Showing posts with the label Python Text Files

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How to Check Column Nulls and Replace: Pandas

Here is a post that shows how to count Nulls and replace them with the value you want in the Pandas Dataframe. We have explained the process in two steps - Counting and Replacing the Null values. Count null values (column-wise) in Pandas ## count null values column-wise null_counts = df.isnull(). sum() print(null_counts) ``` Output: ``` Column1    1 Column2    1 Column3    5 dtype: int64 ``` In the above code, we first create a sample Pandas DataFrame `df` with some null values. Then, we use the `isnull()` function to create a DataFrame of the same shape as `df`, where each element is a boolean value indicating whether that element is null or not. Finally, we use the `sum()` function to count the number of null values in each column of the resulting DataFrame. The output shows the count of null values column-wise. to count null values column-wise: ``` df.isnull().sum() ``` ##Code snippet to count null values row-wise: ``` df.isnull().sum(axis=1) ``` In the above code, `df` is the Panda

How to Read CSV file Data in Python

Here is a way to read  CSV files  in Python pandas. The packages you need to import are numpy and pandas. On the flip side, f or Text files, you don't need to import these special libraries since python by default support it. Python pandas read_csv >>> import numpy as np >>> import pandas as pd To see how pandas handle this kind of data, we'll create a small CSV file in the working directory as ch05_01.csv. white, red, blue, green, animal 1,5,2,3,cat  2,7,8,5,dog  3,3,6,7,horse  2,2,8,3,duck  4,4,2,1,mouse Since this file is comma-delimited , you can use the read_csv() function to read its content and convert it to a dataframe object. >>> csvframe = pd.read_csv('ch05_01.csv') >>> csvframe white red blue green animal 0 1 5 2 3 cat 1 2 7 8 5 dog 2 3 3 6 7 horse 3 2 2 8 3 duck 4 4 4 2 1 mouse Python reading text files Since python supp