I have around 600 csv file datasets, all have the very same column names [‘DateTime’, ‘Actual’, ‘Consensus’, ‘Previous’, ‘Revised’], all economic indicators and all-time series data sets. the aim is to merge them all together in one csv file. With ‘DateTime’ as an index. The way I wanted this file to indexed in is the time line way which means
Tag: csv
Save Pandas df containing long list as csv file
I am trying to save a pandas dataframe as .csv file. Currently my code looks like this: The saving works but the problem is that the lists in my dataframe are just compressed to [first,second,…,last] and all the entries in the middle are discarded. If I just look at the original dataframe all entries are there. Is there any way
Building a function to read CSV
I am new to Python and building a function to read CSV. I am trying to use the pandas.read_csv() inside my function,and while the code gets compiled-i dont see the dataset (I know its an overkill, but am trying to learn it using a trial and error method). I expect that when i run CSV(‘abc.csv’), it should create a df
Pandas: ValueError: cannot convert float NaN to integer
I get ValueError: cannot convert float NaN to integer for following: The “x” is a column in the csv file, I cannot spot any float NaN in the file, and I don’t understand the error or why I am getting it. When I read the column as String, then it has values like -1,0,1,…2000, all look very nice int numbers
How to read .csv with a compound header into a xarray DataArray (using pandas)
Given a dataset with the following structure: Given as a .csv: Note: some values are missing, not all variables are available for all locations, timestamps are available for every record, columns may appear out of order, but timestamp is reliably the first column. I’m not sure all these aspects are relevant to an optimal solution, but there they are. I
ValueError: The number of classes has to be greater than one; got 1
I am trying to write an SVM following this tutorial but using my own data. https://pythonprogramming.net/preprocessing-machine-learning/?completed=/linear-svc-machine-learning-testing-data/ I keep getting this error: My code is: My array for features which is used for X looks like this: My array for labels used in Y looks like this: I have only used 5 sets of data so far because I knew the
Trying to ignore Nan in csv file throws a typeerror
I’m loading a local csv file that contains data. I’m trying to find the smallest float in a row thats mixed of NaN and numbers. I have tried using the numpy function called np.nanmin, but it throws: Any suggestions to why nanmin might not work? A link to the entire csv file: http://www.sharecsv.com/s/5aea6381d1debf75723a45aacd40abf8/database.csv Here is a sample of my coun_weight:
Writing To CSV file Without Line Space in Python 3
I am trying out the program for writing to a CSV file. Here’s my code: The program runs well. But in the CSV file, there is a blank newline space (without any entries) between each entry. How to eliminate that line in the resultant CSV file? Answer Recommended implementation per Python3 Documentation. https://docs.python.org/3/library/csv.html#csv.writer
Prevent pandas read_csv treating first row as header of column names
I’m reading in a pandas DataFrame using pd.read_csv. I want to keep the first row as data, however it keeps getting converted to column names. I tried header=False but this just deleted it entirely. (Note on my input data: I have a string (st = ‘n’.join(lst)) that I convert to a file-like object (io.StringIO(st)), then build the csv from that
Formatting output of CSV file in Python
I am creating a very rudimentary “Address Book” program in Python. I am grabbing contact data from a CSV file, the contents of which looks like the following example: I am trying to format the output so that it looks cleaner and more readable, i.e. everything lined up in rows and columns, like this: My current code is as follows: