我正在尝试将合并的数据框保存到CSV文件中。代码一到达“ data.to_csv”行,它就会中断。我的代码如下:
import pandas as pd
import numpy as np
import os,errno
import glob
print ("Path has been read successfully")
path1 = glob.glob('S:\*Data\*Files\*Raw Data\*CPU\*Perf\*YesterdayDataset*.xlsx')
print (path1)
path2 = glob.glob("S:\*Data\*Files\*Raw Data\*CPU\*Perf\*CPUPerf_201920.csv")
print ("Path has been read successfully")
print ("Action has been completed successfully")
data = []
for df in path1:
df = pd.read_excel(df)
data.append(df)
data.to_csv("H:\\test1.csv", index = False)
def sremove():
try:
os.remove()
except OSError as e:
if e.errno != errno.ENOENT:
raise
执行此代码后收到的错误是:
AttributeError:“列表”对象没有属性“ to_csv”
对此的任何帮助将不胜感激。谢谢
答案 0 :(得分:1)
您尝试在to_csv()
而非数据框上使用list
函数。您必须先将x个数据帧合并为一个数据帧,然后才能从其中生成csv。
尝试这样的事情:
import pandas as pd
import numpy as np
import os,errno
import glob
print ("Path has been read successfully")
path1 = glob.glob('S:\*Data\*Files\*Raw Data\*CPU\*Perf\*YesterdayDataset*.xlsx')
print (path1)
path2 = glob.glob("S:\*Data\*Files\*Raw Data\*CPU\*Perf\*CPUPerf_201920.csv")
print ("Path has been read successfully")
print ("Action has been completed successfully")
data = []
for df in path1:
df = pd.read_excel(df)
data.append(df)
finaldf = pd.concat(data, axis=1, join='inner').sort_index()
finaldf.to_csv("H:\\test1.csv", index = False)
def sremove():
try:
os.remove()
except OSError as e:
if e.errno != errno.ENOENT:
raise
答案 1 :(得分:1)
您的问题是您有一个数据帧列表,并且要在整个列表中调用to_csv而不是单个数据帧。这里有两个选项,如果列表中只有一个数据帧,请使用以下代码:
data[0].to_csv("H:\\test1.csv", index = False)
如果其中有多个数据帧,请执行以下操作:
for i in data:
i.to_csv("filename", index = False)
请记住,对于第二个选项,您将需要使文件名动态化以避免覆盖。
编辑:
误读了您的问题。您实际上需要合并数据帧
df1 = pd.read_excel(path1)
df2 = pd.read_execl(path2)
df = df1.merge(df2, how = 'inner', on = 'JoinField')
df.to_csv("H:\\test1.csv", index = False)
答案 2 :(得分:1)
问题是您的data
对象是DataFrames的list
。您可以单独转换DataFrame,例如df.to_csv(...)
或将它们合并在一起并输出为一个文件。
尝试更改此部分:
data = []
for df in path1:
df = pd.read_excel(df)
data.append(df)
data.to_csv("H:\\test1.csv", index = False)
对此:
df = pd.concat(pd.read_excel(fl) for fl in path1)
df.to_csv("H:\\test1.csv", index = False)