigned most recently.
This was a single value, which is not 'iterable'.
I created an HDF5 file with:
pfad = "E:\Geld\Handelssysteme\Kursdaten\Ivolatity/Daten Monatsoptionen/ODAX_alles.h5"
df.to_hdf(pfad,'df', format='table')
Now I want to read and put a portion of the table back into a dataframe without reading all of the lines in the file.
I tried
df=pandas.read_hdf('pfad', 'df', where = ['expiration<expirations[1] and expiration>=expirations[0]'])
where expirations is a list that contains datetime64[ns] values and I want to get a dataframe where the values in column "expiration" are between expirations[1] and expirations[0].
However, I get a KeyError: 'No object named df in the file'
What would the right syntax be?
The following works instead:
hdf=pandas.HDFStore(pfad)
df=hdf.select('df')
This is the part of the code that gives me a hard time:
if (id1 == id2):
idlist.append[id1]
The error:
builtins.TypeError: 'builtin_function_or_method' object is not subscriptable
the problematic line is "idlist.append[id1]"
Any idea why ? I am trying to append the value id1 hold into idlist.
Thanks !!
Lists have a method that is called append
Because it is a method you should use it like that:
.append(something)
ie. invoke (like any other func)