Pandas：比较 dataframe 与 csv 文件并更新 Z628CB5675FF524F3E719B7AA2E88FE3 文件

Question

我有以下 ddataframe

          domain   hostname      ip address  status           managed by      monitor target name
0         jetty.com  aabb   XXX.XX.XX.XXX         Deployed  Sec Team  aabb.jetty.com
1         jetty.com  axcd   XXX.XX.XX.XXX         Deployed  Sec Team  axcd.jetty.com

现在我有另一个 csv 文件报告。csv

"domain","hostname","ip address","managed by", "monitor target name"
"jetty.com","aabb","XXX.XX.XX.XXX", "Decreased","OP Team", "aabb.jetty.com"
"jetty.com","axcd","XXX.XX.XX.XXX", "Decreased","OP2 Team", "axcd.jetty.com"
"jetty.com","appd","XXX.XX.XX.XXX", "Dec","OP8 Team", "appd.jetty.com"

 

现在我想将 df 与此 csv 进行比较，然后将 csv 更新为以下

"domain","hostname","ip address","managed by", "monitor target name"
"jetty.com","aabb","XXX.XX.XX.XXX", "Deployed","OP Team", "aabb.jetty.com"
"jetty.com","axcd","XXX.XX.XX.XXX", "Deployed","OP Team", "axcd.jetty.com"
"jetty.com","appd","XXX.XX.XX.XXX", "Dec","OP8 Team", "appd.jetty.com"

现在它已更新并且看起来与 df 中的相同

如何根据 df 值更新 csv 但不修改 csv 中已经存在的其他行

Answer 1

利用：

df2 = pd.read_csv('reporst.csv')

df1 = ddataframe.set_index(['domain','hostname','ip address'])
df2 = reporst.set_index(['domain','hostname','ip address'])

df2.update(df1)

df2.to_csv('out.csv')