我有一个Pandas DataFrame,包含i、行和j列。我希望将这个DataFrame中的值替换为第二个DataFrame中的所有值,后者具有相同的i行,但有k列,其中k是j的子集。
有效的办法是:
for col in df2.columns:
df1[col] = df2[col]
有没有一种更快、更无头绪的方法?
df.drop(['column_name'],axis=1,inplace=True)
给出
"Warning (from warnings module):
File "/home/sourav/.local/lib/python3.5/site-packages/pandas/core/frame.py", line 3697
errors=errors)
SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
我正在尝试构建一个pandas Series来连接到一个数据帧上。
import numpy as np
import pandas as pd
rawData = pd.read_csv(input, header=1) # the DataFrame
strikes = pd.Series() # the empty Series
for i, row in rawData.iterrows():
sym = rawData.loc[i,'Symbol']
strike = float(sym[-6:])/1000
strikes = s
我有以下代码来确定一只股票是否有52周的高点:
import pandas as pd
from pandas_datareader import data as web
import numpy as np
tickers = 'goog', 'fb', 'aapl', 'tsla'
df = web.DataReader(tickers, 'yahoo')
for t in tickers:
df['52wk'] = df['High'][t].asfreq('