如何将多个csv连接到xarray并定义坐标? [英] How to concatenate multiple csv to xarray and define coordinates?

问题描述

我有多个csv文件，具有相同的行和列，并且它们包含的数据根据​​日期而有所不同.每个csv文件都附有不同的日期，并以其名称列出，例如data.2018-06-01.csv.我的数据的一个最小示例如下:我有两个文件data.2018-06-01.csv和data.2019-06-01.csv，分别包含

I have multiple csv-files, with the same rows and columns and their contained data varies depending on the date. Each csv-file is affiliated with a different date, listed in its name, e.g. data.2018-06-01.csv. A minimal example of my data looks like that: I have the 2 files, data.2018-06-01.csv and data.2019-06-01.csv, that respectively contain

user_id, weight, status
001, 70, healthy
002, 90, healthy 

和

user_id, weight, status
001, 72, healthy
002, 103, obese

我的问题:如何将csv文件串联到一个xarray中，并定义xarray的坐标为user_id和date?

My Question: How can I concatenate the csv-files into a xarray and also define that the coordinates of the xarray are user_id and date?

我尝试了以下代码

df_all = [] 
date_arr = []

for f in [`data.2018-06-01.csv`, `data.2019-06-01.csv`]:
  date = f.split('.')[1]
  df = pd.read_csv(f)
  df_all.append(df)
  date_arr.append(date)

x_arr = xr.concat([df.to_xarray() for df in df_all], coords=[date_arr, 'user_id'])

但coords=[...]导致错误.我该怎么办?谢谢

but coords=[...] leads to an error. What can I do insted? Thanks

推荐答案

尝试以下方法:

    import glob
    import pandas as pd

    path=(r'ur file')
    all_file = glob.glob(path + "/*.csv")
    li = []
    for filename in all_file:
    df = pd.read_csv(filename, index_col=None, header=0)
    li.append(df)
    frame = pd.concat(li, axis=0, ignore_index=True)

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