Question

我想从初始值-3.9找到Dew_P Temp (C)的pct_change。我想在新专栏中使用pct_change。

来源：

weather = pd.read_csv('https://raw.githubusercontent.com/jvns/pandas-cookbook/master/data/weather_2012.csv')
weather[weather.columns[:4]].head()


Date/Time        Temp (C)   Dew_P Temp (C)  Rel Hum (%)
0   2012-01-01   -1.8       -3.9             86
1   2012-01-01   -1.8       -3.7             87
2   2012-01-01   -1.8       -3.4             89
3   2012-01-01   -1.5       -3.2             88
4   2012-01-01   -1.5       -3.3             88

我尝试过这种for循环的变体（甚至可以添加这里显示的索引），但无济于事：

for index, dew_point in weather['Dew_P Temp (C)'].iteritems():
    new = weather['Dew_P Temp (C)'][index]
    old = weather['Dew_P Temp (C)'][0]
    pct_diff = (new-old)/old*100
    weather['pct_diff'] = pct_diff

我认为问题是weather['pct_diff']，它不需要new它取数据框的最后一个值并从old中减去它

所以它总是（2.1-3.9）/3.9*100因此我的百分比变化总是-46％。

我想要的最终结果是：

Date/Time        Temp (C)   Dew_P Temp (C)  Rel Hum (%)   pct_diff
0   2012-01-01   -1.8       -3.9             86           0.00%
1   2012-01-01   -1.8       -3.7             87           5.12%
2   2012-01-01   -1.8       -3.4             89           12.82%

有什么想法吗？谢谢！

Answer 1

您可以使用iat来访问标量值（例如iat[0]访问系列中的第一个值。）

df = weather
df['pct_diff'] = df['Dew_P Temp (C)'] / df['Dew_P Temp (C)'].iat[0] - 1

Answer 2

IIUC你可以这样做：

In [88]: ((weather['Dew Point Temp (C)'] - weather.ix[0, 'Dew Point Temp (C)']).abs() / weather.ix[0, 'Dew Point Temp (C)']).abs() * 100
Out[88]:
0         0.000000
1         5.128205
2        12.820513
3        17.948718
4        15.384615
5        15.384615
6        20.512821
7         7.692308
8         7.692308
9        20.512821

Answer 3

我发现这更优雅

weather['Dew_P Temp (C)'].pct_change().fillna(0).add(1).cumprod().sub(1)

0    0.000000
1   -0.051282
2   -0.128205
3   -0.179487
4   -0.153846
Name: Dew_P Temp (C), dtype: float64

使用绝对值获得预期输出

weather['pct_diff'] = weather['Dew_P Temp (C)'].pct_change().fillna(0).add(1).cumprod().sub(1).abs()
weather

熊猫pct从初始值变化

3 个答案: