Python / Pandas - 计算具有特定索引的行数
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Python / Pandas - Count number of rows with certain index
提问by abutremutante
I have this dataframe:
我有这个数据框：
content
id
17 B
17 A
6 A
15 A
...
I want to count how many rows have the index 17 (in this case that would be 2). Is there a way to do that?
我想计算有多少行索引为 17（在本例中为 2）。有没有办法做到这一点？
回答by student
You can try:
你可以试试：
sum(df.index == 17)
df.index == 17returns an array with booleanwith Truewhen index value matches else False. And while
using sumfunction Trueis equivalent to 1.
df.index == 17返回以与阵列boolean与True当索引值其他匹配False。而使用sum函数True相当于1.
回答by WY Hsu
Problem: How to count the quantity of index label?
问题：如何统计索引标签的数量？
Input: # Your DataFrame
test_dict = {'id': ['17', '17', '6', '15'], 'content': ['B', 'A', 'A', 'A']}
testd_df = pd.DataFrame.from_dict(test_dict) # create DataFrame from dict
testd_df.set_index('id', inplace=True) # set 'id' as index in inplace way
testd_df
Output:
|content
--------------
id |
-------------
17 | B
17 | A
6 | A
15 | A
Solution: Use api pandas.Index.value_counts
解决方案：使用api pandas.Index.value_counts
Based on the document, pandas.Index.value_countswill return object containing counts of unique values and return a pd.Series.
根据文档，pandas.Index.value_counts将返回包含唯一值计数的对象并返回一个pd.Series.
so now, I can select the specific indexI want by using pandas.Series.loc(not get confused with .iloc)
所以现在，我可以选择我想要的特定索引pandas.Series.loc（不要混淆.iloc）
# Solution
Input: index_count = pd.Index(testd_df.index).value_counts() # count value of unique value
index_count
Output: 17 2
15 1
6 1
dtype: int64
---------------------------------
Input: index_count.loc['17'] # select the information you care about
Output: 2
回答by YOBEN_S
You can groupby level
您可以按级别分组
df.groupby(level=0).count()
Or reset_index()
或者 reset_index()
df.reset_index().groupby('id').count()
