15 things to do with just a single line of Pandas code

Pandas is a popular library for data manipulation and analysis in Python. Here are 15 things you can do with just a single line of Pandas code.

1. Read a CSV file

import pandas as pd; 
df = pd.read_csv("filename.csv")

2. Filter rows based on a condition

df[df['column'] > 5]

3. Sort a dataframe by a column

df.sort_values('column')

4. Group rows by a column and calculate the mean of another column:

df.groupby('column1')['column2'].mean()

5. Merge two dataframes

pd.merge(df1, df2, on='column')

6. Pivot a table

import pandas as pd; 
df.pivot(index='column1', columns='column2', values='column3')

7. Reshape a dataframe

df.melt(id_vars=['column1'], value_vars=['column2', 'column3'])

8. Rename columns

df.rename(columns={'old_column': 'new_column'})

9. Drop missing values

import pandas as pd; 
df.dropna()

10. Fill missing values with a specific value

df.fillna(value=0)

11. Calculate the correlation matrix

df.corr()

12. Calculate descriptive statistics

df.describe()

13. Apply a function to each element in a column

df['column'].apply(lambda x: x**2)

14. Create a new column based on a condition

df['new_column'] = np.where(df['column'] > 5, 'yes', 'no')

15. Write a dataframe to a CSV file

df.to_csv("filename.csv", index=False)

These are just a few examples of the many things you can do with a single line of Pandas code. With its powerful data manipulation and analysis capabilities, Pandas is a great library for working with structured data in Python.

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