如何 pandas 数据框中的 select 行在某些列中只有特定值?
How to select rows in pandas dataframe that only have certain values in some columns?
假设我有下面的 DF,我只想 select 具有 Adj Close
值超过 90 的行。我想 select 这些值的所有列。我该怎么做?
High Low Open Close Volume Adj Close
Date
2020-01-02 86.139999 84.342003 84.900002 86.052002 47660500.0 86.052002
2020-01-03 90.800003 87.384003 88.099998 88.601997 88892500.0 88.601997
2020-01-06 90.311996 88.000000 88.094002 90.307999 50665000.0 90.307999
2020-01-07 94.325996 90.671997 92.279999 93.811996 89410500.0 93.811996
2020-01-08 99.697998 93.646004 94.739998 98.428001 155721500.0 98.428001
我正在尝试如下操作:
for i in data['Adj Close']:
if i>200:
print (data)
谢谢!
按照你说的,下面的代码可以解决
#import libs
import pandas as pd
import numpy as np
#import dataset
df = pd.read_csv('/content/Data.csv')
#filter
df[df['Adj Close']>90]
Obs:在 google colab 中,您必须通过具有文件夹符号的字段添加数据库,然后单击该字段(上传到会话存储)
假设我有下面的 DF,我只想 select 具有 Adj Close
值超过 90 的行。我想 select 这些值的所有列。我该怎么做?
High Low Open Close Volume Adj Close
Date
2020-01-02 86.139999 84.342003 84.900002 86.052002 47660500.0 86.052002
2020-01-03 90.800003 87.384003 88.099998 88.601997 88892500.0 88.601997
2020-01-06 90.311996 88.000000 88.094002 90.307999 50665000.0 90.307999
2020-01-07 94.325996 90.671997 92.279999 93.811996 89410500.0 93.811996
2020-01-08 99.697998 93.646004 94.739998 98.428001 155721500.0 98.428001
我正在尝试如下操作:
for i in data['Adj Close']:
if i>200:
print (data)
谢谢!
按照你说的,下面的代码可以解决
#import libs
import pandas as pd
import numpy as np
#import dataset
df = pd.read_csv('/content/Data.csv')
#filter
df[df['Adj Close']>90]
Obs:在 google colab 中,您必须通过具有文件夹符号的字段添加数据库,然后单击该字段(上传到会话存储)