![]() ![]() So what do you do in a situation like this? TypeError: sequence item 3: expected str instance, int found If your list has any item that is not a string, then you will get an error. Note that this only works if you have a list of strings. ![]() In this case, the separator is the comma string “, “ and the iterable is the fruits list. Say you have a list of strings as follows: fruits = Īnd you would like to convert the list into a single string with all the items in the list separated by a comma. Let’s take another example just to make sure everything is clear. In this article, I will focus mainly on lists but the same concept applies to tuples, strings, and any iterable for that matter. This iterable will include all the words to be joined. iterable could be any iterable (lists, tuples, string…).str is a string representing the separator between the words to be joined.The general syntax of join is as follows: str.join(iterable) Join() is a method that is defined on the string class. Now that you know the answer, let me explain the join method in more detail. The correct way to achieve this is by using the join method. If that’s the case, you may want to check the following guide that explains the steps to perform the conversion.Converting a list of strings into a string is a very common operation.įor example, assume you have a list of words that that look like this: words = Īnd you want to convert this into the string: "Messi is the best soccer player" Sometimes, you may face an opposite situation, where you’ll need to convert a DataFrame to a list. Run the Python code, and you’ll get these stats: The mean price is: 480 Print ('The min price is: ' + str(min_value)) Print ('The max price is: ' + str(max_value)) Print ('The mean price is: ' + str(mean_value)) In the context of our example, you can apply the code below in order to get the mean, max and min price using Pandas: import pandas as pd įor instance, you may use Pandas to derive some statistics about your data. Once you converted your list into a DataFrame, you’ll be able to perform an assortment of operations and calculations using Pandas. Print ('products_list: ' + str(type(products_list))) DataFrame) by applying this code: import pandas as pd If needed, you may also check the type of the objects (e.g., List vs. Run the code, and you’ll get the same DataFrame: product_name price Products_list = ,]ĭf = pd.DataFrame (products_list).transpose() Therefore, the Python code to perform the conversion to a DataFrame would be: import pandas as pd Products_list = ,]Īnd this is the result that you’ll get: product_name priceĪlternatively, you may have your list of lists as follows: products_list = ,] You can then run the code below to perform the conversion to a DataFrame: import pandas as pd How would you then convert a list of lists to a DataFrame?įor instance, let’s say that you have the following list of lists: products_list = ,] ![]() This is the DataFrame that you’ll get: product_name Products_list = ĭf = pd.DataFrame (products_list, columns = ) ![]() You can then apply the following syntax in order to convert the list of products to Pandas DataFrame: import pandas as pd Let’s say that you have the following list that contains 5 products: products_list = Examples of Converting a List to Pandas DataFrame Example 1: Convert a List In the next section, you’ll see how to perform the conversion in practice. List_name = ĭf = pd.DataFrame (list_name, columns = ) You may then use this template to convert your list to a DataFrame: import pandas as pd At times, you may need to convert a list to Pandas DataFrame in Python. ![]()
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