Last, because the values in our file are delimited by commas, we use the string split method to populate our list. Įxplanation: We first open the text or csv file for read only, we then use the read() function to add the content of the file into a string object. We can use a simple list comprehension to convert it to integers. This will result in a Python list of strings. Similarly, we can also add the contents of a file into a Python: with open (file_path, 'r') as my_file: Note: unless a delimiter is specified you will get a value error: ValueError: could not convert string to float #3 Read csv or txt into list This will return the following ndarray object: We can then easily look into the array contents: print(numbers_array) Numbers_array = np.loadtxt(r'C:\WorkDir\numbers.txt', delimiter=',') Remember to import the numpy library into your namespace before invoking np.loadtxt(). We can use the numpy loadtxt() method in order to read a text or comma separated csv file into an ndarray object. Related: How to read a list into a text file with Python #2 Read text file into Numpy array # or tuple, or int if passed to the file object write function Here’s is the code in order to create the file: numbers = "0,1,2,3.5,4.5,32.1,4,2.2,4,62,1"Īside: Note that you’ll need to convert ensure that the numbers variable is a string and not a tuple or list here as other wise you will receive a type error: TypeError: write() argument must be str, not list Use the np.loadtxt() function to write your text into an array and the file object read() function to populate a Python list #1 Data PreparationĪssume that you have a text file that contains the following comma delimited values: 0,1,2,3,4,32,4,2,4,62,1 We would like to read the file contents into a Numpy array and a Python list. Here’s our task: We have a text file containing numerical data. How to Fix: TypeError: ‘numpy.Create a list or array from a text file in Python How to Fix in Python: ‘numpy.ndarray’ object is not callable The following tutorials explain how to fix other common errors in Python: Notice that we’re able to convert the revenue column from a string to a float and we don’t receive any error since we removed the dollar signs before performing the conversion. The way to resolve this error is to use the replace() function to replace the dollar signs in the revenue column with nothing before performing the conversion: #convert revenue column to floatĭf = df. We receive an error since the revenue column contains a dollar sign in the strings. ValueError : could not convert string to float: '$400.42' Now suppose we attempt to convert the revenue column from a string to a float: #attempt to convert 'revenue' from string to floatĭf = df. Suppose we have the following pandas DataFrame: import pandas as pdĭf = pd. The following example shows how to resolve this error in practice. When this occurs, you must first remove these characters from the string before converting it to a float. This error usually occurs when you attempt to convert a string to a float in pandas, yet the string contains one or more of the following: One common error you may encounter when using pandas is: ValueError : could not convert string to float: '$400.42'
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