How to create a freqeuncy table in Pandas

How to create a freqeuncy table in Pandas

To create a frequency table in Pandas, you can use the value_counts() method on a Pandas Series. This will return a Series containing the counts of each unique value in the original Series.

Here is an example:

import pandas as pd

# Create a sample Pandas Series
s = pd.Series(['apple', 'orange', 'apple', 'banana'])

# Use the value_counts() method to create a frequency table
freq_table = s.value_counts()

# Print the frequency table
print(freq_table)

This will output the following frequency table:

apple     2
banana    1
orange    1
dtype: int64

Create a frequency table for two or more columns

You can also use the crosstab() method to create a frequency table for two or more columns in a Pandas DataFrame.

This can be useful when you want to see the relationship between different variables in your data.

Here is an example:

import pandas as pd

# Create a sample Pandas DataFrame
df = pd.DataFrame({'fruit': ['apple', 'orange', 'apple', 'banana'],
                   'color': ['red', 'orange', 'green', 'yellow']})

# Use the crosstab() method to create a frequency table
freq_table = pd.crosstab(df['fruit'], df['color'])

# Print the frequency table
print(freq_table)

This will output the following frequency table:

color   green  orange  red  yellow
fruit
apple       1       0    1       0
banana      0       0    0       1
orange      0       1    0       0

In both of these examples, the frequency table shows the number of times each unique value appears in the original data.