How to replace a string in a list of strings in a DataFrame (Python)?

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I have a Dataframe which consists of lists of lists in two seperate columns.

import pandas as pd
data = pd.DataFrame()
data["Website"] = [["", ""], [""], ["", "no website"]]
data["App"] = [["Ok Google", "Alexa"], ["Ok Google"], ["AOL App", "Generic Device"]]

Thats how the Dataframe looks like

I need to replace certain strings in the first column (here: "no website") with the according string in the second column (here: "Generic Device"). The replacing string has the same index in the list as the string that needs to be replaced.

What did not work so far: I tried several forms of str.replace(x,y) for lists and DataFrames and nothing worked. A simple replace(x,y) does not work as I need to replace several different strings. I think I can't get my head around the indexing thing. I already googled and stackoverflowed for two hours and haven't found a solution yet.

Many thanks in advance! Sorry for bad engrish or noob mistakes, I am still learning.


Define replacement function and use apply to vectorize

def replacements(websites, apps):
    " Substitute items in list replace_items that's found in websites "
    replace_items = ["no website", ] # can add to this list of keys 
                                     # that trigger replacement

    for i, k in enumerate(websites):
        # Check each item in website for replacement
        if k in replace_items:
            # This is an item to be replaced
            websites[i] = apps[i]  # replace with corresponding item in apps

    return websites

# Create Dataframe
websites = [["", ""], [""], ["", "no website"]]
app = [["Ok Google", "Alexa"], ["Ok Google"], ["AOL App", "Generic Device"]]
data = list(zip(websites, app))
df = pd.DataFrame(data, columns = ['Websites', 'App'])

# Perform replacement
df['Websites'] = df.apply(lambda row: replacements(row['Websites'], row['App']), axis=1)


                   Websites                        App
0   [,]         [Ok Google, Alexa]
1               []                [Ok Google]
2  [, Generic Device]  [AOL App, Generic Device]

Python, n: Number of replacement to make in a single string, default is -1 which In the following examples, the data frame used contains data of some� Python is a great language for doing data analysis, primarily because of the fantastic ecosystem of data-centric python packages. Pandas is one of those packages and makes importing and analyzing data much easier. Pandas dataframe.replace() function is used to replace a string, regex, list, dictionary, series, number etc. from a dataframe. This is a very rich function as it has many variations.

Try this,You can define replaceable values in a array and execute.

def f(x,items):
    for rep in items:
        if rep in list(x.Website):
    return x

items = ["no website"]
data = data.apply(lambda x: f(x,items),axis=1)


                     Website                        App
0   [,]         [Ok Google, Alexa]
1               []                [Ok Google]
2  [, Generic Device]  [AOL App, Generic Device]

pandas.DataFrame.replace — pandas 1.1.0 documentation, str: string exactly matching to_replace will be replaced with value Second, if regex=True then all of the strings in both lists will be interpreted as regexs� Equivalent to str.replace() or re.sub(), depending on the regex value. Parameters pat str or compiled regex. String can be a character sequence or regular expression. repl str or callable. Replacement string or a callable. The callable is passed the regex match object and must return a replacement string to be used. See re.sub(). n int, default -1 (all)

First of all, Happy Holidays!

I wasn't really sure what your expected output was and I'm not really sure what you have tried previously, but I think that this may work:

data["Website"] = data["Website"].replace("no website", "Generic Device")

I really hope this helps!

pandas.Series.str.split — pandas 1.1.0 documentation, If False , return Series/Index, containing lists of strings. Returns. Series, Index, DataFrame or MultiIndex. Type matches caller unless expand=True (see� I have a very large dataset were I want to replace strings with numbers. I would like to operate on the dataset without typing a mapping function for each key (column) in the dataset. (similar to the fillna method, but replace specific string with assosiated value).

You can create a function like this:

def f(replaced_value, col1, col2):
    def r(s):
        while replaced_value in s[col1]:
            s[col1][s[col1].index(replaced_value)] = s[col2][s[col1].index(replaced_value)]
        return s
    return r

and use apply:

df=df.apply(f("no website","Website","App"), axis=1)

Working with text data — pandas 1.1.0 documentation, Currently, the performance of object dtype arrays of strings and arrays. For backwards-compatibility, object dtype remains the default type we infer a list of strings to Or astype after the Series or DataFrame is created If you do want literal replacement of a string (equivalent to str.replace() ), you can set the optional regex� Replace the two first occurrence of the word "one": txt = "one one was a race horse, two two was one too." x = txt.replace ("one", "three", 2)

Python Strings: Replace, Join, Split, Reverse, Uppercase & Lowercase, var = "Hello World!" In this tutorial, we will learn -. Accessing Values in Strings; Various String Operators; Some more examples; Python String� Before calling .replace() on a Pandas series, .str has to be prefixed in order to differentiate it from the Python’s default replace method. Syntax: Series.str.replace(pat, repl, n=-1, case=None, regex=True) Parameters: pat: string or compiled regex to be replaced repl: string or callabe to replace instead of pat

Python Replace Comma With Space In List, Python: Replacing strings in a list with values from a dictionary. In this tutorial, we will learn how to split a string by comma , in Python using String. GroupBy Value in DataFrame and getting a list of words seperated by comma Hot but maybe a comma if converting to a CSV file)? Ideally, the Python program would not� If this is True then to_replace must be a string. Alternatively, this could be a regular expression or a list, dict, or array of regular expressions in which case to_replace must be None. method {‘pad’, ‘ffill’, ‘bfill’, None} The method to use when for replacement, when to_replace is a scalar, list or tuple and value is None.

How can I replace values with 'none' in a dataframe using pandas , How can I replace values with 'none' in a dataframe using pandas. +2 votes You can do it by passing either a list or a dictionary: In [11]: How can I write code to find a palindrome in python without using string functions? The 'string' extension type solves several issues with object-dtype NumPy arrays: 1) You can accidentally store a mixture of strings and non-strings in an object dtype array. A StringArray can only store strings. 2) object dtype breaks dtype-specific operations like DataFrame.select_dtypes().

  • hey Max, are you able to show your intended output?
  • @all: Thank you very much! All your codes worked on my sample data, but not when I integrate it into my own script. I have to find out why, but that's beyond the scope of this question.