隨着時間的推移後綴數字在numpy的

Question

字符串轉換我有類似「1.0秒」，「100毫秒」等我不能繪製該值的numpy的系列（有熊貓，把陣列分成一系列後），因爲熊貓不承認這些是數字。如何讓numpy或熊貓將這些數據推算爲數字，同時注意後綴？

Answer 1

此代碼可以解決你的問題。

# Test data 
se = Series(['10s', '100ms', '1.0s']) 

# Pattern to match ms and as integer of float 
pat = "([0-9]*\.?[0-9]+)(ms|s)" 
# Extracting the data 
df = se.str.extract(pat, flags=0, expand=True) 
# Renaming columns 
df.columns = ['value', 'unit'] 
# Converting to number 
df['value'] = pd.to_numeric(df['value']) 
# Converting to the same unit 
df.loc[df['unit']=='s', ['value', 'unit']] = (df['value'] * 1000, 'ms') 

# Now you are ready to plot ! 
print(df['value']) 
# 0  10000.0 
# 1  100.0 
# 2 100000.0 

Answer 2

見問題how do I get at the pandas.offsets object given an offset string

---

• 使用pandas.tseries.frequencies.to_offset
• 皈依timedeltas
• 獲得總秒數

---

from pandas.tseries.frequencies import to_offset 

s = pd.Series(['1.0s', '100ms', '10s', '0.5T']) 
pd.to_timedelta(s.apply(to_offset)).dt.total_seconds() 

0  0.0 
1  0.1 
2  10.0 
3 300.0 
dtype: float64