dataframe操作

1.去除重复项drop_duplication

#去除重复项drop_duplication

import pandas as pd
df = pd.DataFrame({"col1":[1, 1, 2, 2], "col2" : ["a", "a", "b", "b"]})
print(df)
#指定某个列,保留第一出现的元素
df.drop_duplicates("col1", "first", inplace=True)
print(df)

df = pd.DataFrame({"col1":[1, 1, 2, 2], "col2" : ["a", "a", "b", "b"]})
print(df)
#对某一列进行去除
df = df["col1"].drop_duplicates()
print(df)

   col1 col2
0     1    a
1     1    a
2     2    b
3     2    b
   col1 col2
0     1    a
2     2    b
   col1 col2
0     1    a
1     1    a
2     2    b
3     2    b
0    1
2    2
Name: col1, dtype: int64

2.设置索引

#设置索引
import pandas as pd
df = pd.DataFrame({"col1":[1, 1, 2, 2], "col2" : ["a", "a", "b", "b"]})
df.set_index("col1", inplace=True)
print(df)
df.index.name = "索引"
print(df)

df = pd.DataFrame({"col1":[1, 1, 2, 2], "col2" : ["a", "a", "b", "b"]})
index = df.pop("col1")
df.index = index
df.index.name = "索引"
print(df)

     col2
col1
1       a
1       a
2       b
2       b
   col2
索引
1     a
1     a
2     b
2     b
   col2
索引
1     a
1     a
2     b
2     b

3.round操作
发现该操作只能把小数点位数减少,而不能够把小数点位数变多.比如小数点后3位的可以round成小数点后2位,反之则不可以.
可以用applymap来增加小数点的位数,但是对所有的列进行的操作.只针对某列的还有找到.

df = pd.DataFrame({"a":[,2.0,], "b":[,5.0,]}, columns = ["a", "b"])
df = df.applymap(lambda x : "%.3f" % x)

       a      b
0  1.000  4.000
1  2.000  5.000
2  3.000  6.000