Question

我试图合并Excel集中的列，当我合并这些列时，如果该列为空，则会放置一个NaN。如何摆脱NaN而不丢掉整行？

import os
import pandas as pd
import numpy as np
path = os.getcwd()
files = os.listdir(path)
files_xls = [f for f in files if f[-4:] == 'xlsx']
df = pd.DataFrame()
for f in files_xls:
  qw = pd.read_excel(f)
  df = df.append(qw)
  cf = df.iloc[:, df.columns.str.contains('address1|address2|city|state|zip|Location Address', case=False)]
  vf = df['address1'].map(str) + '-' + df['address2'].map(str) + '-' + df['city'].map(str) + '-' + df['state'].map(str) + '-' + df['zip'].map(str)
export_csv = vf.to_csv('dataframe.csv', index=None, header=True)

Answer 1

使用replace函数

import os
import pandas as pd
import numpy as np
path = os.getcwd()
files = os.listdir(path)
files_xls = [f for f in files if f[-4:] == 'xlsx']
df = pd.DataFrame()
for f in files_xls:
    qw = pd.read_excel(f)
    df = df.append(qw)
    cf = df.iloc[:, 
    df.columns.str.contains('address1|address2|city|state|zip|Location Address', case=False)]
    vf = df['address1'].map(str) + '-' + df['address2'].map(str) + '-' + 
    df['city'].map(str) + '-' + df['state'].map(str) + '-' + df['zip'].map(str)
df = df.replace(np.nan, '', regex=True)
export_csv = vf.to_csv('dataframe.csv', index=None, header=True)

输出返回NaN我如何在不丢掉整行的情况下乘坐NaN

1 个答案: