pd.read_csv('examples/spx.csv', index_col=0, parse_dates=True)
时间: 2023-05-17 17:04:48 浏览: 127
这是一个 Python 中 Pandas 库中的函数,用于读取 CSV 文件并将其转换为 DataFrame 对象。其中,'examples/spx.csv' 是 CSV 文件的路径,index_col=0 表示将第一列作为索引,parse_dates=True 表示将日期数据解析为日期类型。
相关问题
pd.read_csv('examples/ex6.csv', chunksize=1000
This code reads a CSV file called 'ex6.csv' in chunks of 1000 rows at a time using pandas' `read_csv` function. This is useful when working with large datasets that may not fit into memory all at once. By reading the file in smaller chunks, we can process the data incrementally and avoid memory errors.
pd.read_csv usecol
`pd.read_csv` is a function provided by the pandas library in Python, used to read data from a CSV file into a DataFrame. The `usecols` parameter is an optional parameter that allows you to specify which columns from the CSV file you want to read.
You can pass `usecols` as an argument to `pd.read_csv` and provide it with a list of column names or column indices that you want to include in the DataFrame. For example:
```python
import pandas as pd
df = pd.read_csv('data.csv', usecols=['column1', 'column2']) # reading specific columns by name
# or
df = pd.read_csv('data.csv', usecols=[0, 1, 3]) # reading specific columns by index
```
In the above examples, only the columns specified in the `usecols` parameter will be read from the CSV file and stored in the DataFrame.
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