系统:Windows 10 编辑器:JetBrains PyCharm Community Edition 2018.2.2 x64 pandas:1.1.5
- 这个系列讲讲Python的科学计算及可视化
- 今天讲讲pandas模块
- 将df按某列进行去重
Part 1:场景描述
- 已知df1,包括6列,
"time", "pos", "value1", "value2", "value3", "value4
- 有两个需求: 根据pos列,去除重复记录; 根据pos和value1列,去除重复记录,即要求这两列都相等时去重
df_1
Part 2:根据pos列去重
代码语言:javascript复制import pandas as pd
dict_1 = {"time": ["2019-11-02", "2019-11-03", "2019-11-04", "2019-11-05",
"2019-12-02", "2019-12-03", "2019-12-04", "2019-12-05"],
"pos": ["A", "A", "C", "D", "E", "E", "G", "H"],
"value1": [20, 20, 30, 40, 50, 60, 70, 80],
"value2": [100, 200, 300, 400, 500, 600, 700, 800],
"value3": [50, 20, 30, 90, 50, 60, 80, 80],
"value4": ['21W12', '21W10', '21W01', '21W05', '21W06', '21W36', '21W21', '21W23']}
df_1 = pd.DataFrame(dict_1, columns=["time", "pos", "value1", "value2", "value3", "value4"])
print("n", "df_1", "n", df_1, "n")
df_2 = df_1
df_2.drop_duplicates(subset=["pos"], keep="first", inplace=True)
print("n", "df_2", "n", df_2, "n")
print("n", "df_1", "n", df_1, "n")
代码截图
执行结果
Part 3:根据pos和value1列去重
代码语言:javascript复制import pandas as pd
dict_1 = {"time": ["2019-11-02", "2019-11-03", "2019-11-04", "2019-11-05",
"2019-12-02", "2019-12-03", "2019-12-04", "2019-12-05"],
"pos": ["A", "A", "C", "D", "E", "E", "G", "H"],
"value1": [20, 20, 30, 40, 50, 60, 70, 80],
"value2": [100, 200, 300, 400, 500, 600, 700, 800],
"value3": [50, 20, 30, 90, 50, 60, 80, 80],
"value4": ['21W12', '21W10', '21W01', '21W05', '21W06', '21W36', '21W21', '21W23']}
df_1 = pd.DataFrame(dict_1, columns=["time", "pos", "value1", "value2", "value3", "value4"])
print("n", "df_1", "n", df_1, "n")
df_3 = df_1
df_3.drop_duplicates(subset=["pos", "value1"], keep="first", inplace=True)
print("n", "df_3", "n", df_3, "n")
print("n", "df_1", "n", df_1, "n")
代码截图
执行结果
Part 4:部分代码解读
df_2.drop_duplicates(subset=["pos"], keep="first", inplace=True)
,subset对应列表取值去重参考列,若列表元素大于1个,要求同时满足多列对应记录相同才能去重。keep="first"
表示去重后,保留第1个记录df_2=df_1
后对,df_2进行去重后,df_1同时发生了变化,表明两个变量对应的地址应该是同一区域
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