pandas 如何向 DataFrame 添加字符串值？
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How do I add a string value to DataFrame?
提问by Chipmunkafy
string = 'cool'
df = pd.DataFrame(columns=['string_values'])
Append
附加
df.append(string)
I get this error when I try to append it into df. (Is it only for numerical data?)
当我尝试将其附加到 df 时出现此错误。（是否仅适用于数值数据？）
cannot concatenate object of type "<class 'str'>"; only pd.Series, pd.DataFrame, and pd.Panel (deprecated) objs are valid
I just want to add a string value string = 'cool'into the dataframe, but I get this error.
我只想string = 'cool'在数据框中添加一个字符串值，但出现此错误。
回答by jezrael
I think best is use DataFramecontructor and assign one element list:
我认为最好是使用DataFrame构造函数并分配一个元素列表：
string = 'cool'
df = pd.DataFrame([string], columns=['string_values'])
print (df)
string_values
0 cool
If strings are generated in loop best is append them to one list and then pass to constructor only once:
如果在循环中生成字符串，最好将它们附加到一个列表中，然后只传递给构造函数一次：
L = []
for x in range(3):
L.append(string)
df = pd.DataFrame(L, columns=['string_values'])
print (df)
string_values
0 cool
1 cool
2 cool
Performance:
性能:
In [43]: %%timeit
...: L = []
...: for x in range(1000):
...: value1 = "dog" + str(x)
...: L.append(value1)
...:
...: df = pd.DataFrame(L, columns=['string_values'])
...:
1.29 ms ± 56.6 μs per loop (mean ± std. dev. of 7 runs, 1000 loops each)
In [44]: %%timeit
...: df = pd.DataFrame(columns=['string_values'])
...: for x in range(1000):
...: value1 = "dog" + str(x)
...: df = df.append({'string_values': value1}, ignore_index=True)
...:
1.19 s ± 34.3 ms per loop (mean ± std. dev. of 7 runs, 1 loop each)
回答by Edgar Ramírez Mondragón
If you need to add more than a single value, see @jezraels answer. If you only need to add a single value, you can do this:
如果您需要添加多个值，请参阅@jezraels 答案。如果您只需要添加一个值，您可以这样做：
import pandas as pd
df = pd.DataFrame(columns=['string_values'])
value1 = "dog"
df = df.append({'string_values': value1}, ignore_index=True)
# string_values
# 0 dog
value2 = "cat"
df = df.append({'string_values': value2}, ignore_index=True)
# string_values
# 0 dog
# 1 cat
Check the docs.
检查文档。
