Preface
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Introduction
The csv file is a very common data source file. Generally, when we analyze small-scale data, most of us will directly read the .csv file.
The full name of the csv file is "Comma-Separated Values", which is interpreted as comma-separated values.
When we want to read a CSV file into Python, one of the most commonly used methods is to use pd.read_csv() to read the CSV data as a DataFrame.
Environment introduction
- System environment: Windows 10
- Python version: Python 3.7
- Essential library: pandas
Core sentence
import pandas as pd
pd.read_csv('/文件路径')
Code sample
Assuming that there is a .csv file named "orange_cat" in our computer, the file is saved in the following path:
C:/Users/osc/Desktop/
We can use the following statement to import data into Python and rename it to dataSet .
# 读取电脑中的文件到Python中
dataSet = pd.read_csv("C:/Users/osc/Desktop/orange_cat.csv")
Core parameter
There are more than 30 parameters in pd.read_csv(). By configuring these parameters, you can filter and remove data at the same time during the process of reading .csv.
- The official website description of pd.read_csv() parameters:
https://pandas.pydata.org/pandas-docs/version/0.16.2/generated/pandas.read_csv.html
The following are a few core parameters of the formula, generally I only use these.
If you want to know about the remaining more than 20 parameters, it is recommended to read on the official website of pandas.