Questions tagged [python-applymap]

44 questions
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Why apply function did not work on pandas dataframe

ct_data['IM NO'] = ct_data['IM NO'].apply(lambda x: pyffx.Integer(b'dkrya@Jppl1994', length=20).encrypt(int(x))) I am trying to encyrpt here is below head of ct_data Unnamed: 0 IM NO CT ID 0 …
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Python - Pandas - Style.ApplyMap working strange

Can anybody help me out with the following strange scenario? So I have the following Table ( Oracle ) which looks like as follows: Screenshot Going back to python, I have created the following Script. I connect to the database and afterwards I…
Paul C.
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Apply Function for Text Cleaning to Multiple Columns

I have three columns of text in my dataframe that I want to apply the same function to. Here is what I have tried below. What should I pass as a parameter to my function? def clean_columns(): df['column'] =…
codingInMyBasement
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Modifying an indexed DataFrame inside a function changes the original variable

The following script prints the same input variable input_df twice at the end - before and after df_lower has been called: import pandas as pd def df_lower(df): cols = ['col_1'] df[cols] = df[cols].applymap(lambda x: x.lower()) return…
Marek Grzenkowicz
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Why doesn't the clean-up persist?

I clean a csv table. I want to delete symbols in the ID. It looks like this: ID Address "(2 Hamburg "(3 Cologne "(4 Berlin "(5 ... I want to delete the "( The code I used Ost.applymap(lambda x: x.replace('"(', '')) when I check the csv…
Noel Harris
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Count and map number of appearances of strings

I am mapping specific keywords with text data using applymap in Python. Let's say I want to check how often the keyword "hello" matches with the text data over all rows. Applymap gives me the desired matrix outcome, however only a "True" or "False"…
XsLiar
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Get the maximum length of a word from a paragraph

I am working on a text problem where I have my pandas dataframe holding many columns out of which one consists of paragraphs. What I need in output are 3 columns as defined - Length of largest words Number of largest words (in case if there are…
sync11
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call multiple argument function in applymap in python

I wrote a function for giving colors to the variables for pandas data frame. there I used two arguments first one is variables list and another is threshold values list(i'am having only two values in the list e.g, say 30 and 50) for color the…
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Using a formatter function with pandas.DataFrame.applymap has no effect

I have the following CSV file, that I want to read and reformat with pandas:…
tmaric
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How to use applymap in python pandas dataframe to handle scale for normalization

Firstly, i apologize for a vague question . Let me explain. I have a pandas dataframe containing 2 columns namely square feet and number of bedrooms. I am trying to compute the price using linear regression and want to run the matrix to compute…
sunny
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Python replace NaN values of a field holding numeric values with empty and not single quotes which will be treated later as strings

I am uploading some data frames into snowflake cloud. I had to use the following to transform all field values into string: data = data.applymap(str) The only reason I am doing that is that without it, I will get the following error: TypeError:…
alim1990
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Python: Apply function to certain elements/cells in pandas dataframe

I Have the following table in Pandas. +--------+--------+--------+-----+ | A | B | C | D | +--------+--------+--------+-----+ | foo | b'bar0 | b'foo0 | 253 | | b'bar0 | bar | blah | 485…
valenzio
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Remove NaN from lists in Pandas dataframe

I have a dataframe whose values are lists which contains 'nan'. Is there an easy and pythonic way to remove those 'nan' values from lists within the dataframe? I have defined a function which returns a list without 'nan', but how can I apply it to…
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Apply function in python (dataframe)

I read that the apply function takes the entire series as the input and apply the custom function to that series. However I applied the below function to a col in a dataframe and it worked as if It was passing data element wise (because it was…
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