I have read multiple posts regarding this error, but I still can’t figure it out. When I try to loop through my function: Here is the error: Answer As you stated in the comments, some of the values appeared to be floats, not strings. You will need to change it to strings before passing it to re.sub. The simplest way
Tag: pandas
Python Pandas iterate over rows and access column names
I am trying to iterate over the rows of a Python Pandas dataframe. Within each row of the dataframe, I am trying to to refer to each value along a row by its column name. Here is what I have: I used this approach to iterate, but it is only giving me part of the solution – after selecting a
Remove ‘seconds’ and ‘minutes’ from a Pandas dataframe column
Given a dataframe like: I would like to remove the ‘minutes’ and ‘seconds’ information. The following (mostly stolen from: How to remove the ‘seconds’ of Pandas dataframe index?) works okay, but it feels strange to convert a datetime to a string then back to a datetime. Is there a way to do this more directly? Answer dt.round This is how
How to automatically annotate maximum value in pyplot
I’m trying to figure out how I can automatically annotate the maximum value in a figure window. I know you can do this by manually entering in x,y coordinates to annotate whatever point you want using the .annotate() method, but I want the annotation to be automatic, or to find the maximum point by itself. Here’s my code so far:
How can I read a range(‘A5:B10’) and place these values into a dataframe using openpyxl
Being able to define the ranges in a manner similar to excel, i.e. ‘A5:B10’ is important to what I need so reading the entire sheet to a dataframe isn’t very useful. So what I need to do is read the values from multiple ranges in the Excel sheet to multiple different dataframes. or I have searched but either I have
How to drop column according to NAN percentage for dataframe?
For certain columns of df, if 80% of the column is NAN. What’s the simplest code to drop such columns? Answer You can use isnull with mean for threshold and then remove columns by boolean indexing with loc (because remove columns), also need invert condition – so <.8 means remove all columns >=0.8: Sample: If want remove columns by minimal
Singleton array array(, dtype=object) cannot be considered a valid collection
Not sure how to fix . Any help much appreciate. I saw thi Vectorization: Not a valid collection but not sure if i understood this error below : Not sure how to fix . Any help much appreciate. I saw thi Vectorization: Not a valid collection but not sure if i understood this Answer This error arises because your function
Converting a iterable of ordered dict’s to pandas dataframe
I am iterating over OrderedDict’s and want to store them as pandas dataframe. Is there a commend to do that? Currently, the code is: One row in res looks like this: OrderedDict([(‘field_id’, 1), (‘date’, datetime.date(2016, 1, 3)), (‘temp’, 30.08), (‘norm_temperature’, None), (‘prcp’, 12.8848107785339), (‘abcd’, 0.0), (‘efgh’, None), (‘ijkl’, 1.38), (‘lmno’, None), (‘poq’, None)]) I get this error: *** TypeError: data
Pandas: Pivot a DataFrame, columns to rows
I have a DataFrame defined like this: The DataFrame is now this: I want to pivot the DataFrame so that it then looks like this: I think I want to do this via pivoting, but I’ve not yet worked out how to do this using the pivot() or pivot_table()functions. How can I do this, with or without using a pivot?
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