[英]How to concatenate a specific column from a pandas.DataFrame()?
I have a list of files, and I want to combine a specific column from it for all my files, to run some cumulative analysis. 我有一个文件列表,我想为我的所有文件合并一个特定的列,以运行一些累积分析。
import pandas as pd
import numpy as np
all_data_sets = pd.DataFrame([])
for file_name in file_list:
my_data = pd.DataFrame([])
my_data = pd.read_csv(file_name, delimiter=',', names=header_row)
my_data = my_data.reset_index()
all_data_sets.append(my_data['sales'])
#np.mean(all_data_sets['sales'])
np.mean(all_data_sets)
you can use concat
to concatenate a list of DataFrames 您可以使用concat
串联一个DataFrames列表
df_list = [pd.read_csv(file_name, delimiter=',', names=header_row) for file_name in file_list] #opens your csv
df = pd.concat(df_list)
Then you calculate the mean via 然后您通过计算平均值
df.sales.mean()
A small example 一个小例子
a = pd.DataFrame({'sales' : [2,4,6] , 'other' : [1,2,1]})
b = pd.DataFrame({'sales' : [7,4,7] , 'other' : [9,2,1]})
df = pd.concat([a,b])
the dataframe is 数据框是
other sales
0 1 2
1 2 4
2 1 6
0 9 7
1 2 4
2 1 7
and the mean 和平均值
df.sales.mean()
5.0
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