this is a part of my OCR code. This part looks for a special word in a scanned PDF and prints this out. I have like 10 Queries like this and all print me the word I am looking for. Now I want to get the found words saved in a CSV, but I don’t know how to do that.
Tag: pandas
Create a customised pandas dataframe from items in a dictionary
I want to create a customised pandas DataFrame from items in dictionary. For example I can convert a dictionary to a DataFrame using pandas’ from_dict() function: To produce a DataFrame such as below: However what I want is to have only 2 columns, such as below, where the word column returns the dictionary keys and count column returns a count
how to ignore null values in DataFrame when comparing columns
I am new to Pandas and learning. I am reading excel to DataFrame and comparing columns and highlight the column that’s not same. For example if Column A is not same as Column B then highlight the Column B. However I have some null values in Column A and Column B. When I execute the code, I don’t want to
Create a dataframe based on 3 linked dataframes using a constraint on cumsum
I do have three dataframes like this: that looks as follows and I would like to create another dataframe using these 3 dataframes that looks as follows: Here is the logic for C1: First, one checks the first value in column C1 in df3 which is an a. Second, one checks in df2 where one first finds the letter determined
df.explode() function not working in python
I am facing a weird issue, I have a column name ‘window’ in a data frame and it has a list of values i.e., [3,9,45,78]. I am trying to explode this column using df.explode(‘window’) but this is doing no job. datatype of ‘window’ column is object. I have checked my pandas version it is – 1.3.4 dataframe example Answer Remember
How to get the average of average of a column of list of lists as string data type?
I have a dataframe with a column like this: It shows the probability of one word in one sentence in one paragraph, the number of words and sentences is random. I would like to get another column average_prob that is the average of the average of each row. so basically 0.225 and 0.25 here. The data type of column word_probs
How can convert struct column timestamp with start and end into normal pythonic stamp column?
I have a time-series pivot table with struct timestamp column including start and end of time frame of records as follow: Since later I will use timestamps as the index for time-series analysis, I need to convert it into timestamps with just end/start. I have tried to find the solution using regex maybe unsuccessfully based on this post as follows:
Python – Write a row into an array into a text file
I have to work on a flat file (size > 500 Mo) and I need to create to split file on one criterion. My original file as this structure (simplified): JournalCode|JournalLib|EcritureNum|EcritureDate|CompteNum| I need to create to file depending on the first digit from ‘CompteNum’. I have started my code as well It seems ok, my concern is to create my
Python Dataframe – only keep oldest records from each month
I have a Pandas Dataframe with a date column. I want to only have the oldest records for each month and remove any records that came before. There will be duplicates and I want to keep them. I also need a new column with only the month and year. Input Provider date Apple 01/01/2022 Apple 05/01/2022 Apple 20/01/2022 Apple 20/01/2022
Dropping duplicate rows ignoring case (lowercase or Uppercase)
I have a data frame with one column (col). I’m trying to remove duplicate records regardless of lowercase or Uppercase, for example output: Expected Output: How can this Dropping be done regardless of case-insensitively? Answer You could use: output: