dataframe find
时间: 2023-11-18 22:41:48 浏览: 33
在Python的DataFrame中,没有直接的find方法。但是可以使用其他方法来查找特定值在DataFrame中的位置。其中一种方法是使用isin()方法来检查某列中是否包含指定的值。例如,如果我们想要查找成绩列中是否包含90分的行,可以使用以下代码:
```python
table[table['成绩'].isin(['90'])]
```
这将返回包含成绩为90的行的子DataFrame。这个方法可以根据不同的需求来进行适当的调整和扩展,以查找其他特定的值。
相关问题
how to find number in Dataframe?
To find a number in a DataFrame, you can use the following code:
```python
import pandas as pd
# create a DataFrame
df = pd.DataFrame({'A': [1, 2, 3], 'B': [4, 5, 6], 'C': [7, 8, 9]})
# check if the number 5 is in the DataFrame
if 5 in df.values:
print('Number 5 is in the DataFrame')
else:
print('Number 5 is not in the DataFrame')
```
In this example, the code creates a DataFrame with three columns and checks if the number 5 is in the DataFrame using the `in` keyword and the `values` attribute of the DataFrame. If the number is found, the code prints a message indicating that it is in the DataFrame; otherwise, it prints a message indicating that it is not found.
how to find the common values between two different sizes of dataframe
To find the common values between two different-sized DataFrames in Python, you can use the `merge()` function from the pandas library. The `merge()` function combines two DataFrames based on common values in specified columns. Here's an example:
```python
import pandas as pd
# Create two example DataFrames
df1 = pd.DataFrame({'A': [1, 2, 3], 'B': [4, 5, 6]})
df2 = pd.DataFrame({'A': [2, 3, 4], 'C': [7, 8, 9]})
# Find common values between the two DataFrames
common_values = pd.merge(df1, df2, on='A')
print(common_values)
```
Output:
```
A B C
0 2 5 7
1 3 6 8
```
In the above code, we merge `df1` and `df2` based on the common values in column `'A'`. The result is a new DataFrame `common_values` that contains rows with common values in column `'A'`. The resulting DataFrame includes the columns from both `df1` and `df2`.