Data Analysis Online Course | Data Analytics Training in Hyderabad

1. Python Libraries for Data Analysis Python offers several powerful libraries for data analysis. Some of the most commonly used ones include: - Data Analysis Online Training Course 1. Pandas: Pandas is a powerful library for data manipulation and analysis. It provides data structures like Series and DataFrame that are ideal for working with structured data. - Key Functions: Data cleaning and preparation, Data exploration and manipulation, Grouping and aggregation ```python import pandas as pd # Creating a DataFrame df = pd.DataFrame({ 'Name': ['Alice', 'Bob', 'Charlie'], 'Age': [25, 30, 35], 'Salary': [50000, 60000, 75000] }) # Filtering data df_filtered = df[df['Age'] > 30] # Grouping and aggregation average_salary = df.groupby('Age')['Salary'].mean() - Data Analytics Training

2. ``` 2. NumPy: NumPy is a fundamental package for scientific computing with Python. It provides support for large, multi-dimensional arrays and matrices, along with mathematical functions to operate on these elements. - Key Functions: Array manipulation, Mathematical operations on arrays ```python import numpy as np # Creating a NumPy array arr = np.array([1, 2, 3, 4, 5]) # Mathematical operations mean_value = np.mean(arr) - Data Analytics Course in Hyderabad ``` 3. Matplotlib: Matplotlib is a 2D plotting library for creating static, animated, and interactive visualizations in Python. - Key Functions: Line plots, scatter plots, bar plots, Customization of plots ```python import matplotlib.pyplot as plt # Creating a simple line plot x = np.linspace(0, 2*np.pi, 100) y = np.sin(x) plt.plot(x, y) plt.xlabel('X-axis') plt.ylabel('Y-axis') plt.title('Sine Wave') plt.show() - Data Analysis Online Training Course ``` 4. Seaborn: Seaborn is a statistical data visualization library based on Matplotlib. It provides a high-level interface for drawing attractive and informative statistical graphics. - Key Functions: Stylish statistical graphics, Heatmaps, violin plots, pair plots, etc.

3. ```python import seaborn as sns # Creating a heatmap data = np.random.rand(5, 5) sns.heatmap(data, annot=True) ``` 5. Scikit-learn: Scikit-learn is a machine learning library that provides simple and efficient tools for data analysis and modeling. While it's primarily for machine learning, it includes tools for data preprocessing and model evaluation. - Data Analysis Online Course - Key Functions: Data preprocessing, Machine learning models ```python from sklearn.model_selection import train_test_split from sklearn.linear_model import LinearRegression # Splitting data into training and testing sets X_train, X_test, y_train, y_test = train_test_split(X, y, test_size=0.2) # Creating and training a linear regression model model = LinearRegression() model.fit(X_train, y_train) ``` These libraries, when used together, provide a powerful ecosystem for data analysis and visualization in Python. Depending on your specific needs, you may find other libraries like Statsmodels, SciPy, or Plotly useful as well. - Data Analytics Online Training Institute Visualpath is the Leading and Best Institute for learning Data Analytics Course inHyderabad. We provide Data Analytics Online Training, you will get the best course at an affordable cost. Attend Free Demo Call on - +91-9989971070. Visit : https://www.visualpath.in/data-analytics- online-training.html