我有一个大型数据框df_Trial，其中一行名为reaction。其中有五个值，可能是:152Gd-p、154Gd-p、155Gd-p、156Gd-p 、15Gd-p、158Gd-p、160Gd-p。以下列包含一些与此步骤无关的信息，但是我希望根据“reaction”中存在的字符串将以下列乘以一个常数。我尝试将此应用为:
for index, row in df_trial.iterrows():
if row['reaction'] == '152Gd-p':
row[2:]*=0.002
if row['reaction'] == '154Gd-p':
row[2:]*=0.0218
if row['reaction'] == '155Gd-p':
row[2:]*=0.148
if row['reaction'] == '156Gd-p':
row[2:]*=0.2047
if row['reaction'] == '157Gd-p':
row[2:]*=0.1565
if row['reaction'] == '158Gd-p':
row[2:]*=0.2484
if row['reaction'] == '160Gd-p':
row[2:]*=0.2186
但这并没有将行中的值相乘。
这是我的数据框外观的示例:
reaction product 0.5 1.0 1.5 2.0 2.5 3.0 3.5 4.0 ... 35.5 36.0 36.5 37.0 37.5 38.0 38.5 39.0 39.5 40.0
81 155Gd-p 062150.tot 0.0 0.0 0.0 0.0 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 ... 1.101530e-02 1.253720e-02 1.404620e-02 1.562480e-02 1.713510e-02 1.855860e-02 1.989160e-02 2.113160e-02 2.228710e-02 2.333700e-02
82 155Gd-p 065156.L00 0.0 0.0 0.0 0.0 2.842720e-10 4.331690e-09 3.176340e-08 1.873100e-03 ... 1.836500e-01 1.803630e-01 1.728360e-01 1.606180e-01 1.685970e-01 1.679980e-01 1.639340e-01 1.538330e-01 1.639280e-01 1.656980e-01
83 155Gd-p 063149.tot 0.0 0.0 0.0 0.0 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 ... 6.990920e+00 7.877440e+00 8.781220e+00 9.594980e+00 1.034780e+01 1.097080e+01 1.156940e+01 1.196730e+01 1.230900e+01 1.241800e+01
84 155Gd-p 061146.tot 0.0 0.0 0.0 0.0 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 ... 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 9.529110e-04
85 155Gd-p 061147.tot 0.0 0.0 0.0 0.0 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 ... 1.000000e-07 1.000000e-07 1.000000e-07 1.000000e-07 1.000000e-07 1.063060e-03 1.130870e-03 1.172590e-03 1.180610e-03 1.165960e-03
86 155Gd-p 062151.tot 0.0 0.0 0.0 0.0 0.000000e+00 0.000000e+00 1.000000e-07 1.000000e-07 ... 1.041300e-03 1.076720e-03 1.090690e-03 1.109420e-03 1.137780e-03 1.135450e-03 1.128680e-03 1.149190e-03 1.143860e-03 1.150390e-03
87 155Gd-p 063154.L00 0.0 0.0 0.0 0.0 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 ... 3.173660e+00 3.444480e+00 3.724070e+00 4.007600e+00 4.323930e+00 4.673050e+00 4.971810e+00 5.346970e+00 5.661720e+00 6.060110e+00
88 155Gd-p 064150.tot 0.0 0.0 0.0 0.0 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 ... 2.579220e-03 4.992070e-03 9.679620e-03 2.035170e-02 3.447910e-02 5.437450e-02 9.089650e-02 1.471190e-01 2.126190e-01 2.896810e-01
89 155Gd-p 064154.tot 0.0 0.0 0.0 0.0 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 ... 2.337670e+02 2.386140e+02 2.390300e+02 2.431350e+02 2.413420e+02 2.446070e+02 2.421500e+02 2.447660e+02 2.425080e+02 2.446910e+02
90 155Gd-p 062148.tot 0.0 0.0 0.0 0.0 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 ... 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 1.172560e-03 1.722920e-03
91 155Gd-p 061148.tot 0.0 0.0 0.0 0.0 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 ... 1.000000e-07 1.000000e-07 1.000000e-07 1.000000e-07 1.000000e-07 6.300980e-05 6.278910e-05 6.094680e-05 5.998620e-05 5.900480e-05
92 155Gd-p 063153.tot 0.0 0.0 0.0 0.0 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 ... 3.136120e+00 3.390600e+00 3.631630e+00 3.958020e+00 4.197170e+00 4.564750e+00 4.762130e+00 4.948580e+00 5.314960e+00 5.549590e+00
93 155Gd-p 063152.tot 0.0 0.0 0.0 0.0 1.000000e-07 1.000000e-07 1.000000e-07 1.000000e-07 ... 2.371420e+00 2.502180e+00 2.629100e+00 2.699470e+00 2.818750e+00 2.972010e+00 3.188610e+00 3.416830e+00 3.648320e+00 3.884690e+00
94 155Gd-p 065151.tot 0.0 0.0 0.0 0.0 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 ... 6.969380e+01 1.072870e+02 1.483310e+02 1.996210e+02 2.548350e+02 3.046590e+02 3.501350e+02 3.969820e+02 4.371780e+02 4.748900e+02
95 155Gd-p 063150.L01 0.0 0.0 0.0 0.0 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 ... 2.297790e+00 2.303140e+00 2.279280e+00 2.212180e+00 2.171240e+00 2.134990e+00 2.086730e+00 2.017590e+00 1.979700e+00 1.957500e+00
96 155Gd-p 065152.tot 0.0 0.0 0.0 0.0 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 ... 7.834620e+02 7.493000e+02 7.095910e+02 6.583400e+02 6.050390e+02 5.525560e+02 5.055030e+02 4.521510e+02 4.095180e+02 3.664050e+02
显然，在完整的数据框中，它包含包含所有反应的行。
最佳答案
您可以定义一个函数来乘以每行，然后将其应用到每行 apply .
此外，为了改善条件，您可以设置 elif 而不是 if。这可以防止每次都测试所有条件。
在答案中，我使用字典来保存系数。然后，我通过 reaction 键调用它。
代码如下:
# Coefficients
multi_coef = {
'152Gd-p': 0.002,
'154Gd-p': 0.0218,
'155Gd-p': 0.148,
'156Gd-p': 0.2047,
'157Gd-p': 0.1565,
'158Gd-p': 0.2484,
'160Gd-p': 0.2186,
}
# Get columns name
columns = df.columns
# Function to apply to each row
def multiply_coef(row):
# If the reaction name is in the dictionary
if row.reaction in multi_coef.keys():
# Multiply by the reaction coefficient
row[columns[2:]] = row[columns[2:]] * multi_coef[row.reaction]
return row
# Apply the function (axis = 1 means over rows)
new_df = df.apply(multiply_coef, axis=1)
print(new_df)
# reaction product 0.5 1.0 1.5 2.0 ... 37.5 38.0 38.5 39.0 39.5 40.0
# 0 155Gd-p 062150.tot 0.0 0.0 0.0 0.0 ... 2.535995e-03 0.002747 0.002944 0.003127 0.003298 0.003454
# 1 155Gd-p 065156.L00 0.0 0.0 0.0 0.0 ... 2.495236e-02 0.024864 0.024262 0.022767 0.024261 0.024523
# 2 155Gd-p 063149.tot 0.0 0.0 0.0 0.0 ... 1.531474e+00 1.623678 1.712271 1.771160 1.821732 1.837864
# 3 155Gd-p 061146.tot 0.0 0.0 0.0 0.0 ... 0.000000e+00 0.000000 0.000000 0.000000 0.000000 0.000141
# 4 155Gd-p 061147.tot 0.0 0.0 0.0 0.0 ... 1.480000e-08 0.000157 0.000167 0.000174 0.000175 0.000173
# 5 155Gd-p 062151.tot 0.0 0.0 0.0 0.0 ... 1.683914e-04 0.000168 0.000167 0.000170 0.000169 0.000170
# 6 155Gd-p 063154.L00 0.0 0.0 0.0 0.0 ... 6.399416e-01 0.691611 0.735828 0.791352 0.837935 0.896896
# 7 155Gd-p 064150.tot 0.0 0.0 0.0 0.0 ... 5.102907e-03 0.008047 0.013453 0.021774 0.031468 0.042873
# 8 155Gd-p 064154.tot 0.0 0.0 0.0 0.0 ... 3.571862e+01 36.201836 35.838200 36.225368 35.891184 36.214268
# 9 155Gd-p 062148.tot 0.0 0.0 0.0 0.0 ... 0.000000e+00 0.000000 0.000000 0.000000 0.000174 0.000255
# 10 155Gd-p 061148.tot 0.0 0.0 0.0 0.0 ... 1.480000e-08 0.000009 0.000009 0.000009 0.000009 0.000009
# 11 155Gd-p 063153.tot 0.0 0.0 0.0 0.0 ... 6.211812e-01 0.675583 0.704795 0.732390 0.786614 0.821339
# 12 155Gd-p 063152.tot 0.0 0.0 0.0 0.0 ... 4.171750e-01 0.439857 0.471914 0.505691 0.539951 0.574934
# 13 155Gd-p 065151.tot 0.0 0.0 0.0 0.0 ... 3.771558e+01 45.089532 51.819980 58.753336 64.702344 70.283720
# 14 155Gd-p 063150.L01 0.0 0.0 0.0 0.0 ... 3.213435e-01 0.315979 0.308836 0.298603 0.292996 0.289710
# 15 155Gd-p 065152.tot 0.0 0.0 0.0 0.0 ... 8.954577e+01 81.778288 74.814444 66.918348 60.608664 54.227940
关于python - 给定一列具有特定值的情况下编辑数据框的行，我们在Stack Overflow上找到一个类似的问题： https://stackoverflow.com/questions/57114422/