Hello, everyone! Welcome back to My Channel Learn Now from your learning partner.In this Video, we'll be learning how to filter multiple column in an Excel file using Pandas.
To apply multiple filters at once. Let's say we want to filter our data to only show rows where the value in the 'Age' column is greater than or equal to 18, and the value in the 'Gender' column is 'Female'. To access our Excel file, simply double-click on it and it will automatically open with Microsoft Office. As you can observe, the file is already open and displays data of age and gender is visible, but no filter is applied. so let start with python, To filter both criteria simultaneously, we will execute the following code:
filtered_data equal to data age should be greater than and equal to 18 and another filter where gender is equal to Female
#Python Pandas;#Data Analysis;#Data Manipulation;#Data Cleaning;#Data Wrangling;#Data Transformation;#Data Filtering;#Data Sorting;#Data Aggregation;#Data Visualization;#Data Exploration;#Data Processing;#DataFrame;#Series;#Indexing;#Selecting Data;#Data Structures;#Data Reshaping;#Missing Data;#Data Merging;#Data Joining;#Data Concatenation;#Data Grouping;#Data Pivot;#Data Melting;#Data Stacking;#Data Unstacking;#Data Splitting;#Data Summarization;#Time Series;#DateTime Operations;#Data Analysis Tools;#Data Cleaning Techniques;#Data Transformation Methods;#Data Filtering Methods;#Data Sorting Algorithms;#Data Aggregation Functions;#Data Visualization Tools;#Data Exploration Techniques;#Data Processing Functions;#Data I/O;#Reading Data;#Writing Data;#CSV;#Excel;#SQL;#JSON;#HDF5;#SQL Database;#Data Cleaning Strategies;#Data Imputation;#Data Validation;#Data Normalization;#Data Scaling;#Data Encoding;#Data Categorization;#Data Visualization Libraries;#Matplotlib;#Seaborn;#Plotly;#Bokeh;#Data Analysis Libraries;#NumPy;#Scikit-Learn;#Statsmodels;#Time Series Analysis;#Financial Data Analysis;#Data Aggregation Techniques;#Groupby;#Resampling;#Rolling Statistics;#Window Functions;#MultiIndex;#Data Slicing;#Data Dicing;#Data Filtering Techniques;#Boolean Indexing;#Querying Data;#Data Sorting Methods;#Data Visualization Techniques;#Box Plots;#Histograms;#Scatter Plots;#Bar Charts;#Line Plots;#Heatmaps;#Pair Plots;#Time Series Plots;#Data Exploration Functions;#Summary Statistics;#Correlation Analysis;#Data Sampling;#Data Splitting Techniques;#Cross-Validation;#Train-Test Split;#Data Normalization Methods;#Data Scaling Techniques;#Categorical Data Handling;#Data Encoding Methods;#Data Analysis Best Practices
コメント