Posts

Showing posts with the label Python CSV Files

Featured Post

Top Questions People Ask About Pandas, NumPy, Matplotlib & Scikit-learn — Answered!

Image
 Whether you're a beginner or brushing up on your skills, these are the real-world questions Python learners ask most about key libraries in data science. Let’s dive in! 🐍 🐼 Pandas: Data Manipulation Made Easy 1. How do I handle missing data in a DataFrame? df.fillna( 0 ) # Replace NaNs with 0 df.dropna() # Remove rows with NaNs df.isna(). sum () # Count missing values per column 2. How can I merge or join two DataFrames? pd.merge(df1, df2, on= 'id' , how= 'inner' ) # inner, left, right, outer 3. What is the difference between loc[] and iloc[] ? loc[] uses labels (e.g., column names) iloc[] uses integer positions df.loc[ 0 , 'name' ] # label-based df.iloc[ 0 , 1 ] # index-based 4. How do I group data and perform aggregation? df.groupby( 'category' )[ 'sales' ]. sum () 5. How can I convert a column to datetime format? df[ 'date' ] = pd.to_datetime(df[ 'date' ]) ...

How to Read CSV file Data in Python

Image
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 Sinc...