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我正在遍历每月的气象站数据。我可以按如下方式连接文件：

path = r"D:\NOAA\output\TEST" 
all_files = glob.glob(path + "/*.csv")

for filename in all_files:
    print filename # prints D:\NOAA\output\TEST\189501.tave.conus.csv
    df = (pd.read_csv(f) for f in all_files)
    concatenated_df = pd.concat(df, axis=1, join='inner')

这导致以下数据框：

     lat      lon     temp    lat      lon     temp    lat      lon    temp
0  24.5625 -81.8125  21.06  24.5625 -81.8125  17.08  24.5625 -81.8125  22.42
1  24.5625 -81.7708  21.06  24.5625 -81.7708  17.08  24.5625 -81.7708  22.47
2  24.5625 -81.7292  21.06  24.5625 -81.7292  17.08  24.5625 -81.7292  22.47
3  24.5625 -81.6875  21.05  24.5625 -81.6875  17.04  24.5625 -81.6875  22.47
4  24.6042 -81.6458  21.06  24.6042 -81.6458  17.08  24.6042 -81.6458  22.45

lat和列是相同的lon，所以我想删除那些重复的列。这些temp列对于每个月度 CSV 文件都是唯一的。我想保留所有这些，但也给它们有意义的列名，取自文件名，即：

        lat      lon   temp185901   temp185902   temp185903
0    24.5625  -81.8125   21.06        17.08        22.42
1    24.5625  -81.7708   21.06        17.08        22.47
2    24.5625  -81.7292   21.06        17.08        22.47
3    24.5625  -81.6875   21.05        17.04        22.47
4    24.6042  -81.6458   21.06        17.08        22.45

我是 Pandas 的新手（看起来很棒，但吸收了很多东西），我将不胜感激。我认为解决方案在我用于 、 和 的.concat()参数.duplicate()中.loc()。

示例数据： ftp: //ftp.commissions.leg.state.mn.us/pub/gis/Temp/NOAA/

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2 回答 2

1

您可以合并两列并为其他列设置后缀：

temp = df1.merge(df2, on=['lat','lon'], suffixes=('185901','185902'))

       lat      lon  temp185901  temp185902
0  24.5625 -81.8125       21.06       17.08
1  24.5625 -81.7708       21.06       17.08
2  24.5625 -81.7292       21.06       17.08
3  24.5625 -81.6875       21.05       17.04
4  24.6042 -81.6458       21.06       17.08

或者在一个循环中

temp.merge(df3, on=['lat','lon']).rename(columns={'temp':'temp185903'})

       lat      lon  temp185901  temp185902  temp185903
0  24.5625 -81.8125       21.06       17.08       22.42
1  24.5625 -81.7708       21.06       17.08       22.47
2  24.5625 -81.7292       21.06       17.08       22.47
3  24.5625 -81.6875       21.05       17.04       22.47
4  24.6042 -81.6458       21.06       17.08       22.45

df = []
for filename in all_files:
    df1 = pd.read_csv(filename)
    # if the first loop
    if not list(df):
       df = df1
    else:
       df = df.merge(df1, on=['lat','lon'])
    df.rename(columns={'temp':'temp'+put_numer_from_filename}, inplace=True)
于 2019-10-23T15:56:50.267 回答
0

这会将新数据作为带有“日期”列的新行附加到连接的数据框中，以指示数据来自哪个文件。修改逻辑以从文件名中获取日期。

import pandas as pd
import glob

path = r'D:\NOAA\output\TEST'
all_files = glob.glob(path + '/*.csv')

df_concat = pd.DataFrame()

for file in all_files:
    df = pd.read_csv(file)
    df['date'] = file #ammend the variable file to get the date from your file names

    df_concat = df_concat.append(df)
于 2019-10-23T18:31:05.423 回答