【820】Python R 读取 csv 文件加入数据类型控制

参考：PySe-023-pandas.read_csv 读取 csv 文件，指定列数据类型 解决字符串数据列变为数字的问题

参考：Read a delimited file (including CSV and TSV) into a tibble

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Python：根据具体的列名指定数据格式

import pandas as pd
# the column of "id" will be stored as "string", otherwise it will be stored as "int", maybe
pd.read_csv("df.csv", dtype={"id": str})

R：用缩写代替具体的列的属性

df <- readr::read_csv("df_eu_sim.csv", col_types = "Ddc") 

具体如下：

col_types

One of NULL, a cols() specification, or a string. See vignette("readr") for more details.

If NULL, all column types will be inferred from guess_max rows of the input, interspersed throughout the file. This is convenient (and fast), but not robust. If the guessed types are wrong, you'll need to increase guess_max or supply the correct types yourself.

Column specifications created by list() or cols() must contain one column specification for each column. If you only want to read a subset of the columns, use cols_only().

Alternatively, you can use a compact string representation where each character represents one column:

• c = character

• i = integer

• n = number

• d = double

• l = logical

• f = factor

• D = date

• T = date time

• t = time

• ? = guess

• _ or - = skip