result = pd.read_csv('examples/ex5.csv', na_values=['NULL'])
时间: 2024-05-27 10:11:36 浏览: 11
As an AI language model, I cannot execute this code as I don't have access to the file system. However, I can explain what this line of code does.
This line of code reads a CSV file named 'ex5.csv' located in the 'examples' folder and assigns the resulting DataFrame object to a variable called 'result'. The 'na_values' parameter is used to specify a list of strings that should be considered as missing values (NaN) in the DataFrame.
In this case, the string 'NULL' is specified as a missing value, so any occurrence of this string in the CSV file will be replaced with NaN in the resulting DataFrame.
相关问题
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.
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.