編碼:
import pandas as pd
data = {'Identifier': ['55555-abc','77777-xyz','99999-mmm']}
df = pd.DataFrame(data, columns=['Identifier'])
left = df['Identifier'].str[:5]
union = pd.concat([df,left], ignore_index=True)
print(union)
結果:
| | Identifier | 0 |
|--| ---------- | --- |
|0 | 55555-abc | NaN |
|1 | 77777-xyz | NaN |
|2 | 99999-mmm | NaN |
|3 | NaN |55555|
|4 | NaN |77777|
|5 | NaN |99999|
我想要的是:
| | Identifier |
|--| ---------- |
|0 | 55555-abc |
|1 | 77777-xyz |
|2 | 99999-mmm |
|3 | 55555 |
|4 | 77777 |
|5 | 99999 |
uj5u.com熱心網友回復:
嘗試使用 Pandas 的 append 函式作為:
import pandas as pd
data = {'Identifier': ['55555-abc','77777-xyz','99999-mmm']}
df = pd.DataFrame(data,columns=['Identifier'])
left = df['Identifier'].str[:5]
for i in left:
df = df.append({'Identifier': i}, ignore_index=True)
print(df)
轉載請註明出處,本文鏈接:https://www.uj5u.com/qukuanlian/369437.html
下一篇:比較兩個資料幀中的資料
