PythonPythonPerformance
Data Analysis with Python and Pandas
Learn how to load, clean, transform, and visualize data using Pandas and Matplotlib in Python.
Apr 6, 20269 min read6,700 views1280 words
Loading Data
PY
| 1 | import pandas as pd |
| 2 | import matplotlib.pyplot as plt |
| 3 | |
| 4 | df = pd.read_csv('data.csv') |
| 5 | print(df.head()) |
| 6 | print(df.describe()) |
Data Cleaning
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| 1 | # Drop missing values |
| 2 | df.dropna(subset=['email'], inplace=True) |
| 3 | |
| 4 | # Convert types |
| 5 | df['created_at'] = pd.to_datetime(df['created_at']) |
| 6 | |
| 7 | # Remove duplicates |
| 8 | df.drop_duplicates(subset=['id'], inplace=True) |