数据集条目数量统计及指定词重复次数查询方法

Hey there! Let's walk through how to solve these two common data analysis tasks using pandas (a go-to tool for working with structured data in Python):

Getting the total number of rows (entries) in your dataset is straightforward. Once you've loaded your data into a pandas DataFrame, you have two simple options:

import pandas as pd

# First, load your dataset (replace with your actual file path/loading method)
df = pd.read_csv('your_data.csv')

# Option 1: Use .shape[0] to get the row count
total_entries = df.shape[0]

# Option 2: Use len() on the DataFrame
total_entries = len(df)

print(f"Total entries in the dataset: {total_entries}")

Both methods work equally well—df.shape[0] returns the first value of the DataFrame's shape tuple (rows × columns), while len(df) directly counts the number of rows.

Let's say you have a column (like 'region') with values such as East, Northeast, West, and you want to count how many times "Northeast" appears. Here are two reliable ways to do this:

Exact match (case-sensitive by default) #

# Option 1: Use value_counts() to get counts for all values, then fetch the target
northeast_count = df['region'].value_counts().get('Northeast', 0)

# Option 2: Use boolean masking with sum() to count matches
northeast_count = (df['region'] == 'Northeast').sum()

print(f"'Northeast' appears {northeast_count} times in the 'region' column")

The .get('Northeast', 0) ensures you get 0 instead of an error if "Northeast" doesn't exist in the column.

Bonus: Case-insensitive or partial match #

If you need to count entries that contain "Northeast" (e.g., "East-Northeast") or match regardless of capitalization, use str.contains():

# Count all entries with "Northeast" (case-insensitive)
northeast_related_count = df['region'].str.contains('Northeast', case=False).sum()

print(f"Entries containing 'Northeast' (case-insensitive): {northeast_related_count}")

内容的提问来源于stack exchange，提问作者Justin Beshears