合并熊猫数据框时在python中出现MemoryError

Question

我试图将十个数据帧合并为一个，我要从九个数据帧中取一列并将其添加到主数据帧中。它适用于两个合并，然后给我这个。

Traceback (most recent call last):
  File "C:\Users\name\Desktop\project\test.py", line 34, in <module>
    file_checks(path)
  File "C:\Users\name\Desktop\project\test.py", line 27, in file_checks
    main = pd.merge(main, samp_df[["Date", col]],on="Date", how="left")
  File "C:\Users\name\Anaconda3\lib\site-packages\pandas\core\reshape\merge.py", line 48, in merge
    return op.get_result()
  File "C:\Users\name\Anaconda3\lib\site-packages\pandas\core\reshape\merge.py", line 560, in get_result
    concat_axis=0, copy=self.copy)
  File "C:\Users\name\Anaconda3\lib\site-packages\pandas\core\internals\managers.py", line 2061, in concatenate_block_managers
    concatenate_join_units(join_units, concat_axis, copy=copy),
  File "C:\Users\name\Anaconda3\lib\site-packages\pandas\core\internals\concat.py", line 242, in concatenate_join_units
    for ju in join_units]
  File "C:\Users\name\Anaconda3\lib\site-packages\pandas\core\internals\concat.py", line 242, in <listcomp>
    for ju in join_units]
  File "C:\Users\name\Anaconda3\lib\site-packages\pandas\core\internals\concat.py", line 225, in get_reindexed_values
    fill_value=fill_value)
  File "C:\Users\name\Anaconda3\lib\site-packages\pandas\core\algorithms.py", line 1651, in take_nd
    out = np.empty(out_shape, dtype=dtype)
MemoryError

这是我的代码：

# import libraries
import pandas as pd
import numpy as np
import datetime
import os.path

#Path to files
path  = 'my_path'
#Column types
main_dtype = {"COAST" : "object","EAST" : "object","FAR_WEST" : "object","NORTH" : "object",\
"NORTH_C" : "object","SOUTHERN" : "object","SOUTH_C" : "object","WEST" : "object","ERCOT" : "object"}
def merge_data(path):
    # Load the main dataframe
    main = pd.read_csv("hist_load.csv", dtype=main_dtype)
    main["Date"]=pd.to_datetime(main["Date"]).dt.strftime('%m-%d-%Y')
    for file in os.listdir(path):
        if file.endswith("sample.csv"): # Loop through the files for files with specific ending
            samp_df = pd.read_csv(file) # Load the files and extracts name from header
            city_name = samp_df.columns[7][:-10]
            samp_df = pd.read_csv(file, header=[1]) # Reloads file and skips header
            samp_df["Date"]=pd.to_datetime(samp_df["Date"]).dt.strftime('%m-%d-%Y')
            samp_df['Precip'] = samp_df['Precip'].replace('-', 0) #replace missing values
            samp_df.rename(columns = {'Precip' : city_name.lower() + '_precip'}, inplace=True) # rename col
            col = city_name.lower() + '_precip'
            main = pd.merge(main, samp_df[["Date", col]],on="Date", how="left") # Merge dataframes