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Convert Pandas column containing NaNs to dtype `int` [duplicate]

由 佐手、 提交于 2019-11-26 01:47:02
问题 This question already has answers here : NumPy or Pandas: Keeping array type as integer while having a NaN value (7 answers) Closed 6 months ago . I read data from a .csv file to a Pandas dataframe as below. For one of the columns, namely id , I want to specify the column type as int . The problem is the id series has missing/empty values. When I try to cast the id column to integer while reading the .csv, I get: df= pd.read_csv(\"data.csv\", dtype={\'id\': int}) error: Integer column has NA

How do I replace NA values with zeros in an R dataframe?

由 徘徊边缘 提交于 2019-11-26 01:19:06
问题 I have a data frame and some columns have NA values. How do I replace these NA values with zeroes? 回答1: See my comment in @gsk3 answer. A simple example: > m <- matrix(sample(c(NA, 1:10), 100, replace = TRUE), 10) > d <- as.data.frame(m) V1 V2 V3 V4 V5 V6 V7 V8 V9 V10 1 4 3 NA 3 7 6 6 10 6 5 2 9 8 9 5 10 NA 2 1 7 2 3 1 1 6 3 6 NA 1 4 1 6 4 NA 4 NA 7 10 2 NA 4 1 8 5 1 2 4 NA 2 6 2 6 7 4 6 NA 3 NA NA 10 2 1 10 8 4 7 4 4 9 10 9 8 9 4 10 NA 8 5 8 3 2 1 4 5 9 4 7 9 3 9 10 1 9 9 10 5 3 3 10 4 2 2 5

Convert Pandas column containing NaNs to dtype `int` [duplicate]

由 天大地大妈咪最大 提交于 2019-11-25 21:46:33
This question already has an answer here: NumPy or Pandas: Keeping array type as integer while having a NaN value 7 answers I read data from a .csv file to a Pandas dataframe as below. For one of the columns, namely id , I want to specify the column type as int . The problem is the id series has missing/empty values. When I try to cast the id column to integer while reading the .csv, I get: df= pd.read_csv("data.csv", dtype={'id': int}) error: Integer column has NA values Alternatively, I tried to convert the column type after reading as below, but this time I get: df= pd.read_csv("data.csv")
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