pandas

问题 I have multi-index df as follows x y id date abc 3/1/1994 100 7 9/1/1994 90 8 3/1/1995 80 9 Where dates are stored as str. I want to parse date index. The following statement df.index.levels[1] = pd.to_datetime(df.index.levels[1]) returns error: TypeError: 'FrozenList' does not support mutable operations. 回答1: As mentioned, you have to recreate the index: df.index = df.index.set_levels([df.index.levels[0], pd.to_datetime(df.index.levels[1])]) 回答2: You cannot modify it in-place. You can use

问题 I have multi-index df as follows x y id date abc 3/1/1994 100 7 9/1/1994 90 8 3/1/1995 80 9 Where dates are stored as str. I want to parse date index. The following statement df.index.levels[1] = pd.to_datetime(df.index.levels[1]) returns error: TypeError: 'FrozenList' does not support mutable operations. 回答1: As mentioned, you have to recreate the index: df.index = df.index.set_levels([df.index.levels[0], pd.to_datetime(df.index.levels[1])]) 回答2: You cannot modify it in-place. You can use

问题 I want to read the file f (file size:85GB) in chunks to a dataframe. Following code is suggested. chunksize = 5 TextFileReader = pd.read_csv(f, chunksize=chunksize) However, this code gives me TextFileReader, not dataframe. Also, I don't want to concatenate these chunks to convert TextFileReader to dataframe because of the memory limit. Please advise. 回答1: As you are trying to process 85GB CSV file, if you will try to read all the data by breaking it into chunks and converting it into

问题 I want to read the file f (file size:85GB) in chunks to a dataframe. Following code is suggested. chunksize = 5 TextFileReader = pd.read_csv(f, chunksize=chunksize) However, this code gives me TextFileReader, not dataframe. Also, I don't want to concatenate these chunks to convert TextFileReader to dataframe because of the memory limit. Please advise. 回答1: As you are trying to process 85GB CSV file, if you will try to read all the data by breaking it into chunks and converting it into

问题 I want to read the file f (file size:85GB) in chunks to a dataframe. Following code is suggested. chunksize = 5 TextFileReader = pd.read_csv(f, chunksize=chunksize) However, this code gives me TextFileReader, not dataframe. Also, I don't want to concatenate these chunks to convert TextFileReader to dataframe because of the memory limit. Please advise. 回答1: As you are trying to process 85GB CSV file, if you will try to read all the data by breaking it into chunks and converting it into

问题 I have strings like '03-21-2019' that I want to convert to the native Python datetime object: that is, of the datetime.datetime type. The conversion is easy enough through pandas : import pandas as pd import datetime as dt date_str = '03-21-2019' pd_Timestamp = pd.to_datetime(date_str) py_datetime_object = pd_Timestamp.to_pydatetime() print(type(py_datetime_object)) with the result <class 'datetime.datetime'> This is precisely what I want, since I want to compute timedelta 's by subtracting

问题 I have a dataframe df like below NETWORK config_id APPLICABLE_DAYS Case Delivery 0 Grocery 5399 SUN 10 1 1 Grocery 5399 MON 20 2 2 Grocery 5399 TUE 30 3 3 Grocery 5399 WED 40 4 I want to implode( combine Applicable_days from multiple rows into single row like below) and get the average case and delivery per config_id NETWORK config_id APPLICABLE_DAYS Avg_Cases Avg_Delivery 0 Grocery 5399 SUN,MON,TUE,WED 90 10 using the groupby on network,config_id i can get the avg_cases and avg_delivery like

问题 I want to read data from my oracle, I use the pandas's read_sql and set the parameter chunksize=20000 , from sqlalchemy import create_engine import pandas as pd engine = create_engine("my oracle") df = pd.read_sql("select clause",engine,chunksize=20000) It returns a iterator, and I want to convert this generator to a dataframe using df = pd.DataFrame(df) , but it's wrong, How can the iterator be converted to a dataframe? 回答1: This iterator can be concatenated, then it return a dataframe: df =

问题 This chart is built by Excel. How can I do the same using matplotlib? I mean how to add two formatters: years months. Now i use something like this: fig, ax = plt.subplots(1,1) ax.margins(x=0) ax.plot(list(df['Date']), list(df['Value']), color="g") ax.xaxis.set_major_locator(matplotlib.dates.YearLocator()) ax.xaxis.set_major_formatter(matplotlib.dates.DateFormatter('%Y')) plt.text(df["Date"].iloc[-1], df["Value"].iloc[-1], df["Value"].iloc[-1]) plt.title(title) plt.get_current_fig_manager()

问题 This chart is built by Excel. How can I do the same using matplotlib? I mean how to add two formatters: years months. Now i use something like this: fig, ax = plt.subplots(1,1) ax.margins(x=0) ax.plot(list(df['Date']), list(df['Value']), color="g") ax.xaxis.set_major_locator(matplotlib.dates.YearLocator()) ax.xaxis.set_major_formatter(matplotlib.dates.DateFormatter('%Y')) plt.text(df["Date"].iloc[-1], df["Value"].iloc[-1], df["Value"].iloc[-1]) plt.title(title) plt.get_current_fig_manager()