Find and replace loop in Pandas

Related searches

I have a dataframe which has a lot of characters that need changing.

I can do this line by line but I couldn't figure out how to loop through these characters to replace with a new character.

This is my code so far:

df_media_input['MediaChannel']=df_media_input['MediaChannel'].map(lambda x: str.replace(x, "Direct Mail","DM"))
df_media_input['MediaChannel']=df_media_input['MediaChannel'].map(lambda x: str.replace(x, "DR TV","DRTV"))
df_media_input['MediaChannel']=df_media_input['MediaChannel'].map(lambda x: str.replace(x, "Affilliates","Affiliates"))
df_media_input['MediaChannel']=df_media_input['MediaChannel'].map(lambda x: str.replace(x, "DRTV","TV"))
df_media_input['MediaChannel']=df_media_input['MediaChannel'].map(lambda x: str.replace(x, "All Time TV","TV"))
df_media_input['MediaChannel']=df_media_input['MediaChannel'].map(lambda x: str.replace(x, "Peak TV","TV"))
df_media_input['MediaChannel']=df_media_input['MediaChannel'].map(lambda x: str.replace(x, "Regional Press","Press"))
df_media_input['MediaChannel']=df_media_input['MediaChannel'].map(lambda x: str.replace(x, "National Press","Press"))

but I feel something like this should be possible:

dic= {Direct Mail:DM}


for i and j in dic:

df_media_input['MediaChannel']=df_media_input['MediaChannel'].map(lambda x: str.replace(x, i,j))

where Direct Mail is i and DM is j

The Pandas DataFrame replace methods accepts a dictionary where the keys correspond to existing strings and the values correspond to the string to replace each with.

So in your example:

replacements = {
    "Direct Mail": "DM",
    "DR TV": "DRTV",
    # and so on...
}

df_media_input['MediaChannel'].replace(replacements, inplace=True)

Assuming that the values in the 'MediaChannel' column are just the strings to replace and do not contain those strings. For example, "Direct Mail" will be changed to "DM", however "I like Direct Mail" will not be changed to "I like DM". To handle this case with substrings, you'll need to set the regex keyword argument of replace to True.

Replacing for loop in pandas Python search and replace, I have 2 pandas dataframes. I want to do a find and replace between 2 dataframes. In the df_find dataframe, in the current_title column, i want to  I have 2 pandas dataframes. I want to do a find and replace between 2 dataframes. In the df_find dataframe, in the current_title column, i want to search in every row for any occurrence of values from 'keywrod' column in the df_replace dataframe and if found replace it with corresponding value from 'keywordlength' column.

First create dictionary for replacing:

d = {"Direct Mail":"DM", 
     "DR TV":"DRTV",
     ...}

If want replace substrings use replace with regex=True:

df_media_input['MediaChannel'] = df_media_input['MediaChannel'].replace(d, regex=True)

If want replace values faster way use map with fillna:

df_media_input['MediaChannel'] = df_media_input['MediaChannel'].map(d)
                                     .fillna(df_media_input['MediaChannel'])

Check difference in sample:

df_media_input = pd.DataFrame({'MediaChannel':['Direct Mail','DR TV new','val']})
print (df_media_input)
  MediaChannel
0  Direct Mail
1    DR TV new
2          val

d = {"Direct Mail":"DM", "DR TV":"DRTV"}


df_media_input['MediaChannel1'] = df_media_input['MediaChannel'].replace(d, regex=True)

df_media_input['MediaChannel2'] = (df_media_input['MediaChannel'].map(d)
                                     .fillna(df_media_input['MediaChannel']))
print (df_media_input)
  MediaChannel MediaChannel1 MediaChannel2
0  Direct Mail            DM            DM
1    DR TV new      DRTV new     DR TV new
2          val           val           val

Pandas Tutorial: Replacing Values in , Matplotlib Tutorial: replace, at, loc to change values. Use at if you only need to get or set a single value in a DataFrame or Series." loc on the other hand can be used to 129 µs ± 2.1 µs per loop (mean ± std. dev. of 7 runs, 1000 loops each). Python | Pandas dataframe.replace () 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.

Since you need to iterate, you could do something like this.

for i in range(len(df)):

    d = {"Direct Mail":"DM",
         "DR TV":"DRTV",
         "DRTV":"TV",
         "All Time TV":"TV",
         "Peak TV":"TV",
         "Regional Press":"Press",
         "National Press":"Press"
     }
    for x,y in d.items(): 
        df['MediaChannel'].values[i] = df['MediaChannel'].values[i].replace(x, y)

pandas.Series.replace, See the examples section for examples of each of these. valuescalar, dict, list, str, regex, default None. Value to replace any values matching to_replace with. I have 2 pandas dataframes. I want to do a find and replace between 2 dataframes. In the df_find dataframe, in the current_title column, i want to search in every row for any occurrence of values from 'keywrod' column in the df_replace dataframe and if found replace it with corresponding value from 'keywordlength' column.

Python, n: Number of replacement to make in a single string, default is -1 which means All​. case: Takes boolean value to decide case sensitivity. Make false for case  Pandas has iterrows () function that will help you loop through each row of a dataframe. Pandas’ iterrows () returns an iterator containing index of each row and the data in each row as a Series. Since iterrows () returns iterator, we can use next function to see the content of the iterator.

Python, 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. The  Replace values given in to_replace with value. Values of the DataFrame are replaced with other values dynamically. This differs from updating with .loc or .iloc, which require you to specify a location to update with some value. Parameters to_replace str, regex, list, dict, Series, int, float, or None. How to find the values that will be replaced.

Then we’ll dig into using for loops in tandem with common Python data science libraries like numpy, pandas, and matplotlib. We’ll also take a closer look at the range() function and how it’s useful when writing for loops.

Comments
  • @fred.schwartz - If performance is important, rather use map + fillna
  • df_media_input['MediaChannel'] = df_media_input['MediaChannel'].replace(d, regex=True)
  • should the above change from Fre&d to Fred?
  • I'm getting this; error: nothing to repeat at position 0
  • what is d ? like d = {"Fre&d":"Fred"} ? Then regex=True not working
  • @fred.schwartz - Ya, I think best is create new question about it.