Shulou(Shulou.com)06/01 Report--

This article will explain in detail how to input and output data in pandas. The editor thinks it is very practical, so I share it for you as a reference. I hope you can get something after reading this article.

1. Reading and writing of text format data

Read_csv (): reads delimited data from a file, URL, or file object, with a comma as the default delimiter

Read_table (): reads delimited data from a file, URL, or file object, with tabs ('\ t') as the default delimiter

Windows users print the original contents of the file

Because this file is comma-separated, we can use read_csv to read it into a DataFrame:

You can also use read_table and specify a delimiter

Just now the file contains the header line, but some files do not contain the header row, such as

If you read it directly, the first row is used as the table header by default, that is, the default header=0, which represents the first behavior header row.

There are two ways to change.

One is to allow pandas to automatically assign default column names.

The second is to specify the column name yourself.

Suppose you want the message column to be the index that returns DataFrame, you can specify the column index at location 4, or pass' message' to the parameter index_col:

Form a hierarchical index from multiple columns

Parsing functions have many additional parameters to handle various exception file formats. For example, you can use skiprows to skip the first, third, and fourth lines.

Dealing with missing values

Typically, missing values are either not displayed (an empty string or with some identification value)

By default, pandas uses some common logos, such as NaN and NULL

The na_values option can be passed in a list or a set of strings to handle missing values

In the dictionary, each column can specify a different missing value identity

1.1 read text files in chunks

If you want to read only a small portion (avoid reading the whole file), you can specify nrows

To read the file in chunks, you can specify chunksize as the number of lines for each block

The TextParser object returned by read_csv allows you to traverse the file according to chunksize and aggregate the'a 'column to get the count value

1.2 write data to text format

Using DataFrame's to_csv method, you can export data as a comma-delimited file

By default, both row and column labels are written if no other option is specified, but both can also be disabled.

Or you can just write to a subset of the columns and write in the order in which you choose

The default missing value appears as an empty string on output, and can be marked with other identification values.

(the result of the text printed in the console when written to sys.stdout)

The default delimiter is a comma, which can be selected with the sep option

Series also has a to_csv method.

I don't know why the line 0 was finally written.

This is the end of the article on "how to input and output data in pandas". I hope the above content can be of some help to you, so that you can learn more knowledge. if you think the article is good, please share it for more people to see.

Welcome to subscribe "Shulou Technology Information " to get latest news, interesting things and hot topics in the IT industry, and controls the hottest and latest Internet news, technology news and IT industry trends.